diff --git a/.github/workflows/pr_local_integration_tests.yml b/.github/workflows/pr_local_integration_tests.yml
index 0787b8a3f2c..143cfe40973 100644
--- a/.github/workflows/pr_local_integration_tests.yml
+++ b/.github/workflows/pr_local_integration_tests.yml
@@ -42,6 +42,13 @@ jobs:
           enable-cache: true
       - name: Install dependencies
         run: make install-python-dependencies-ci
+      - name: Cache Hadoop tarball
+        uses: actions/cache@v4
+        with:
+          path: ~/hadoop-3.4.2.tar.gz
+          key: hadoop-3.4.2
+      - name: Install Hadoop dependencies
+        run: make install-hadoop-dependencies-ci
       - name: Test local integration tests
         if: ${{ always() }}  # this will guarantee that step won't be canceled and resources won't leak
         run: make test-python-integration-local
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 7b2cf7a551c..374e436b882 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,33 @@
 # Changelog
 
+# [0.56.0](https://github.com/feast-dev/feast/compare/v0.55.0...v0.56.0) (2025-10-27)
+
+
+### Bug Fixes
+
+* Add mode field to Transformation proto for proper serialization ([2390d2e](https://github.com/feast-dev/feast/commit/2390d2ea654e299fc74f697212542b755f3b4938))
+* Date wise remote offline store historical data retrieval  ([#5686](https://github.com/feast-dev/feast/issues/5686)) ([949ba3d](https://github.com/feast-dev/feast/commit/949ba3dae420f82f493018113d1fd6de9e130a56))
+* Fix STRING type handling in on-demand feature views ([#5669](https://github.com/feast-dev/feast/issues/5669)) ([dfbb743](https://github.com/feast-dev/feast/commit/dfbb7433f059e6f0d1d4ef6c0ef65b63dac1c1ff))
+* Fixed torch install issue in CI ([366e5a8](https://github.com/feast-dev/feast/commit/366e5a8c8f8093eda840b667849c6d2e45fa56bb))
+* ODFV not getting counted in resource count ([1d640b6](https://github.com/feast-dev/feast/commit/1d640b6c8136c47a78887e4490a5b7ae677b7c99))
+* Skip tag updates if user do not have permissions ([#5673](https://github.com/feast-dev/feast/issues/5673)) ([0a951ce](https://github.com/feast-dev/feast/commit/0a951ce8d7f9b31490fa279339eacd444d2d2434))
+
+
+### Features
+
+* Add document of Go feature server. ([#5697](https://github.com/feast-dev/feast/issues/5697)) ([cbd1dde](https://github.com/feast-dev/feast/commit/cbd1dde9a0a6e5a3ec7e3520b6613d3818bcd842))
+* Add flexible commandArgs support for complete Feast CLI control ([#5678](https://github.com/feast-dev/feast/issues/5678)) ([6414924](https://github.com/feast-dev/feast/commit/64149246c1925e9f3dcac60d9ab629225c232261))
+* Add HDFS as a feature registry ([#5655](https://github.com/feast-dev/feast/issues/5655)) ([4c65872](https://github.com/feast-dev/feast/commit/4c65872ee6cf7e14ed14c8a8a7e141126027e575))
+* Add nodeSelector to service config ([#5675](https://github.com/feast-dev/feast/issues/5675)) ([9728cde](https://github.com/feast-dev/feast/commit/9728cde4d3cf4d22a790d3a3af2eba705b7a56d3))
+* Add OTEL based observability to the Go Feature Server ([#5685](https://github.com/feast-dev/feast/issues/5685)) ([f4afdad](https://github.com/feast-dev/feast/commit/f4afdad27c7fe92e9778e29ad08e4b227a3c17a4))
+* Added health endpoint for the UI ([#5665](https://github.com/feast-dev/feast/issues/5665)) ([3aec5d5](https://github.com/feast-dev/feast/commit/3aec5d5fd24540d10f07e79c081c2658ca35678c))
+* Added kuberay support ([e0b698d](https://github.com/feast-dev/feast/commit/e0b698d7b8733c8177ca053bc89defb01ebeb538))
+* Added support for filtering multi-projects ([#5688](https://github.com/feast-dev/feast/issues/5688)) ([eb0a86e](https://github.com/feast-dev/feast/commit/eb0a86eb81defb5ccb2407a0d5f2b2425bcb61c1))
+* Batch Embedding at scale for RAG with Ray ([cc2a46d](https://github.com/feast-dev/feast/commit/cc2a46d54c413ed52a9bf568588dd06096592c1f))
+* Optimize SQL entity handling without creating temporary tables ([#5695](https://github.com/feast-dev/feast/issues/5695)) ([aa2c838](https://github.com/feast-dev/feast/commit/aa2c8386253181145c4f314187e0873b96b2be59))
+* Support aggregation in odfv ([#5666](https://github.com/feast-dev/feast/issues/5666)) ([564e965](https://github.com/feast-dev/feast/commit/564e9651dabea5458a77a8889920749cb1a6a5ed))
+* Support cache_mode for registries ([021e9ea](https://github.com/feast-dev/feast/commit/021e9ea759bfee0292c5f7c804119ed9a15d6a58))
+
 # [0.55.0](https://github.com/feast-dev/feast/compare/v0.54.0...v0.55.0) (2025-10-14)
 
 
diff --git a/Makefile b/Makefile
index e1d10404ded..6dc410b83b5 100644
--- a/Makefile
+++ b/Makefile
@@ -83,11 +83,28 @@ install-python-dependencies-minimal: ## Install minimal Python dependencies usin
 install-python-dependencies-ci: ## Install Python CI dependencies in system environment using uv
 	# Install CPU-only torch first to prevent CUDA dependency issues
 	pip uninstall torch torchvision -y || true
-	pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu --force-reinstall
-	uv pip sync --system sdk/python/requirements/py$(PYTHON_VERSION)-ci-requirements.txt
+	@if [ "$$(uname -s)" = "Linux" ]; then \
+		echo "Installing dependencies with torch CPU index for Linux..."; \
+		uv pip sync --system --extra-index-url https://download.pytorch.org/whl/cpu --index-strategy unsafe-best-match sdk/python/requirements/py$(PYTHON_VERSION)-ci-requirements.txt; \
+	else \
+		echo "Installing dependencies from PyPI for macOS..."; \
+		uv pip sync --system sdk/python/requirements/py$(PYTHON_VERSION)-ci-requirements.txt; \
+	fi
 	uv pip install --system --no-deps -e .
 
-# Used by multicloud/Dockerfile.dev
+# Used in github actions/ci
+install-hadoop-dependencies-ci: ## Install Hadoop dependencies
+	@if [ ! -f $$HOME/hadoop-3.4.2.tar.gz ]; then \
+		echo "Downloading Hadoop tarball..."; \
+		wget -q https://dlcdn.apache.org/hadoop/common/hadoop-3.4.2/hadoop-3.4.2.tar.gz -O $$HOME/hadoop-3.4.2.tar.gz; \
+	else \
+		echo "Using cached Hadoop tarball"; \
+	fi
+	@if [ ! -d $$HOME/hadoop ]; then \
+		echo "Extracting Hadoop tarball..."; \
+		tar -xzf $$HOME/hadoop-3.4.2.tar.gz -C $$HOME; \
+		mv $$HOME/hadoop-3.4.2 $$HOME/hadoop; \
+	fi
 install-python-ci-dependencies: ## Install Python CI dependencies in system environment using piptools
 	python -m piptools sync sdk/python/requirements/py$(PYTHON_VERSION)-ci-requirements.txt
 	pip install --no-deps -e .
@@ -146,6 +163,9 @@ test-python-integration: ## Run Python integration tests (CI)
 test-python-integration-local: ## Run Python integration tests (local dev mode)
 	FEAST_IS_LOCAL_TEST=True \
 	FEAST_LOCAL_ONLINE_CONTAINER=True \
+	HADOOP_HOME=$$HOME/hadoop \
+	CLASSPATH="$$( $$HADOOP_HOME/bin/hadoop classpath --glob ):$$CLASSPATH" \
+	HADOOP_USER_NAME=root \
 	python -m pytest --tb=short -v -n 8 --color=yes --integration --durations=10 --timeout=1200 --timeout_method=thread --dist loadgroup \
 		-k "not test_lambda_materialization and not test_snowflake_materialization" \
 		-m "not rbac_remote_integration_test" \
diff --git a/docs/README.md b/docs/README.md
index 02ecaefa10c..172111964b7 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -52,6 +52,11 @@ Feast helps ML platform/MLOps teams with DevOps experience productionize real-ti
 
 * *For AI Engineers*: Feast provides a platform designed to scale your AI applications by enabling seamless integration of richer data and facilitating fine-tuning. With Feast, you can optimize the performance of your AI models while ensuring a scalable and efficient data pipeline.
 
+
+![](assets/feast_persona_diagram.png)
+
+
+
 ## What Feast is not?
 
 ### Feast is not
diff --git a/docs/assets/feast_persona_diagram.png b/docs/assets/feast_persona_diagram.png
new file mode 100644
index 00000000000..005902a68c2
Binary files /dev/null and b/docs/assets/feast_persona_diagram.png differ
diff --git a/docs/reference/beta-on-demand-feature-view.md b/docs/reference/beta-on-demand-feature-view.md
index f45620a1cee..2482bbc1c8f 100644
--- a/docs/reference/beta-on-demand-feature-view.md
+++ b/docs/reference/beta-on-demand-feature-view.md
@@ -35,10 +35,40 @@ When defining an ODFV, you can specify the transformation mode using the `mode`
 
 ### Singleton Transformations in Native Python Mode
 
-Native Python mode supports transformations on singleton dictionaries by setting `singleton=True`. This allows you to 
-write transformation functions that operate on a single row at a time, making the code more intuitive and aligning with 
+Native Python mode supports transformations on singleton dictionaries by setting `singleton=True`. This allows you to
+write transformation functions that operate on a single row at a time, making the code more intuitive and aligning with
 how data scientists typically think about data transformations.
 
+## Aggregations
+
+On Demand Feature Views support aggregations that compute aggregate statistics over groups of rows. When using aggregations, data is grouped by entity columns (e.g., `driver_id`) and aggregated before being passed to the transformation function.
+
+**Important**: Aggregations and transformations are mutually exclusive. When aggregations are specified, they replace the transformation function.
+
+### Usage
+
+```python
+from feast import Aggregation
+from datetime import timedelta
+
+@on_demand_feature_view(
+    sources=[driver_hourly_stats_view],
+    schema=[
+        Field(name="total_trips", dtype=Int64),
+        Field(name="avg_rating", dtype=Float64),
+    ],
+    aggregations=[
+        Aggregation(column="trips", function="sum"),
+        Aggregation(column="rating", function="mean"),
+    ],
+)
+def driver_aggregated_stats(inputs):
+    # No transformation function needed when using aggregations
+    pass
+```
+
+Aggregated columns are automatically named using the pattern `{function}_{column}` (e.g., `sum_trips`, `mean_rating`).
+
 ## Example
 See [https://github.com/feast-dev/on-demand-feature-views-demo](https://github.com/feast-dev/on-demand-feature-views-demo) for an example on how to use on demand feature views.
 
diff --git a/docs/reference/compute-engine/ray.md b/docs/reference/compute-engine/ray.md
index 4ecc449e40b..5547901b873 100644
--- a/docs/reference/compute-engine/ray.md
+++ b/docs/reference/compute-engine/ray.md
@@ -62,11 +62,22 @@ batch_engine:
 | `max_parallelism_multiplier` | int | 2 | Parallelism as multiple of CPU cores |
 | `target_partition_size_mb` | int | 64 | Target partition size (MB) |
 | `window_size_for_joins` | string | "1H" | Time window for distributed joins |
-| `ray_address` | string | None | Ray cluster address (None = local Ray) |
+| `ray_address` | string | None | Ray cluster address (triggers REMOTE mode) |
+| `use_kuberay` | boolean | None | Enable KubeRay mode (overrides ray_address) |
+| `kuberay_conf` | dict | None | **KubeRay configuration dict** with keys: `cluster_name` (required), `namespace` (default: "default"), `auth_token`, `auth_server`, `skip_tls` (default: false) |
+| `enable_ray_logging` | boolean | false | Enable Ray progress bars and logging |
 | `enable_distributed_joins` | boolean | true | Enable distributed joins for large datasets |
 | `staging_location` | string | None | Remote path for batch materialization jobs |
-| `ray_conf` | dict | None | Ray configuration parameters |
-| `execution_timeout_seconds` | int | None | Timeout for job execution in seconds |
+| `ray_conf` | dict | None | Ray configuration parameters (memory, CPU limits) |
+
+### Mode Detection Precedence
+
+The Ray compute engine automatically detects the execution mode:
+
+1. **Environment Variables** → KubeRay mode (if `FEAST_RAY_USE_KUBERAY=true`)
+2. **Config `kuberay_conf`** → KubeRay mode
+3. **Config `ray_address`** → Remote mode
+4. **Default** → Local mode
 
 ## Usage Examples
 
diff --git a/docs/reference/data-sources/trino.md b/docs/reference/data-sources/trino.md
index 74c8c3cc956..5448726533c 100644
--- a/docs/reference/data-sources/trino.md
+++ b/docs/reference/data-sources/trino.md
@@ -20,8 +20,8 @@ from feast.infra.offline_stores.contrib.trino_offline_store.trino_source import
 )
 
 driver_hourly_stats = TrinoSource(
-    event_timestamp_column="event_timestamp",
-    table_ref="feast.driver_stats",
+    timestamp_field="event_timestamp",
+    table="feast.driver_stats",
     created_timestamp_column="created",
 )
 ```
diff --git a/docs/reference/feature-servers/go-feature-server.md b/docs/reference/feature-servers/go-feature-server.md
new file mode 100644
index 00000000000..fafe3fa917f
--- /dev/null
+++ b/docs/reference/feature-servers/go-feature-server.md
@@ -0,0 +1,54 @@
+# Go feature server (Alpha)
+
+## Overview
+The Go feature server is an HTTP/gRPC endpoint that serves features. It is written in Go.
+
+## Configuration of `feature_store.yaml`
+The current Go feature server needs a Python based feature Transformation service support. Please refer to the following code as an example:
+```
+# -*- coding: utf-8 -*-
+from feast.feature_store import FeatureStore
+
+
+def main():
+    # Init the Feature Store
+    store = FeatureStore(repo_path="./feature_repo/")
+
+    # Start the feature transformation server
+    # default port is 6569
+    store.serve_transformations(6569)
+
+if __name__ == "__main__":
+    main()
+```
+At the same time, we need to configure the `feature_store.yaml` as following:
+
+```
+...
+entity_key_serialization_version: 3
+feature_server:
+    type: local
+    transformation_service_endpoint: "localhost:6569"
+...
+```
+## Supported APIs
+Here is the list of supported APIs:
+| Method | API | Comment |
+|:---: | :---: | :---: |
+| POST   | /get-online-features | Retrieve features of one or many entities |
+| GET    | /health              | Status of the Go Feature Server |
+
+## OTEL based Observability
+The Go feature server support [OTEL](https://opentelemetry.io/) based Observabilities.
+To enable it, we need to set the global env `ENABLE_OTEL_TRACING` to `"true"` (as a string type!) in the container or your local OS.
+```
+export ENABLE_OTEL_TRACING='true'
+```
+There are example OTEL infra setup under the `/go/infra/docker/otel` folder.
+
+## Demo
+Please check the Reference[2] for a local demo of Go feature server. If you want to see a real world example of applying Go feature server in Production, please check Reference[1].
+
+## Reference
+1. [Expedia Group's Go Feature Server Implementation (in Production)](https://github.com/EXPEbdodla/feast)
+2. [A Go Feature server demo from Feast](https://github.com/feast-dev/feast-credit-score-local-tutorial)
\ No newline at end of file
diff --git a/docs/reference/offline-stores/ray.md b/docs/reference/offline-stores/ray.md
index 58f62c34ece..a46102ee132 100644
--- a/docs/reference/offline-stores/ray.md
+++ b/docs/reference/offline-stores/ray.md
@@ -9,10 +9,11 @@ The Ray offline store is a data I/O implementation that leverages [Ray](https://
 
 The Ray offline store provides:
 - Ray-based data reading from file sources (Parquet, CSV, etc.)
-- Support for both local and distributed Ray clusters
+- Support for local, remote, and KubeRay (Kubernetes-managed) clusters
 - Integration with various storage backends (local files, S3, GCS, HDFS)
 - Efficient data filtering and column selection
 - Timestamp-based data processing with timezone awareness
+- Enterprise-ready KubeRay cluster support via CodeFlare SDK
 
 
 ## Functionality Matrix
@@ -59,9 +60,15 @@ For complex feature processing, historical feature retrieval, and distributed jo
 
 ## Configuration
 
-The Ray offline store can be configured in your `feature_store.yaml` file. Below are two main configuration patterns:
+The Ray offline store can be configured in your `feature_store.yaml` file. It supports **three execution modes**:
 
-### Basic Ray Offline Store
+1. **LOCAL**: Ray runs locally on the same machine (default)
+2. **REMOTE**: Connects to a remote Ray cluster via `ray_address`
+3. **KUBERAY**: Connects to Ray clusters on Kubernetes via CodeFlare SDK
+
+### Execution Modes
+
+#### Local Mode (Default)
 
 For simple data I/O operations without distributed processing:
 
@@ -72,7 +79,44 @@ provider: local
 offline_store:
     type: ray
     storage_path: data/ray_storage        # Optional: Path for storing datasets
-    ray_address: localhost:10001          # Optional: Ray cluster address
+```
+
+#### Remote Ray Cluster
+
+Connect to an existing Ray cluster:
+
+```yaml
+offline_store:
+    type: ray
+    storage_path: s3://my-bucket/feast-data
+    ray_address: "ray://my-cluster.example.com:10001"
+```
+
+#### KubeRay Cluster (Kubernetes)
+
+Connect to Ray clusters on Kubernetes using CodeFlare SDK:
+
+```yaml
+offline_store:
+    type: ray
+    storage_path: s3://my-bucket/feast-data
+    use_kuberay: true
+    kuberay_conf:
+        cluster_name: "feast-ray-cluster"
+        namespace: "feast-system"
+        auth_token: "${RAY_AUTH_TOKEN}"
+        auth_server: "https://api.openshift.com:6443"
+        skip_tls: false
+    enable_ray_logging: false
+```
+
+**Environment Variables** (alternative to config file):
+```bash
+export FEAST_RAY_USE_KUBERAY=true
+export FEAST_RAY_CLUSTER_NAME=feast-ray-cluster
+export FEAST_RAY_AUTH_TOKEN=your-token
+export FEAST_RAY_AUTH_SERVER=https://api.openshift.com:6443
+export FEAST_RAY_NAMESPACE=feast-system
 ```
 
 ### Ray Offline Store + Compute Engine
@@ -175,8 +219,29 @@ batch_engine:
 |--------|------|---------|-------------|
 | `type` | string | Required | Must be `feast.offline_stores.contrib.ray_offline_store.ray.RayOfflineStore` or `ray` |
 | `storage_path` | string | None | Path for storing temporary files and datasets |
-| `ray_address` | string | None | Address of the Ray cluster (e.g., "localhost:10001") |
+| `ray_address` | string | None | Ray cluster address (triggers REMOTE mode, e.g., "ray://host:10001") |
+| `use_kuberay` | boolean | None | Enable KubeRay mode (overrides ray_address) |
+| `kuberay_conf` | dict | None | **KubeRay configuration dict** with keys: `cluster_name` (required), `namespace` (default: "default"), `auth_token`, `auth_server`, `skip_tls` (default: false) |
+| `enable_ray_logging` | boolean | false | Enable Ray progress bars and verbose logging |
 | `ray_conf` | dict | None | Ray initialization parameters for resource management (e.g., memory, CPU limits) |
+| `broadcast_join_threshold_mb` | int | 100 | Size threshold for broadcast joins (MB) |
+| `enable_distributed_joins` | boolean | true | Enable distributed joins for large datasets |
+| `max_parallelism_multiplier` | int | 2 | Parallelism as multiple of CPU cores |
+| `target_partition_size_mb` | int | 64 | Target partition size (MB) |
+| `window_size_for_joins` | string | "1H" | Time window for distributed joins |
+
+#### Mode Detection Precedence
+
+The Ray offline store automatically detects the execution mode using the following precedence:
+
+1. **Environment Variables** (highest priority)
+   - `FEAST_RAY_USE_KUBERAY`, `FEAST_RAY_CLUSTER_NAME`, etc.
+2. **Config `kuberay_conf`**
+   - If present → KubeRay mode
+3. **Config `ray_address`**
+   - If present → Remote mode
+4. **Default**
+   - Local mode (lowest priority)
 
 #### Ray Compute Engine Options
 
@@ -385,6 +450,8 @@ job.persist(hdfs_storage, allow_overwrite=True)
 
 ### Using Ray Cluster
 
+#### Standard Ray Cluster
+
 To use Ray in cluster mode for distributed data access:
 
 1. Start a Ray cluster:
@@ -406,6 +473,53 @@ offline_store:
 ray start --address='head-node-ip:10001'
 ```
 
+#### KubeRay Cluster (Kubernetes)
+
+To use Feast with Ray clusters on Kubernetes via CodeFlare SDK:
+
+**Prerequisites:**
+- KubeRay cluster deployed on Kubernetes
+- CodeFlare SDK installed: `pip install codeflare-sdk`
+- Access credentials for the Kubernetes cluster
+
+**Configuration:**
+
+1. Using configuration file:
+```yaml
+offline_store:
+    type: ray
+    use_kuberay: true
+    storage_path: s3://my-bucket/feast-data
+    kuberay_conf:
+        cluster_name: "feast-ray-cluster"
+        namespace: "feast-system"
+        auth_token: "${RAY_AUTH_TOKEN}"
+        auth_server: "https://api.openshift.com:6443"
+        skip_tls: false
+    enable_ray_logging: false
+```
+
+2. Using environment variables:
+```bash
+export FEAST_RAY_USE_KUBERAY=true
+export FEAST_RAY_CLUSTER_NAME=feast-ray-cluster
+export FEAST_RAY_AUTH_TOKEN=your-k8s-token
+export FEAST_RAY_AUTH_SERVER=https://api.openshift.com:6443
+export FEAST_RAY_NAMESPACE=feast-system
+export FEAST_RAY_SKIP_TLS=false
+
+# Then use standard Feast code
+python your_feast_script.py
+```
+
+**Features:**
+- The CodeFlare SDK handles cluster connection and authentication
+- Automatic TLS certificate management
+- Authentication with Kubernetes clusters
+- Namespace isolation
+- Secure communication between client and Ray cluster
+- Automatic cluster discovery
+
 ### Data Source Validation
 
 The Ray offline store validates data sources to ensure compatibility:
diff --git a/docs/reference/registries/README.md b/docs/reference/registries/README.md
index ac0f58e6135..01671cf2212 100644
--- a/docs/reference/registries/README.md
+++ b/docs/reference/registries/README.md
@@ -26,6 +26,10 @@ Please see [Registry](../../getting-started/components/registry.md) for a concep
 [snowflake.md](snowflake.md)
 {% endcontent-ref %}
 
+{% content-ref url="hdfs.md" %}
+[hdfs.md](hdfs.md)
+{% endcontent-ref %}
+
 {% content-ref url="remote.md" %}
 [remote.md](remote.md)
 {% endcontent-ref %}
diff --git a/docs/reference/registries/hdfs.md b/docs/reference/registries/hdfs.md
new file mode 100644
index 00000000000..c6f6b641aff
--- /dev/null
+++ b/docs/reference/registries/hdfs.md
@@ -0,0 +1,42 @@
+# HDFS Registry
+
+## Description
+
+HDFS registry provides support for storing the protobuf representation of your feature store objects (data sources, feature views, feature services, etc.) in Hadoop Distributed File System (HDFS).
+
+While it can be used in production, there are still inherent limitations with a file-based registries, since changing a single field in the registry requires re-writing the whole registry file. With multiple concurrent writers, this presents a risk of data loss, or bottlenecks writes to the registry since all changes have to be serialized (e.g. when running materialization for multiple feature views or time ranges concurrently).
+
+### Pre-requisites
+
+The HDFS registry requires Hadoop 3.3+ to be installed and the `HADOOP_HOME` environment variable set.
+
+### Authentication and User Configuration
+
+The HDFS registry is using `pyarrow.fs.HadoopFileSystem` and **does not** support specifying HDFS users or Kerberos credentials directly in the `feature_store.yaml` configuration. It relies entirely on the Hadoop and system environment configuration available to the process running Feast.
+
+By default, `pyarrow.fs.HadoopFileSystem` inherits authentication from the underlying Hadoop client libraries and environment variables, such as:
+
+- `HADOOP_USER_NAME`
+- `KRB5CCNAME`
+- `hadoop.security.authentication`
+- Any other relevant properties in `core-site.xml` and `hdfs-site.xml`
+
+For more information, refer to:
+- [pyarrow.fs.HadoopFileSystem API Reference](https://arrow.apache.org/docs/python/generated/pyarrow.fs.HadoopFileSystem.html)
+- [Hadoop Security: Simple & Kerberos Authentication](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-common/SecureMode.html)
+
+## Example
+
+An example of how to configure this would be:
+
+{% code title="feature_store.yaml" %}
+```yaml
+project: feast_hdfs
+registry:
+  path: hdfs://[YOUR NAMENODE HOST]:[YOUR NAMENODE PORT]/[PATH TO REGISTRY]/registry.pb
+  cache_ttl_seconds: 60
+online_store: null
+offline_store: null
+```
+{% endcode %}
+
diff --git a/go.mod b/go.mod
index 91ab0c05559..a097aa67719 100644
--- a/go.mod
+++ b/go.mod
@@ -1,8 +1,8 @@
 module github.com/feast-dev/feast
 
-go 1.23
+go 1.24.0
 
-toolchain go1.23.12
+toolchain go1.24.4
 
 require (
 	github.com/apache/arrow/go/v17 v17.0.0
@@ -19,10 +19,16 @@ require (
 	github.com/roberson-io/mmh3 v0.0.0-20190729202758-fdfce3ba6225
 	github.com/rs/zerolog v1.33.0
 	github.com/spaolacci/murmur3 v1.1.0
-	github.com/stretchr/testify v1.9.0
-	google.golang.org/genproto/googleapis/rpc v0.0.0-20240903143218-8af14fe29dc1
-	google.golang.org/grpc v1.67.0
-	google.golang.org/protobuf v1.34.2
+	github.com/stretchr/testify v1.11.1
+	go.opentelemetry.io/otel v1.38.0
+	go.opentelemetry.io/otel/exporters/otlp/otlptrace v1.38.0
+	go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracehttp v1.38.0
+	go.opentelemetry.io/otel/sdk v1.38.0
+	go.opentelemetry.io/otel/trace v1.38.0
+	golang.org/x/sync v0.17.0
+	google.golang.org/genproto/googleapis/rpc v0.0.0-20250825161204-c5933d9347a5
+	google.golang.org/grpc v1.75.0
+	google.golang.org/protobuf v1.36.8
 )
 
 require (
@@ -45,12 +51,16 @@ require (
 	github.com/aws/aws-sdk-go-v2/service/ssooidc v1.30.1 // indirect
 	github.com/aws/aws-sdk-go-v2/service/sts v1.33.19 // indirect
 	github.com/aws/smithy-go v1.22.2 // indirect
+	github.com/cenkalti/backoff/v5 v5.0.3 // indirect
 	github.com/cespare/xxhash/v2 v2.3.0 // indirect
 	github.com/davecgh/go-spew v1.1.2-0.20180830191138-d8f796af33cc // indirect
 	github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f // indirect
+	github.com/go-logr/logr v1.4.3 // indirect
+	github.com/go-logr/stdr v1.2.2 // indirect
 	github.com/goccy/go-json v0.10.3 // indirect
 	github.com/golang/snappy v0.0.4 // indirect
 	github.com/google/flatbuffers v24.3.25+incompatible // indirect
+	github.com/grpc-ecosystem/grpc-gateway/v2 v2.27.2 // indirect
 	github.com/klauspost/asmfmt v1.3.2 // indirect
 	github.com/klauspost/compress v1.17.9 // indirect
 	github.com/klauspost/cpuid/v2 v2.2.8 // indirect
@@ -62,14 +72,17 @@ require (
 	github.com/pmezard/go-difflib v1.0.1-0.20181226105442-5d4384ee4fb2 // indirect
 	github.com/stretchr/objx v0.5.2 // indirect
 	github.com/zeebo/xxh3 v1.0.2 // indirect
+	go.opentelemetry.io/auto/sdk v1.1.0 // indirect
+	go.opentelemetry.io/otel/metric v1.38.0 // indirect
+	go.opentelemetry.io/proto/otlp v1.7.1 // indirect
 	golang.org/x/exp v0.0.0-20240909161429-701f63a606c0 // indirect
-	golang.org/x/mod v0.21.0 // indirect
-	golang.org/x/net v0.29.0 // indirect
-	golang.org/x/sync v0.8.0 // indirect
-	golang.org/x/sys v0.25.0 // indirect
-	golang.org/x/text v0.18.0 // indirect
-	golang.org/x/tools v0.25.0 // indirect
+	golang.org/x/mod v0.26.0 // indirect
+	golang.org/x/net v0.43.0 // indirect
+	golang.org/x/sys v0.35.0 // indirect
+	golang.org/x/text v0.28.0 // indirect
+	golang.org/x/tools v0.35.0 // indirect
 	golang.org/x/xerrors v0.0.0-20240903120638-7835f813f4da // indirect
+	google.golang.org/genproto/googleapis/api v0.0.0-20250825161204-c5933d9347a5 // indirect
 	gopkg.in/yaml.v2 v2.4.0 // indirect
 	gopkg.in/yaml.v3 v3.0.1 // indirect
 )
diff --git a/go.sum b/go.sum
index 7778a906ecd..f2530758915 100644
--- a/go.sum
+++ b/go.sum
@@ -6,8 +6,6 @@ github.com/apache/arrow/go/v17 v17.0.0 h1:RRR2bdqKcdbss9Gxy2NS/hK8i4LDMh23L6BbkN
 github.com/apache/arrow/go/v17 v17.0.0/go.mod h1:jR7QHkODl15PfYyjM2nU+yTLScZ/qfj7OSUZmJ8putc=
 github.com/apache/thrift v0.21.0 h1:tdPmh/ptjE1IJnhbhrcl2++TauVjy242rkV/UzJChnE=
 github.com/apache/thrift v0.21.0/go.mod h1:W1H8aR/QRtYNvrPeFXBtobyRkd0/YVhTc6i07XIAgDw=
-github.com/aws/aws-sdk-go-v2 v1.36.3 h1:mJoei2CxPutQVxaATCzDUjcZEjVRdpsiiXi2o38yqWM=
-github.com/aws/aws-sdk-go-v2 v1.36.3/go.mod h1:LLXuLpgzEbD766Z5ECcRmi8AzSwfZItDtmABVkRLGzg=
 github.com/aws/aws-sdk-go-v2 v1.36.4 h1:GySzjhVvx0ERP6eyfAbAuAXLtAda5TEy19E5q5W8I9E=
 github.com/aws/aws-sdk-go-v2 v1.36.4/go.mod h1:LLXuLpgzEbD766Z5ECcRmi8AzSwfZItDtmABVkRLGzg=
 github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.10 h1:zAybnyUQXIZ5mok5Jqwlf58/TFE7uvd3IAsa1aF9cXs=
@@ -18,12 +16,8 @@ github.com/aws/aws-sdk-go-v2/credentials v1.17.67 h1:9KxtdcIA/5xPNQyZRgUSpYOE6j9
 github.com/aws/aws-sdk-go-v2/credentials v1.17.67/go.mod h1:p3C44m+cfnbv763s52gCqrjaqyPikj9Sg47kUVaNZQQ=
 github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30 h1:x793wxmUWVDhshP8WW2mlnXuFrO4cOd3HLBroh1paFw=
 github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30/go.mod h1:Jpne2tDnYiFascUEs2AWHJL9Yp7A5ZVy3TNyxaAjD6M=
-github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.34 h1:ZK5jHhnrioRkUNOc+hOgQKlUL5JeC3S6JgLxtQ+Rm0Q=
-github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.34/go.mod h1:p4VfIceZokChbA9FzMbRGz5OV+lekcVtHlPKEO0gSZY=
 github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.35 h1:o1v1VFfPcDVlK3ll1L5xHsaQAFdNtZ5GXnNR7SwueC4=
 github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.35/go.mod h1:rZUQNYMNG+8uZxz9FOerQJ+FceCiodXvixpeRtdESrU=
-github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.34 h1:SZwFm17ZUNNg5Np0ioo/gq8Mn6u9w19Mri8DnJ15Jf0=
-github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.34/go.mod h1:dFZsC0BLo346mvKQLWmoJxT+Sjp+qcVR1tRVHQGOH9Q=
 github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.35 h1:R5b82ubO2NntENm3SAm0ADME+H630HomNJdgv+yZ3xw=
 github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.35/go.mod h1:FuA+nmgMRfkzVKYDNEqQadvEMxtxl9+RLT9ribCwEMs=
 github.com/aws/aws-sdk-go-v2/internal/ini v1.8.3 h1:bIqFDwgGXXN1Kpp99pDOdKMTTb5d2KyU5X/BZxjOkRo=
@@ -56,6 +50,8 @@ github.com/bsm/ginkgo/v2 v2.12.0 h1:Ny8MWAHyOepLGlLKYmXG4IEkioBysk6GpaRTLC8zwWs=
 github.com/bsm/ginkgo/v2 v2.12.0/go.mod h1:SwYbGRRDovPVboqFv0tPTcG1sN61LM1Z4ARdbAV9g4c=
 github.com/bsm/gomega v1.27.10 h1:yeMWxP2pV2fG3FgAODIY8EiRE3dy0aeFYt4l7wh6yKA=
 github.com/bsm/gomega v1.27.10/go.mod h1:JyEr/xRbxbtgWNi8tIEVPUYZ5Dzef52k01W3YH0H+O0=
+github.com/cenkalti/backoff/v5 v5.0.3 h1:ZN+IMa753KfX5hd8vVaMixjnqRZ3y8CuJKRKj1xcsSM=
+github.com/cenkalti/backoff/v5 v5.0.3/go.mod h1:rkhZdG3JZukswDf7f0cwqPNk4K0sa+F97BxZthm/crw=
 github.com/cespare/xxhash/v2 v2.3.0 h1:UL815xU9SqsFlibzuggzjXhog7bL6oX9BbNZnL2UFvs=
 github.com/cespare/xxhash/v2 v2.3.0/go.mod h1:VGX0DQ3Q6kWi7AoAeZDth3/j3BFtOZR5XLFGgcrjCOs=
 github.com/coreos/go-systemd/v22 v22.5.0/go.mod h1:Y58oyj3AT4RCenI/lSvhwexgC+NSVTIJ3seZv2GcEnc=
@@ -65,6 +61,11 @@ github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f h1:lO4WD4F/r
 github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f/go.mod h1:cuUVRXasLTGF7a8hSLbxyZXjz+1KgoB3wDUb6vlszIc=
 github.com/ghodss/yaml v1.0.0 h1:wQHKEahhL6wmXdzwWG11gIVCkOv05bNOh+Rxn0yngAk=
 github.com/ghodss/yaml v1.0.0/go.mod h1:4dBDuWmgqj2HViK6kFavaiC9ZROes6MMH2rRYeMEF04=
+github.com/go-logr/logr v1.2.2/go.mod h1:jdQByPbusPIv2/zmleS9BjJVeZ6kBagPoEUsqbVz/1A=
+github.com/go-logr/logr v1.4.3 h1:CjnDlHq8ikf6E492q6eKboGOC0T8CDaOvkHCIg8idEI=
+github.com/go-logr/logr v1.4.3/go.mod h1:9T104GzyrTigFIr8wt5mBrctHMim0Nb2HLGrmQ40KvY=
+github.com/go-logr/stdr v1.2.2 h1:hSWxHoqTgW2S2qGc0LTAI563KZ5YKYRhT3MFKZMbjag=
+github.com/go-logr/stdr v1.2.2/go.mod h1:mMo/vtBO5dYbehREoey6XUKy/eSumjCCveDpRre4VKE=
 github.com/goccy/go-json v0.10.3 h1:KZ5WoDbxAIgm2HNbYckL0se1fHD6rz5j4ywS6ebzDqA=
 github.com/goccy/go-json v0.10.3/go.mod h1:oq7eo15ShAhp70Anwd5lgX2pLfOS3QCiwU/PULtXL6M=
 github.com/godbus/dbus/v5 v5.0.4/go.mod h1:xhWf0FNVPg57R7Z0UbKHbJfkEywrmjJnf7w5xrFpKfA=
@@ -74,16 +75,22 @@ github.com/golang/snappy v0.0.4 h1:yAGX7huGHXlcLOEtBnF4w7FQwA26wojNCwOYAEhLjQM=
 github.com/golang/snappy v0.0.4/go.mod h1:/XxbfmMg8lxefKM7IXC3fBNl/7bRcc72aCRzEWrmP2Q=
 github.com/google/flatbuffers v24.3.25+incompatible h1:CX395cjN9Kke9mmalRoL3d81AtFUxJM+yDthflgJGkI=
 github.com/google/flatbuffers v24.3.25+incompatible/go.mod h1:1AeVuKshWv4vARoZatz6mlQ0JxURH0Kv5+zNeJKJCa8=
-github.com/google/go-cmp v0.6.0 h1:ofyhxvXcZhMsU5ulbFiLKl/XBFqE1GSq7atu8tAmTRI=
-github.com/google/go-cmp v0.6.0/go.mod h1:17dUlkBOakJ0+DkrSSNjCkIjxS6bF9zb3elmeNGIjoY=
+github.com/google/go-cmp v0.7.0 h1:wk8382ETsv4JYUZwIsn6YpYiWiBsYLSJiTsyBybVuN8=
+github.com/google/go-cmp v0.7.0/go.mod h1:pXiqmnSA92OHEEa9HXL2W4E7lf9JzCmGVUdgjX3N/iU=
 github.com/google/uuid v1.6.0 h1:NIvaJDMOsjHA8n1jAhLSgzrAzy1Hgr+hNrb57e+94F0=
 github.com/google/uuid v1.6.0/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
+github.com/grpc-ecosystem/grpc-gateway/v2 v2.27.2 h1:8Tjv8EJ+pM1xP8mK6egEbD1OgnVTyacbefKhmbLhIhU=
+github.com/grpc-ecosystem/grpc-gateway/v2 v2.27.2/go.mod h1:pkJQ2tZHJ0aFOVEEot6oZmaVEZcRme73eIFmhiVuRWs=
 github.com/klauspost/asmfmt v1.3.2 h1:4Ri7ox3EwapiOjCki+hw14RyKk201CN4rzyCJRFLpK4=
 github.com/klauspost/asmfmt v1.3.2/go.mod h1:AG8TuvYojzulgDAMCnYn50l/5QV3Bs/tp6j0HLHbNSE=
 github.com/klauspost/compress v1.17.9 h1:6KIumPrER1LHsvBVuDa0r5xaG0Es51mhhB9BQB2qeMA=
 github.com/klauspost/compress v1.17.9/go.mod h1:Di0epgTjJY877eYKx5yC51cX2A2Vl2ibi7bDH9ttBbw=
 github.com/klauspost/cpuid/v2 v2.2.8 h1:+StwCXwm9PdpiEkPyzBXIy+M9KUb4ODm0Zarf1kS5BM=
 github.com/klauspost/cpuid/v2 v2.2.8/go.mod h1:Lcz8mBdAVJIBVzewtcLocK12l3Y+JytZYpaMropDUws=
+github.com/kr/pretty v0.3.1 h1:flRD4NNwYAUpkphVc1HcthR4KEIFJ65n8Mw5qdRn3LE=
+github.com/kr/pretty v0.3.1/go.mod h1:hoEshYVHaxMs3cyo3Yncou5ZscifuDolrwPKZanG3xk=
+github.com/kr/text v0.2.0 h1:5Nx0Ya0ZqY2ygV366QzturHI13Jq95ApcVaJBhpS+AY=
+github.com/kr/text v0.2.0/go.mod h1:eLer722TekiGuMkidMxC/pM04lWEeraHUUmBw8l2grE=
 github.com/mattn/go-colorable v0.1.13 h1:fFA4WZxdEF4tXPZVKMLwD8oUnCTTo08duU7wxecdEvA=
 github.com/mattn/go-colorable v0.1.13/go.mod h1:7S9/ev0klgBDR4GtXTXX8a3vIGJpMovkB8vQcUbaXHg=
 github.com/mattn/go-isatty v0.0.16/go.mod h1:kYGgaQfpe5nmfYZH+SKPsOc2e4SrIfOl2e/yFXSvRLM=
@@ -106,6 +113,8 @@ github.com/redis/go-redis/v9 v9.6.1 h1:HHDteefn6ZkTtY5fGUE8tj8uy85AHk6zP7CpzIAM0
 github.com/redis/go-redis/v9 v9.6.1/go.mod h1:0C0c6ycQsdpVNQpxb1njEQIqkx5UcsM8FJCQLgE9+RA=
 github.com/roberson-io/mmh3 v0.0.0-20190729202758-fdfce3ba6225 h1:ZMsPCp7oYgjoIFt1c+sM2qojxZXotSYcMF8Ur9/LJlM=
 github.com/roberson-io/mmh3 v0.0.0-20190729202758-fdfce3ba6225/go.mod h1:XEESr+X1SY8ZSuc3jqsTlb3clCkqQJ4DcF3Qxv1N3PM=
+github.com/rogpeppe/go-internal v1.13.1 h1:KvO1DLK/DRN07sQ1LQKScxyZJuNnedQ5/wKSR38lUII=
+github.com/rogpeppe/go-internal v1.13.1/go.mod h1:uMEvuHeurkdAXX61udpOXGD/AzZDWNMNyH2VO9fmH0o=
 github.com/rs/xid v1.5.0/go.mod h1:trrq9SKmegXys3aeAKXMUTdJsYXVwGY3RLcfgqegfbg=
 github.com/rs/zerolog v1.33.0 h1:1cU2KZkvPxNyfgEmhHAz/1A9Bz+llsdYzklWFzgp0r8=
 github.com/rs/zerolog v1.33.0/go.mod h1:/7mN4D5sKwJLZQ2b/znpjC3/GQWY/xaDXUM0kKWRHss=
@@ -113,42 +122,65 @@ github.com/spaolacci/murmur3 v1.1.0 h1:7c1g84S4BPRrfL5Xrdp6fOJ206sU9y293DDHaoy0b
 github.com/spaolacci/murmur3 v1.1.0/go.mod h1:JwIasOWyU6f++ZhiEuf87xNszmSA2myDM2Kzu9HwQUA=
 github.com/stretchr/objx v0.5.2 h1:xuMeJ0Sdp5ZMRXx/aWO6RZxdr3beISkG5/G/aIRr3pY=
 github.com/stretchr/objx v0.5.2/go.mod h1:FRsXN1f5AsAjCGJKqEizvkpNtU+EGNCLh3NxZ/8L+MA=
-github.com/stretchr/testify v1.9.0 h1:HtqpIVDClZ4nwg75+f6Lvsy/wHu+3BoSGCbBAcpTsTg=
-github.com/stretchr/testify v1.9.0/go.mod h1:r2ic/lqez/lEtzL7wO/rwa5dbSLXVDPFyf8C91i36aY=
+github.com/stretchr/testify v1.11.1 h1:7s2iGBzp5EwR7/aIZr8ao5+dra3wiQyKjjFuvgVKu7U=
+github.com/stretchr/testify v1.11.1/go.mod h1:wZwfW3scLgRK+23gO65QZefKpKQRnfz6sD981Nm4B6U=
 github.com/zeebo/assert v1.3.0 h1:g7C04CbJuIDKNPFHmsk4hwZDO5O+kntRxzaUoNXj+IQ=
 github.com/zeebo/assert v1.3.0/go.mod h1:Pq9JiuJQpG8JLJdtkwrJESF0Foym2/D9XMU5ciN/wJ0=
 github.com/zeebo/xxh3 v1.0.2 h1:xZmwmqxHZA8AI603jOQ0tMqmBr9lPeFwGg6d+xy9DC0=
 github.com/zeebo/xxh3 v1.0.2/go.mod h1:5NWz9Sef7zIDm2JHfFlcQvNekmcEl9ekUZQQKCYaDcA=
+go.opentelemetry.io/auto/sdk v1.1.0 h1:cH53jehLUN6UFLY71z+NDOiNJqDdPRaXzTel0sJySYA=
+go.opentelemetry.io/auto/sdk v1.1.0/go.mod h1:3wSPjt5PWp2RhlCcmmOial7AvC4DQqZb7a7wCow3W8A=
+go.opentelemetry.io/otel v1.38.0 h1:RkfdswUDRimDg0m2Az18RKOsnI8UDzppJAtj01/Ymk8=
+go.opentelemetry.io/otel v1.38.0/go.mod h1:zcmtmQ1+YmQM9wrNsTGV/q/uyusom3P8RxwExxkZhjM=
+go.opentelemetry.io/otel/exporters/otlp/otlptrace v1.38.0 h1:GqRJVj7UmLjCVyVJ3ZFLdPRmhDUp2zFmQe3RHIOsw24=
+go.opentelemetry.io/otel/exporters/otlp/otlptrace v1.38.0/go.mod h1:ri3aaHSmCTVYu2AWv44YMauwAQc0aqI9gHKIcSbI1pU=
+go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracehttp v1.38.0 h1:aTL7F04bJHUlztTsNGJ2l+6he8c+y/b//eR0jjjemT4=
+go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracehttp v1.38.0/go.mod h1:kldtb7jDTeol0l3ewcmd8SDvx3EmIE7lyvqbasU3QC4=
+go.opentelemetry.io/otel/metric v1.38.0 h1:Kl6lzIYGAh5M159u9NgiRkmoMKjvbsKtYRwgfrA6WpA=
+go.opentelemetry.io/otel/metric v1.38.0/go.mod h1:kB5n/QoRM8YwmUahxvI3bO34eVtQf2i4utNVLr9gEmI=
+go.opentelemetry.io/otel/sdk v1.38.0 h1:l48sr5YbNf2hpCUj/FoGhW9yDkl+Ma+LrVl8qaM5b+E=
+go.opentelemetry.io/otel/sdk v1.38.0/go.mod h1:ghmNdGlVemJI3+ZB5iDEuk4bWA3GkTpW+DOoZMYBVVg=
+go.opentelemetry.io/otel/sdk/metric v1.38.0 h1:aSH66iL0aZqo//xXzQLYozmWrXxyFkBJ6qT5wthqPoM=
+go.opentelemetry.io/otel/sdk/metric v1.38.0/go.mod h1:dg9PBnW9XdQ1Hd6ZnRz689CbtrUp0wMMs9iPcgT9EZA=
+go.opentelemetry.io/otel/trace v1.38.0 h1:Fxk5bKrDZJUH+AMyyIXGcFAPah0oRcT+LuNtJrmcNLE=
+go.opentelemetry.io/otel/trace v1.38.0/go.mod h1:j1P9ivuFsTceSWe1oY+EeW3sc+Pp42sO++GHkg4wwhs=
+go.opentelemetry.io/proto/otlp v1.7.1 h1:gTOMpGDb0WTBOP8JaO72iL3auEZhVmAQg4ipjOVAtj4=
+go.opentelemetry.io/proto/otlp v1.7.1/go.mod h1:b2rVh6rfI/s2pHWNlB7ILJcRALpcNDzKhACevjI+ZnE=
+go.uber.org/goleak v1.3.0 h1:2K3zAYmnTNqV73imy9J1T3WC+gmCePx2hEGkimedGto=
+go.uber.org/goleak v1.3.0/go.mod h1:CoHD4mav9JJNrW/WLlf7HGZPjdw8EucARQHekz1X6bE=
 golang.org/x/exp v0.0.0-20240909161429-701f63a606c0 h1:e66Fs6Z+fZTbFBAxKfP3PALWBtpfqks2bwGcexMxgtk=
 golang.org/x/exp v0.0.0-20240909161429-701f63a606c0/go.mod h1:2TbTHSBQa924w8M6Xs1QcRcFwyucIwBGpK1p2f1YFFY=
-golang.org/x/mod v0.21.0 h1:vvrHzRwRfVKSiLrG+d4FMl/Qi4ukBCE6kZlTUkDYRT0=
-golang.org/x/mod v0.21.0/go.mod h1:6SkKJ3Xj0I0BrPOZoBy3bdMptDDU9oJrpohJ3eWZ1fY=
-golang.org/x/net v0.29.0 h1:5ORfpBpCs4HzDYoodCDBbwHzdR5UrLBZ3sOnUJmFoHo=
-golang.org/x/net v0.29.0/go.mod h1:gLkgy8jTGERgjzMic6DS9+SP0ajcu6Xu3Orq/SpETg0=
-golang.org/x/sync v0.8.0 h1:3NFvSEYkUoMifnESzZl15y791HH1qU2xm6eCJU5ZPXQ=
-golang.org/x/sync v0.8.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
+golang.org/x/mod v0.26.0 h1:EGMPT//Ezu+ylkCijjPc+f4Aih7sZvaAr+O3EHBxvZg=
+golang.org/x/mod v0.26.0/go.mod h1:/j6NAhSk8iQ723BGAUyoAcn7SlD7s15Dp9Nd/SfeaFQ=
+golang.org/x/net v0.43.0 h1:lat02VYK2j4aLzMzecihNvTlJNQUq316m2Mr9rnM6YE=
+golang.org/x/net v0.43.0/go.mod h1:vhO1fvI4dGsIjh73sWfUVjj3N7CA9WkKJNQm2svM6Jg=
+golang.org/x/sync v0.17.0 h1:l60nONMj9l5drqw6jlhIELNv9I0A4OFgRsG9k2oT9Ug=
+golang.org/x/sync v0.17.0/go.mod h1:9KTHXmSnoGruLpwFjVSX0lNNA75CykiMECbovNTZqGI=
 golang.org/x/sys v0.0.0-20220811171246-fbc7d0a398ab/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.5.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.6.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.12.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
-golang.org/x/sys v0.25.0 h1:r+8e+loiHxRqhXVl6ML1nO3l1+oFoWbnlu2Ehimmi34=
-golang.org/x/sys v0.25.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
-golang.org/x/text v0.18.0 h1:XvMDiNzPAl0jr17s6W9lcaIhGUfUORdGCNsuLmPG224=
-golang.org/x/text v0.18.0/go.mod h1:BuEKDfySbSR4drPmRPG/7iBdf8hvFMuRexcpahXilzY=
-golang.org/x/tools v0.25.0 h1:oFU9pkj/iJgs+0DT+VMHrx+oBKs/LJMV+Uvg78sl+fE=
-golang.org/x/tools v0.25.0/go.mod h1:/vtpO8WL1N9cQC3FN5zPqb//fRXskFHbLKk4OW1Q7rg=
+golang.org/x/sys v0.35.0 h1:vz1N37gP5bs89s7He8XuIYXpyY0+QlsKmzipCbUtyxI=
+golang.org/x/sys v0.35.0/go.mod h1:BJP2sWEmIv4KK5OTEluFJCKSidICx8ciO85XgH3Ak8k=
+golang.org/x/text v0.28.0 h1:rhazDwis8INMIwQ4tpjLDzUhx6RlXqZNPEM0huQojng=
+golang.org/x/text v0.28.0/go.mod h1:U8nCwOR8jO/marOQ0QbDiOngZVEBB7MAiitBuMjXiNU=
+golang.org/x/tools v0.35.0 h1:mBffYraMEf7aa0sB+NuKnuCy8qI/9Bughn8dC2Gu5r0=
+golang.org/x/tools v0.35.0/go.mod h1:NKdj5HkL/73byiZSJjqJgKn3ep7KjFkBOkR/Hps3VPw=
 golang.org/x/xerrors v0.0.0-20240903120638-7835f813f4da h1:noIWHXmPHxILtqtCOPIhSt0ABwskkZKjD3bXGnZGpNY=
 golang.org/x/xerrors v0.0.0-20240903120638-7835f813f4da/go.mod h1:NDW/Ps6MPRej6fsCIbMTohpP40sJ/P/vI1MoTEGwX90=
-gonum.org/v1/gonum v0.15.0 h1:2lYxjRbTYyxkJxlhC+LvJIx3SsANPdRybu1tGj9/OrQ=
-gonum.org/v1/gonum v0.15.0/go.mod h1:xzZVBJBtS+Mz4q0Yl2LJTk+OxOg4jiXZ7qBoM0uISGo=
-google.golang.org/genproto/googleapis/rpc v0.0.0-20240903143218-8af14fe29dc1 h1:pPJltXNxVzT4pK9yD8vR9X75DaWYYmLGMsEvBfFQZzQ=
-google.golang.org/genproto/googleapis/rpc v0.0.0-20240903143218-8af14fe29dc1/go.mod h1:UqMtugtsSgubUsoxbuAoiCXvqvErP7Gf0so0mK9tHxU=
-google.golang.org/grpc v1.67.0 h1:IdH9y6PF5MPSdAntIcpjQ+tXO41pcQsfZV2RxtQgVcw=
-google.golang.org/grpc v1.67.0/go.mod h1:1gLDyUQU7CTLJI90u3nXZ9ekeghjeM7pTDZlqFNg2AA=
-google.golang.org/protobuf v1.34.2 h1:6xV6lTsCfpGD21XK49h7MhtcApnLqkfYgPcdHftf6hg=
-google.golang.org/protobuf v1.34.2/go.mod h1:qYOHts0dSfpeUzUFpOMr/WGzszTmLH+DiWniOlNbLDw=
-gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405 h1:yhCVgyC4o1eVCa2tZl7eS0r+SDo693bJlVdllGtEeKM=
+gonum.org/v1/gonum v0.16.0 h1:5+ul4Swaf3ESvrOnidPp4GZbzf0mxVQpDCYUQE7OJfk=
+gonum.org/v1/gonum v0.16.0/go.mod h1:fef3am4MQ93R2HHpKnLk4/Tbh/s0+wqD5nfa6Pnwy4E=
+google.golang.org/genproto/googleapis/api v0.0.0-20250825161204-c5933d9347a5 h1:BIRfGDEjiHRrk0QKZe3Xv2ieMhtgRGeLcZQ0mIVn4EY=
+google.golang.org/genproto/googleapis/api v0.0.0-20250825161204-c5933d9347a5/go.mod h1:j3QtIyytwqGr1JUDtYXwtMXWPKsEa5LtzIFN1Wn5WvE=
+google.golang.org/genproto/googleapis/rpc v0.0.0-20250825161204-c5933d9347a5 h1:eaY8u2EuxbRv7c3NiGK0/NedzVsCcV6hDuU5qPX5EGE=
+google.golang.org/genproto/googleapis/rpc v0.0.0-20250825161204-c5933d9347a5/go.mod h1:M4/wBTSeyLxupu3W3tJtOgB14jILAS/XWPSSa3TAlJc=
+google.golang.org/grpc v1.75.0 h1:+TW+dqTd2Biwe6KKfhE5JpiYIBWq865PhKGSXiivqt4=
+google.golang.org/grpc v1.75.0/go.mod h1:JtPAzKiq4v1xcAB2hydNlWI2RnF85XXcV0mhKXr2ecQ=
+google.golang.org/protobuf v1.36.8 h1:xHScyCOEuuwZEc6UtSOvPbAT4zRh0xcNRYekJwfqyMc=
+google.golang.org/protobuf v1.36.8/go.mod h1:fuxRtAxBytpl4zzqUh6/eyUujkJdNiuEkXntxiD/uRU=
 gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
+gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c h1:Hei/4ADfdWqJk1ZMxUNpqntNwaWcugrBjAiHlqqRiVk=
+gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c/go.mod h1:JHkPIbrfpd72SG/EVd6muEfDQjcINNoR0C8j2r3qZ4Q=
 gopkg.in/yaml.v2 v2.4.0 h1:D8xgwECY7CYvx+Y2n4sBz93Jn9JRvxdiyyo8CTfuKaY=
 gopkg.in/yaml.v2 v2.4.0/go.mod h1:RDklbk79AGWmwhnvt/jBztapEOGDOx6ZbXqjP6csGnQ=
 gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
diff --git a/go/README.md b/go/README.md
index eebbfb7d62d..a8e381519a4 100644
--- a/go/README.md
+++ b/go/README.md
@@ -1,12 +1,113 @@
-[Update 10/31/2024] This Go feature server code is updated from the Expedia Group's forked Feast branch (https://github.com/ExpediaGroup/feast.git) on 10/22/2024. Thanks the engineers of the Expedia Groups who contributed and improved the Go feature server.  
+[Update 10/31/2024] This Go feature server code is updated from the Expedia Group's forked Feast branch (https://github.com/ExpediaGroup/feast.git) on 10/22/2024. Thanks the engineers of the Expedia Groups who contributed and improved the Go Feature Server.  
 
 
-This directory contains the Go logic that's executed by the `EmbeddedOnlineFeatureServer` from Python.
-
 ## Build and Run
 To build and run the Go Feature Server locally, create a feature_store.yaml file with necessary configurations and run below commands:
 
 ```bash
-    go build -o feast ./go/main.go
-    ./feast --type=http --port=8080
-```
\ No newline at end of file
+    go build -o feast-go ./go/main.go
+    # start the http server
+    ./feast-go --type=http --port=8080
+    # or start the gRPC server
+    #./feast-go --type=grpc  --port=[your-choice]
+```
+
+## OTEL based observability
+The OS level env variable `ENABLE_OTEL_TRACING=="true"/"false"` (string type) is used to enable/disable this service (with Tracing only).
+
+The default exporter URL is "http://localhost:4318". The default schema of sending data to collector is **HTTP**. Please refer the following two docs about the configuration of the OTEL exporter:  
+1. https://opentelemetry.io/docs/languages/sdk-configuration/otlp-exporter/  
+2. https://pkg.go.dev/go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracehttp#WithEndpoint  
+
+## List of files have OTEL observability code  
+1. internal/feast/transformation/transformation.go
+2. internal/feast/onlinestore/redisonlinestore.go
+3. internal/feast/server/grpc_server.go
+4. internal/feast/server/http_server.go
+5. internal/feast/server/server_commons.go
+6. internal/feast/featurestore.go
+
+## Example monitoring infra setup
+1. docker compose file to setup Prometheus, Jaeger, and OTEL-collector.  
+```yaml
+services:
+  prometheus:
+    image: prom/prometheus
+    volumes:
+      - ./prometheus.yaml:/etc/prometheus/prometheus.yaml
+    ports:
+      - 9090:9090   # web UI  http://localhost:9090
+  jaeger:
+    image: jaegertracing/all-in-one:latest
+    ports:
+      - 16686:16686  # Web UI: http://localhost:16686
+      - 14268:14268  # http based receiver
+      - 14250:14250  # gRPC based receiver
+  otel-collector:
+    image: otel/opentelemetry-collector-contrib
+    volumes:
+      - ./otel-collector-config.yaml:/etc/otelcol-contrib/config.yaml
+    ports:
+      #- 1888:1888 # pprof extension
+      - 8888:8888 # Prometheus metrics exposed by the Collector
+      - 8889:8889 # Prometheus exporter metrics
+      #- 13133:13133 # health_check extension
+      #- 4317:4317 # OTLP gRPC receiver
+      - 4318:4318 # OTLP http receiver
+      - 55679:55679 # zpages extension. check http://localhost:55679/debug/tracez
+    depends_on:
+      - jaeger
+      - prometheus
+```  
+2. OTEL collector configure file.  
+```yaml
+receivers:
+  otlp:
+    protocols:
+      http:
+        endpoint: 0.0.0.0:4318
+
+exporters:
+  prometheus:
+    endpoint: 0.0.0.0:8889
+    namespace: feast-go
+  otlp/jaeger:  # this is a gRPC based exporter. use "otelhttp" for http based exporter.
+    endpoint: jaeger:4317
+    tls:
+      insecure: true
+
+extensions:
+  zpages:
+    endpoint: 0.0.0.0:55679
+
+processors:
+  batch:
+
+service:
+  extensions: [zpages]
+  pipelines:
+    metrics:
+      receivers: [otlp]
+      exporters: [prometheus]
+    traces:
+      receivers: [otlp]
+      exporters: [otlp/jaeger]
+```
+3. Prometheus config.
+```yaml
+ #https://github.com/prometheus/prometheus/blob/release-3.6/config/testdata/conf.good.yml
+ scrape_configs:
+  - job_name: 'otel-collector'
+    scrape_interval: 1m
+    scrape_timeout: 30s # Increase this if needed
+    static_configs:
+      # Check the IP address of or Docker host network. 
+      # Refer: https://stackoverflow.com/questions/48546124/what-is-the-linux-equivalent-of-host-docker-internal
+      - targets: ['172.17.0.1:8888'] # Replace with the Collector's IP and port
+  - job_name: 'otel-collected'
+    scrape_interval: 1m
+    scrape_timeout: 30s # Increase this if needed
+    static_configs:
+      - targets: ['172.17.0.1:8889'] # Replace with the Collector's IP and port
+```
+4. Jaeger config file is not used in this setup.    
\ No newline at end of file
diff --git a/go/infra/docker/otel/compose.yaml b/go/infra/docker/otel/compose.yaml
new file mode 100644
index 00000000000..7872797d205
--- /dev/null
+++ b/go/infra/docker/otel/compose.yaml
@@ -0,0 +1,29 @@
+services:
+  prometheus:
+    image: prom/prometheus
+    volumes:
+      - ./prometheus.yaml:/etc/prometheus/prometheus.yaml
+    ports:
+      - 9090:9090
+  jaeger:
+    image: jaegertracing/all-in-one:latest
+    #volumes:
+    #  - ./jaeger.yaml:/jaeger/config.yaml
+    ports:
+      - 16686:16686  # Web UI: http://localhost:16686
+      - 14268:14268  # http based receiver
+      - 14250:14250  # gRPC based receiver
+  otel-collector:
+    image: otel/opentelemetry-collector-contrib
+    volumes:
+      - ./otel-collector-config.yaml:/etc/otelcol-contrib/config.yaml
+    ports:
+      #- 1888:1888 # pprof extension
+      - 8888:8888 # Prometheus metrics exposed by the Collector
+      - 8889:8889 # Prometheus exporter metrics
+      #- 13133:13133 # health_check extension
+      #- 4317:4317 # OTLP gRPC receiver
+      - 4318:4318 # OTLP http receiver
+      - 55679:55679 # zpages extension
+    depends_on:
+      - jaeger
\ No newline at end of file
diff --git a/go/infra/docker/otel/otel-collector-config.yaml b/go/infra/docker/otel/otel-collector-config.yaml
new file mode 100644
index 00000000000..92ecfe017ac
--- /dev/null
+++ b/go/infra/docker/otel/otel-collector-config.yaml
@@ -0,0 +1,31 @@
+receivers:
+  otlp:
+    protocols:
+      http:
+        endpoint: 0.0.0.0:4318
+
+exporters:
+  prometheus:
+    endpoint: 0.0.0.0:8889
+    namespace: feast-go
+  otlp/jaeger:
+    endpoint: jaeger:4317
+    tls:
+      insecure: true
+
+extensions:
+  zpages:
+    endpoint: 0.0.0.0:55679
+
+processors:
+  batch:
+
+service:
+  extensions: [zpages]
+  pipelines:
+    metrics:
+      receivers: [otlp]
+      exporters: [prometheus]
+    traces:
+      receivers: [otlp]
+      exporters: [otlp/jaeger]
\ No newline at end of file
diff --git a/go/infra/docker/otel/prometheus.yaml b/go/infra/docker/otel/prometheus.yaml
new file mode 100644
index 00000000000..8ab32f38870
--- /dev/null
+++ b/go/infra/docker/otel/prometheus.yaml
@@ -0,0 +1,14 @@
+ #https://github.com/prometheus/prometheus/blob/release-3.6/config/testdata/conf.good.yml
+ scrape_configs:
+  - job_name: 'otel-collector'
+    scrape_interval: 1m
+    scrape_timeout: 30s # Increase this if needed
+    static_configs:
+      # Check the IP address of or Docker host network. 
+      # Refer: https://stackoverflow.com/questions/48546124/what-is-the-linux-equivalent-of-host-docker-internal
+      - targets: ['172.17.0.1:8888'] # Replace with the Collector's IP and port
+  - job_name: 'otel-collected'
+    scrape_interval: 1m
+    scrape_timeout: 30s # Increase this if needed
+    static_configs:
+      - targets: ['172.17.0.1:8889'] # Replace with the Collector's IP and port
\ No newline at end of file
diff --git a/go/internal/feast/featurestore.go b/go/internal/feast/featurestore.go
index abe1d195def..f6abd50e3d1 100644
--- a/go/internal/feast/featurestore.go
+++ b/go/internal/feast/featurestore.go
@@ -7,6 +7,7 @@ import (
 	"github.com/apache/arrow/go/v17/arrow/memory"
 
 	//"gopkg.in/DataDog/dd-trace-go.v1/ddtrace/tracer"
+	"go.opentelemetry.io/otel"
 
 	"github.com/feast-dev/feast/go/internal/feast/model"
 	"github.com/feast-dev/feast/go/internal/feast/onlineserving"
@@ -17,6 +18,8 @@ import (
 	prototypes "github.com/feast-dev/feast/go/protos/feast/types"
 )
 
+var tracer = otel.Tracer("github.com/feast-dev/feast/go/feast")
+
 type FeatureStore struct {
 	config                 *registry.RepoConfig
 	registry               *registry.Registry
@@ -322,8 +325,8 @@ func (fs *FeatureStore) readFromOnlineStore(ctx context.Context, entityRows []*p
 	requestedFeatureNames []string,
 ) ([][]onlinestore.FeatureData, error) {
 	// Create a Datadog span from context
-	//span, _ := tracer.StartSpanFromContext(ctx, "fs.readFromOnlineStore")
-	//defer span.Finish()
+	ctx, span := tracer.Start(ctx, "fs.readFromOnlineStore")
+	defer span.End()
 
 	numRows := len(entityRows)
 	entityRowsValue := make([]*prototypes.EntityKey, numRows)
diff --git a/go/internal/feast/onlinestore/redisonlinestore.go b/go/internal/feast/onlinestore/redisonlinestore.go
index 3fa6cf580c7..e39b3505710 100644
--- a/go/internal/feast/onlinestore/redisonlinestore.go
+++ b/go/internal/feast/onlinestore/redisonlinestore.go
@@ -11,7 +11,7 @@ import (
 	"strings"
 
 	"github.com/feast-dev/feast/go/internal/feast/registry"
-	//"gopkg.in/DataDog/dd-trace-go.v1/ddtrace/tracer"
+	"go.opentelemetry.io/otel"
 
 	"github.com/redis/go-redis/v9"
 	"github.com/spaolacci/murmur3"
@@ -24,6 +24,8 @@ import (
 	//redistrace "gopkg.in/DataDog/dd-trace-go.v1/contrib/redis/go-redis.v9"
 )
 
+var tracer = otel.Tracer("github.com/feast-dev/feast/go/onlinestore")
+
 type redisType int
 
 const (
@@ -211,8 +213,8 @@ func (r *RedisOnlineStore) buildRedisKeys(entityKeys []*types.EntityKey) ([]*[]b
 }
 
 func (r *RedisOnlineStore) OnlineRead(ctx context.Context, entityKeys []*types.EntityKey, featureViewNames []string, featureNames []string) ([][]FeatureData, error) {
-	//span, _ := tracer.StartSpanFromContext(ctx, "redis.OnlineRead")
-	//defer span.Finish()
+	ctx, span := tracer.Start(ctx, "redis.OnlineRead")
+	defer span.End()
 
 	featureCount := len(featureNames)
 	featureViewIndices, indicesFeatureView, index := r.buildFeatureViewIndices(featureViewNames, featureNames)
diff --git a/go/internal/feast/server/grpc_server.go b/go/internal/feast/server/grpc_server.go
index d5e18b1c9ef..ab76aa554ca 100644
--- a/go/internal/feast/server/grpc_server.go
+++ b/go/internal/feast/server/grpc_server.go
@@ -9,7 +9,7 @@ import (
 	prototypes "github.com/feast-dev/feast/go/protos/feast/types"
 	"github.com/feast-dev/feast/go/types"
 	"github.com/google/uuid"
-	//"gopkg.in/DataDog/dd-trace-go.v1/ddtrace/tracer"
+
 )
 
 const feastServerVersion = "0.0.1"
@@ -34,16 +34,16 @@ func (s *grpcServingServiceServer) GetFeastServingInfo(ctx context.Context, requ
 // Metadata contains feature names that corresponds to the number of rows in response.Results.
 // Results contains values including the value of the feature, the event timestamp, and feature status in a columnar format.
 func (s *grpcServingServiceServer) GetOnlineFeatures(ctx context.Context, request *serving.GetOnlineFeaturesRequest) (*serving.GetOnlineFeaturesResponse, error) {
-	//span, ctx := tracer.StartSpanFromContext(ctx, "getOnlineFeatures", tracer.ResourceName("ServingService/GetOnlineFeatures"))
-	//defer span.Finish()
+	ctx, span := tracer.Start(ctx, "server.getOnlineFeatures")
+	defer span.End()
 
-	//logSpanContext := LogWithSpanContext(span)
+	logSpanContext := LogWithSpanContext(span)
 
 	requestId := GenerateRequestId()
 	featuresOrService, err := s.fs.ParseFeatures(request.GetKind())
 
 	if err != nil {
-		//logSpanContext.Error().Err(err).Msg("Error parsing feature service or feature list from request")
+		logSpanContext.Error().Err(err).Msg("Error parsing feature service or feature list from request")
 		return nil, err
 	}
 
@@ -56,7 +56,7 @@ func (s *grpcServingServiceServer) GetOnlineFeatures(ctx context.Context, reques
 		request.GetFullFeatureNames())
 
 	if err != nil {
-		//logSpanContext.Error().Err(err).Msg("Error getting online features")
+		logSpanContext.Error().Err(err).Msg("Error getting online features")
 		return nil, err
 	}
 
@@ -75,7 +75,7 @@ func (s *grpcServingServiceServer) GetOnlineFeatures(ctx context.Context, reques
 		featureNames[idx] = vector.Name
 		values, err := types.ArrowValuesToProtoValues(vector.Values)
 		if err != nil {
-			//logSpanContext.Error().Err(err).Msg("Error converting Arrow values to proto values")
+			logSpanContext.Error().Err(err).Msg("Error converting Arrow values to proto values")
 			return nil, err
 		}
 		if _, ok := request.Entities[vector.Name]; ok {
@@ -93,13 +93,13 @@ func (s *grpcServingServiceServer) GetOnlineFeatures(ctx context.Context, reques
 	if featureService != nil && featureService.LoggingConfig != nil && s.loggingService != nil {
 		logger, err := s.loggingService.GetOrCreateLogger(featureService)
 		if err != nil {
-			//logSpanContext.Error().Err(err).Msg("Error to instantiating logger for feature service: " + featuresOrService.FeatureService.Name)
+			logSpanContext.Error().Err(err).Msg("Error to instantiating logger for feature service: " + featuresOrService.FeatureService.Name)
 			fmt.Printf("Couldn't instantiate logger for feature service %s: %+v", featuresOrService.FeatureService.Name, err)
 		}
 
 		err = logger.Log(request.Entities, resp.Results[len(request.Entities):], resp.Metadata.FeatureNames.Val[len(request.Entities):], request.RequestContext, requestId)
 		if err != nil {
-			//logSpanContext.Error().Err(err).Msg("Error to logging to feature service: " + featuresOrService.FeatureService.Name)
+			logSpanContext.Error().Err(err).Msg("Error to logging to feature service: " + featuresOrService.FeatureService.Name)
 			fmt.Printf("LoggerImpl error[%s]: %+v", featuresOrService.FeatureService.Name, err)
 		}
 	}
diff --git a/go/internal/feast/server/http_server.go b/go/internal/feast/server/http_server.go
index def58aedb88..312a0a6352e 100644
--- a/go/internal/feast/server/http_server.go
+++ b/go/internal/feast/server/http_server.go
@@ -5,10 +5,8 @@ import (
 	"encoding/json"
 	"fmt"
 	"net/http"
-	//"os"
 	"runtime"
 	"strconv"
-	//"strings"
 	"time"
 
 	"github.com/feast-dev/feast/go/internal/feast"
@@ -19,8 +17,6 @@ import (
 	prototypes "github.com/feast-dev/feast/go/protos/feast/types"
 	"github.com/feast-dev/feast/go/types"
 	"github.com/rs/zerolog/log"
-	//httptrace "gopkg.in/DataDog/dd-trace-go.v1/contrib/net/http"
-	//"gopkg.in/DataDog/dd-trace-go.v1/ddtrace/tracer"
 )
 
 type httpServer struct {
@@ -150,10 +146,10 @@ func (s *httpServer) getOnlineFeatures(w http.ResponseWriter, r *http.Request) {
 	var err error
 
 	ctx := r.Context()
-	//span, ctx := tracer.StartSpanFromContext(r.Context(), "getOnlineFeatures", tracer.ResourceName("/get-online-features"))
-	//defer span.Finish(tracer.WithError(err))
+	ctx, span := tracer.Start(r.Context(), "server.getOnlineFeatures")
+	defer span.End()
 
-	//logSpanContext := LogWithSpanContext(span)
+	logSpanContext := LogWithSpanContext(span)
 
 	if r.Method != "POST" {
 		http.NotFound(w, r)
@@ -166,7 +162,7 @@ func (s *httpServer) getOnlineFeatures(w http.ResponseWriter, r *http.Request) {
 	if statusQuery != "" {
 		status, err = strconv.ParseBool(statusQuery)
 		if err != nil {
-			//logSpanContext.Error().Err(err).Msg("Error parsing status query parameter")
+			logSpanContext.Error().Err(err).Msg("Error parsing status query parameter")
 			writeJSONError(w, fmt.Errorf("Error parsing status query parameter: %+v", err), http.StatusBadRequest)
 			return
 		}
@@ -176,7 +172,7 @@ func (s *httpServer) getOnlineFeatures(w http.ResponseWriter, r *http.Request) {
 	var request getOnlineFeaturesRequest
 	err = decoder.Decode(&request)
 	if err != nil {
-		//logSpanContext.Error().Err(err).Msg("Error decoding JSON request data")
+		logSpanContext.Error().Err(err).Msg("Error decoding JSON request data")
 		writeJSONError(w, fmt.Errorf("Error decoding JSON request data: %+v", err), http.StatusInternalServerError)
 		return
 	}
@@ -184,7 +180,7 @@ func (s *httpServer) getOnlineFeatures(w http.ResponseWriter, r *http.Request) {
 	if request.FeatureService != nil {
 		featureService, err = s.fs.GetFeatureService(*request.FeatureService)
 		if err != nil {
-			//logSpanContext.Error().Err(err).Msg("Error getting feature service from registry")
+			logSpanContext.Error().Err(err).Msg("Error getting feature service from registry")
 			writeJSONError(w, fmt.Errorf("Error getting feature service from registry: %+v", err), http.StatusInternalServerError)
 			return
 		}
@@ -207,7 +203,7 @@ func (s *httpServer) getOnlineFeatures(w http.ResponseWriter, r *http.Request) {
 		request.FullFeatureNames)
 
 	if err != nil {
-		//logSpanContext.Error().Err(err).Msg("Error getting feature vector")
+		logSpanContext.Error().Err(err).Msg("Error getting feature vector")
 		writeJSONError(w, fmt.Errorf("Error getting feature vector: %+v", err), http.StatusInternalServerError)
 		return
 	}
@@ -249,7 +245,7 @@ func (s *httpServer) getOnlineFeatures(w http.ResponseWriter, r *http.Request) {
 	err = json.NewEncoder(w).Encode(response)
 
 	if err != nil {
-		//logSpanContext.Error().Err(err).Msg("Error encoding response")
+		logSpanContext.Error().Err(err).Msg("Error encoding response")
 		writeJSONError(w, fmt.Errorf("Error encoding response: %+v", err), http.StatusInternalServerError)
 		return
 	}
@@ -257,7 +253,7 @@ func (s *httpServer) getOnlineFeatures(w http.ResponseWriter, r *http.Request) {
 	if featureService != nil && featureService.LoggingConfig != nil && s.loggingService != nil {
 		logger, err := s.loggingService.GetOrCreateLogger(featureService)
 		if err != nil {
-			//logSpanContext.Error().Err(err).Msgf("Couldn't instantiate logger for feature service %s", featureService.Name)
+			logSpanContext.Error().Err(err).Msgf("Couldn't instantiate logger for feature service %s", featureService.Name)
 			writeJSONError(w, fmt.Errorf("Couldn't instantiate logger for feature service %s: %+v", featureService.Name, err), http.StatusInternalServerError)
 			return
 		}
@@ -270,7 +266,7 @@ func (s *httpServer) getOnlineFeatures(w http.ResponseWriter, r *http.Request) {
 		for _, vector := range featureVectors[len(request.Entities):] {
 			values, err := types.ArrowValuesToProtoValues(vector.Values)
 			if err != nil {
-				//logSpanContext.Error().Err(err).Msg("Couldn't convert arrow values into protobuf")
+				logSpanContext.Error().Err(err).Msg("Couldn't convert arrow values into protobuf")
 				writeJSONError(w, fmt.Errorf("Couldn't convert arrow values into protobuf: %+v", err), http.StatusInternalServerError)
 				return
 			}
@@ -340,11 +336,6 @@ func recoverMiddleware(next http.Handler) http.Handler {
 }
 
 func (s *httpServer) Serve(host string, port int) error {
-	// DD
-	//if strings.ToLower(os.Getenv("ENABLE_DATADOG_TRACING")) == "true" {
-	//	tracer.Start(tracer.WithRuntimeMetrics())
-	//	defer tracer.Stop()
-	//}
 	mux := http.NewServeMux()
 	mux.Handle("/get-online-features", recoverMiddleware(http.HandlerFunc(s.getOnlineFeatures)))
 	mux.HandleFunc("/health", healthCheckHandler)
diff --git a/go/internal/feast/server/server_commons.go b/go/internal/feast/server/server_commons.go
index 140269d5c1c..a6959076c4a 100644
--- a/go/internal/feast/server/server_commons.go
+++ b/go/internal/feast/server/server_commons.go
@@ -1,31 +1,23 @@
 package server
 
 import (
-	"github.com/rs/zerolog"
-	//"gopkg.in/DataDog/dd-trace-go.v1/ddtrace/tracer"
 	"os"
-)
 
-func LogWiwithSpanContext() zerolog.Logger {
-	var logger = zerolog.New(os.Stderr).With().
-		Timestamp().
-		Logger()
+	"github.com/rs/zerolog"
+	"go.opentelemetry.io/otel/trace"
+	"go.opentelemetry.io/otel"
+)
 
-	return logger
-}
+var tracer = otel.Tracer("github.com/feast-dev/feast/go/server")
 
-/*
-func LogWithSpanContext(span tracer.Span) zerolog.Logger {
-	spanContext := span.Context()
+func LogWithSpanContext(span trace.Span) zerolog.Logger {
+	spanContext := span.SpanContext()
 
 	var logger = zerolog.New(os.Stderr).With().
+		Str("trace_id", spanContext.TraceID().String()).
+		Str("span_id", spanContext.SpanID().String()).
 		Timestamp().
 		Logger()
-		//Int64("trace_id", int64(spanContext.TraceID())).
-		//Int64("span_id", int64(spanContext.SpanID())).
-		//Timestamp().
-		//Logger()
 
 	return logger
 }
-*/
diff --git a/go/internal/feast/transformation/transformation.go b/go/internal/feast/transformation/transformation.go
index d6df03039d7..1080967b664 100644
--- a/go/internal/feast/transformation/transformation.go
+++ b/go/internal/feast/transformation/transformation.go
@@ -9,7 +9,7 @@ import (
 	"github.com/apache/arrow/go/v17/arrow"
 	"github.com/apache/arrow/go/v17/arrow/memory"
 	"github.com/rs/zerolog/log"
-	//"gopkg.in/DataDog/dd-trace-go.v1/ddtrace/tracer"
+	"go.opentelemetry.io/otel"
 
 	"github.com/feast-dev/feast/go/internal/feast/model"
 	"github.com/feast-dev/feast/go/internal/feast/onlineserving"
@@ -17,6 +17,8 @@ import (
 	"github.com/feast-dev/feast/go/types"
 )
 
+var tracer = otel.Tracer("github.com/feast-dev/feast/go/transformation")
+
 /*
 TransformationCallback is a Python callback function's expected signature.
 The function should accept name of the on demand feature view and pointers to input & output record batches.
@@ -40,8 +42,8 @@ func AugmentResponseWithOnDemandTransforms(
 	fullFeatureNames bool,
 
 ) ([]*onlineserving.FeatureVector, error) {
-	//span, _ := tracer.StartSpanFromContext(ctx, "transformation.AugmentResponseWithOnDemandTransforms")
-	//defer span.Finish()
+	ctx, span := tracer.Start(ctx, "transformation.AugmentResponseWithOnDemandTransforms")
+	defer span.End()
 
 	result := make([]*onlineserving.FeatureVector, 0)
 	var err error
diff --git a/go/main.go b/go/main.go
index feb54faa2e0..77999671e07 100644
--- a/go/main.go
+++ b/go/main.go
@@ -1,12 +1,13 @@
 package main
 
 import (
+	"context"
 	"flag"
 	"fmt"
 	"net"
 	"os"
 	"os/signal"
-	//"strings"
+	"strings"
 	"syscall"
 
 	"github.com/feast-dev/feast/go/internal/feast"
@@ -18,10 +19,18 @@ import (
 	"google.golang.org/grpc"
 	"google.golang.org/grpc/health"
 	"google.golang.org/grpc/health/grpc_health_v1"
-	//grpctrace "gopkg.in/DataDog/dd-trace-go.v1/contrib/google.golang.org/grpc"
-	//"gopkg.in/DataDog/dd-trace-go.v1/ddtrace/tracer"
+
+	"go.opentelemetry.io/otel"
+	"go.opentelemetry.io/otel/exporters/otlp/otlptrace"
+	"go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracehttp"
+	"go.opentelemetry.io/otel/sdk/resource"
+	sdktrace "go.opentelemetry.io/otel/sdk/trace"
+	semconv "go.opentelemetry.io/otel/semconv/v1.37.0"
+	"go.opentelemetry.io/otel/trace"
 )
 
+var tracer trace.Tracer
+
 type ServerStarter interface {
 	StartHttpServer(fs *feast.FeatureStore, host string, port int, writeLoggedFeaturesCallback logging.OfflineStoreWriteCallback, loggingOpts *logging.LoggingOptions) error
 	StartGrpcServer(fs *feast.FeatureStore, host string, port int, writeLoggedFeaturesCallback logging.OfflineStoreWriteCallback, loggingOpts *logging.LoggingOptions) error
@@ -56,6 +65,32 @@ func main() {
 	flag.IntVar(&port, "port", port, "Specify a port for the server")
 	flag.Parse()
 
+	// Initialize tracer
+	if OTELTracingEnabled() {
+		ctx := context.Background()
+
+		exp, err := newExporter(ctx)
+		if err != nil {
+			log.Fatal().Stack().Err(err).Msg("Failed to initialize exporter.")
+		}
+
+		// Create a new tracer provider with a batch span processor and the given exporter.
+		tp, err := newTracerProvider(exp)
+		if err != nil {
+			log.Fatal().Stack().Err(err).Msg("Failed to initialize tracer provider.")
+		}
+
+		// Handle shutdown properly so nothing leaks.
+		defer func() { _ = tp.Shutdown(ctx) }()
+
+		otel.SetTracerProvider(tp)
+
+		// Finally, set the tracer that can be used for this package.
+		tracer = tp.Tracer("github.com/feast-dev/feast/go")
+
+		log.Info().Msg("OTEL based tracing started.")
+	}
+
 	repoConfig, err := registry.NewRepoConfigFromFile(repoPath)
 	if err != nil {
 		log.Fatal().Stack().Err(err).Msg("Failed to convert to RepoConfig")
@@ -110,11 +145,6 @@ func constructLoggingService(fs *feast.FeatureStore, writeLoggedFeaturesCallback
 
 // StartGprcServerWithLogging starts gRPC server with enabled feature logging
 func StartGrpcServer(fs *feast.FeatureStore, host string, port int, writeLoggedFeaturesCallback logging.OfflineStoreWriteCallback, loggingOpts *logging.LoggingOptions) error {
-	// #DD
-	//if strings.ToLower(os.Getenv("ENABLE_DATADOG_TRACING")) == "true" {
-	//	tracer.Start(tracer.WithRuntimeMetrics())
-	//	defer tracer.Stop()
-	//}
 	loggingService, err := constructLoggingService(fs, writeLoggedFeaturesCallback, loggingOpts)
 	if err != nil {
 		return err
@@ -178,3 +208,35 @@ func StartHttpServer(fs *feast.FeatureStore, host string, port int, writeLoggedF
 
 	return ser.Serve(host, port)
 }
+
+func OTELTracingEnabled() bool {
+	return strings.ToLower(os.Getenv("ENABLE_OTEL_TRACING")) == "true"
+}
+
+func newExporter(ctx context.Context) (*otlptrace.Exporter, error) {
+	exp, err := otlptracehttp.New(ctx,
+		otlptracehttp.WithInsecure())
+	if err != nil {
+		return nil, err
+	}
+	return exp, nil
+}
+
+func newTracerProvider(exp sdktrace.SpanExporter) (*sdktrace.TracerProvider, error) {
+	r, err := resource.Merge(
+		resource.Default(),
+		resource.NewWithAttributes(
+			semconv.SchemaURL,
+			semconv.ServiceName("FeastGoFeatureServer"),
+		),
+	)
+
+	if err != nil {
+		return nil, err
+	}
+
+	return sdktrace.NewTracerProvider(
+		sdktrace.WithBatcher(exp),
+		sdktrace.WithResource(r),
+	), nil
+}
diff --git a/infra/charts/feast-feature-server/Chart.yaml b/infra/charts/feast-feature-server/Chart.yaml
index 5d1cc97c4c5..eaf14f21fe6 100644
--- a/infra/charts/feast-feature-server/Chart.yaml
+++ b/infra/charts/feast-feature-server/Chart.yaml
@@ -2,7 +2,7 @@ apiVersion: v2
 name: feast-feature-server
 description: Feast Feature Server in Go or Python
 type: application
-version: 0.55.0
+version: 0.56.0
 keywords:
   - machine learning
   - big data
diff --git a/infra/charts/feast-feature-server/README.md b/infra/charts/feast-feature-server/README.md
index c334acf24e6..e73be95a909 100644
--- a/infra/charts/feast-feature-server/README.md
+++ b/infra/charts/feast-feature-server/README.md
@@ -1,6 +1,6 @@
 # Feast Python / Go Feature Server Helm Charts
 
-Current chart version is `0.55.0`
+Current chart version is `0.56.0`
 
 ## Installation
 
@@ -35,13 +35,14 @@ See [here](https://github.com/feast-dev/feast/tree/master/examples/python-helm-d
 | Key | Type | Default | Description |
 |-----|------|---------|-------------|
 | affinity | object | `{}` |  |
+| commandArgs | list | `[]` | Override the default command arguments for complete control over CLI options If not specified, falls back to legacy behavior based on feast_mode Example for UI mode with custom options: commandArgs:   - "feast"   - "--log-level"   - "INFO"   - "ui"   - "--root_path"   - "/feast"   - "--registry_ttl_sec"   - "300"   - "-h"   - "0.0.0.0"   - "-p"   - "8888" |
 | extraEnvs | list | `[]` | Additional environment variables to be set in the container |
 | feast_mode | string | `"online"` | Feast supported deployment modes - online (default), offline, ui and registry |
 | feature_store_yaml_base64 | string | `""` | [required] a base64 encoded version of feature_store.yaml |
 | fullnameOverride | string | `""` |  |
 | image.pullPolicy | string | `"IfNotPresent"` |  |
 | image.repository | string | `"quay.io/feastdev/feature-server"` | Docker image for Feature Server repository |
-| image.tag | string | `"0.55.0"` | The Docker image tag (can be overwritten if custom feature server deps are needed for on demand transforms) |
+| image.tag | string | `"0.56.0"` | The Docker image tag (can be overwritten if custom feature server deps are needed for on demand transforms) |
 | imagePullSecrets | list | `[]` |  |
 | livenessProbe.initialDelaySeconds | int | `30` |  |
 | livenessProbe.periodSeconds | int | `30` |  |
diff --git a/infra/charts/feast-feature-server/templates/deployment.yaml b/infra/charts/feast-feature-server/templates/deployment.yaml
index 8af21aae80b..6cd17d4a4d1 100644
--- a/infra/charts/feast-feature-server/templates/deployment.yaml
+++ b/infra/charts/feast-feature-server/templates/deployment.yaml
@@ -47,6 +47,10 @@ spec:
               {{- toYaml . | nindent 12 }}
             {{- end}}
           command:
+            {{- if .Values.commandArgs }}
+            {{- toYaml .Values.commandArgs | nindent 12 }}
+            {{- else }}
+            {{- /* Fallback to legacy behavior for backward compatibility */}}
             {{- if eq .Values.feast_mode "offline" }}
             - "feast"
             - "--log-level"
@@ -82,6 +86,7 @@ spec:
             - "0.0.0.0"
             {{- end }}
             {{- end }}
+            {{- end }}
           ports:
             - name: {{ .Values.feast_mode }}
               {{- if eq .Values.feast_mode "offline" }}
diff --git a/infra/charts/feast-feature-server/values.yaml b/infra/charts/feast-feature-server/values.yaml
index 719e8f9cb7a..0f94b5bc579 100644
--- a/infra/charts/feast-feature-server/values.yaml
+++ b/infra/charts/feast-feature-server/values.yaml
@@ -9,7 +9,7 @@ image:
   repository: quay.io/feastdev/feature-server
   pullPolicy: IfNotPresent
   # image.tag -- The Docker image tag (can be overwritten if custom feature server deps are needed for on demand transforms)
-  tag: 0.55.0
+  tag: 0.56.0
 
 logLevel: "WARNING"  # Set log level DEBUG, INFO, WARNING, ERROR, and CRITICAL (case-insensitive)
 
@@ -29,6 +29,24 @@ feature_store_yaml_base64: ""
 # feast_mode -- Feast supported deployment modes - online (default), offline, ui and registry
 feast_mode: "online"
 
+# commandArgs -- Override the default command arguments for complete control over CLI options
+# If not specified, falls back to legacy behavior based on feast_mode
+# Example for UI mode with custom options:
+# commandArgs:
+#   - "feast"
+#   - "--log-level"
+#   - "INFO"
+#   - "ui"
+#   - "--root_path"
+#   - "/feast"
+#   - "--registry_ttl_sec"
+#   - "300"
+#   - "-h"
+#   - "0.0.0.0"
+#   - "-p"
+#   - "8888"
+commandArgs: []
+
 podAnnotations: {}
 
 podSecurityContext: {}
diff --git a/infra/charts/feast/Chart.yaml b/infra/charts/feast/Chart.yaml
index b3c62a8afca..307e01563cd 100644
--- a/infra/charts/feast/Chart.yaml
+++ b/infra/charts/feast/Chart.yaml
@@ -1,7 +1,7 @@
 apiVersion: v1
 description: Feature store for machine learning
 name: feast
-version: 0.55.0
+version: 0.56.0
 keywords:
   - machine learning
   - big data
diff --git a/infra/charts/feast/README.md b/infra/charts/feast/README.md
index a9912769b0a..dca35b67065 100644
--- a/infra/charts/feast/README.md
+++ b/infra/charts/feast/README.md
@@ -8,7 +8,7 @@ This repo contains Helm charts for Feast Java components that are being installe
    
 ## Chart: Feast
 
-Feature store for machine learning Current chart version is `0.55.0`
+Feature store for machine learning Current chart version is `0.56.0`
 
 ## Installation
 
@@ -65,8 +65,8 @@ See [here](https://github.com/feast-dev/feast/tree/master/examples/java-demo) fo
 | Repository | Name | Version |
 |------------|------|---------|
 | https://charts.helm.sh/stable | redis | 10.5.6 |
-| https://feast-helm-charts.storage.googleapis.com | feature-server(feature-server) | 0.55.0 |
-| https://feast-helm-charts.storage.googleapis.com | transformation-service(transformation-service) | 0.55.0 |
+| https://feast-helm-charts.storage.googleapis.com | feature-server(feature-server) | 0.56.0 |
+| https://feast-helm-charts.storage.googleapis.com | transformation-service(transformation-service) | 0.56.0 |
 
 ## Values
 
diff --git a/infra/charts/feast/charts/feature-server/Chart.yaml b/infra/charts/feast/charts/feature-server/Chart.yaml
index 9e45c70ef87..43a7e41c3ab 100644
--- a/infra/charts/feast/charts/feature-server/Chart.yaml
+++ b/infra/charts/feast/charts/feature-server/Chart.yaml
@@ -1,8 +1,8 @@
 apiVersion: v1
 description: "Feast Feature Server: Online feature serving service for Feast"
 name: feature-server
-version: 0.55.0
-appVersion: v0.55.0
+version: 0.56.0
+appVersion: v0.56.0
 keywords:
 - machine learning
 - big data
diff --git a/infra/charts/feast/charts/feature-server/README.md b/infra/charts/feast/charts/feature-server/README.md
index c84b8df1805..46159a543c5 100644
--- a/infra/charts/feast/charts/feature-server/README.md
+++ b/infra/charts/feast/charts/feature-server/README.md
@@ -1,6 +1,6 @@
 # feature-server
 
-![Version: 0.55.0](https://img.shields.io/badge/Version-0.55.0-informational?style=flat-square) ![AppVersion: v0.55.0](https://img.shields.io/badge/AppVersion-v0.55.0-informational?style=flat-square)
+![Version: 0.56.0](https://img.shields.io/badge/Version-0.56.0-informational?style=flat-square) ![AppVersion: v0.56.0](https://img.shields.io/badge/AppVersion-v0.56.0-informational?style=flat-square)
 
 Feast Feature Server: Online feature serving service for Feast
 
@@ -17,7 +17,7 @@ Feast Feature Server: Online feature serving service for Feast
 | envOverrides | object | `{}` | Extra environment variables to set |
 | image.pullPolicy | string | `"IfNotPresent"` | Image pull policy |
 | image.repository | string | `"quay.io/feastdev/feature-server-java"` | Docker image for Feature Server repository |
-| image.tag | string | `"0.55.0"` | Image tag |
+| image.tag | string | `"0.56.0"` | Image tag |
 | ingress.grpc.annotations | object | `{}` | Extra annotations for the ingress |
 | ingress.grpc.auth.enabled | bool | `false` | Flag to enable auth |
 | ingress.grpc.class | string | `"nginx"` | Which ingress controller to use |
diff --git a/infra/charts/feast/charts/feature-server/values.yaml b/infra/charts/feast/charts/feature-server/values.yaml
index 12e89fc1b7c..c054158be62 100644
--- a/infra/charts/feast/charts/feature-server/values.yaml
+++ b/infra/charts/feast/charts/feature-server/values.yaml
@@ -5,7 +5,7 @@ image:
   # image.repository -- Docker image for Feature Server repository
   repository: quay.io/feastdev/feature-server-java
   # image.tag -- Image tag
-  tag: 0.55.0
+  tag: 0.56.0
   # image.pullPolicy -- Image pull policy
   pullPolicy: IfNotPresent
 
diff --git a/infra/charts/feast/charts/transformation-service/Chart.yaml b/infra/charts/feast/charts/transformation-service/Chart.yaml
index 62659b31705..10c15403d9d 100644
--- a/infra/charts/feast/charts/transformation-service/Chart.yaml
+++ b/infra/charts/feast/charts/transformation-service/Chart.yaml
@@ -1,8 +1,8 @@
 apiVersion: v1
 description: "Transformation service: to compute on-demand features"
 name: transformation-service
-version: 0.55.0
-appVersion: v0.55.0
+version: 0.56.0
+appVersion: v0.56.0
 keywords:
 - machine learning
 - big data
diff --git a/infra/charts/feast/charts/transformation-service/README.md b/infra/charts/feast/charts/transformation-service/README.md
index 4cb9619c65b..716d5f9332b 100644
--- a/infra/charts/feast/charts/transformation-service/README.md
+++ b/infra/charts/feast/charts/transformation-service/README.md
@@ -1,6 +1,6 @@
 # transformation-service
 
-![Version: 0.55.0](https://img.shields.io/badge/Version-0.55.0-informational?style=flat-square) ![AppVersion: v0.55.0](https://img.shields.io/badge/AppVersion-v0.55.0-informational?style=flat-square)
+![Version: 0.56.0](https://img.shields.io/badge/Version-0.56.0-informational?style=flat-square) ![AppVersion: v0.56.0](https://img.shields.io/badge/AppVersion-v0.56.0-informational?style=flat-square)
 
 Transformation service: to compute on-demand features
 
@@ -13,7 +13,7 @@ Transformation service: to compute on-demand features
 | envOverrides | object | `{}` | Extra environment variables to set |
 | image.pullPolicy | string | `"IfNotPresent"` | Image pull policy |
 | image.repository | string | `"quay.io/feastdev/feature-transformation-server"` | Docker image for Transformation Server repository |
-| image.tag | string | `"0.55.0"` | Image tag |
+| image.tag | string | `"0.56.0"` | Image tag |
 | nodeSelector | object | `{}` | Node labels for pod assignment |
 | podLabels | object | `{}` | Labels to be added to Feast Serving pods |
 | replicaCount | int | `1` | Number of pods that will be created |
diff --git a/infra/charts/feast/charts/transformation-service/values.yaml b/infra/charts/feast/charts/transformation-service/values.yaml
index af5b3705a26..fe805f0bed1 100644
--- a/infra/charts/feast/charts/transformation-service/values.yaml
+++ b/infra/charts/feast/charts/transformation-service/values.yaml
@@ -5,7 +5,7 @@ image:
   # image.repository -- Docker image for Transformation Server repository
   repository: quay.io/feastdev/feature-transformation-server
   # image.tag -- Image tag
-  tag: 0.55.0
+  tag: 0.56.0
   # image.pullPolicy -- Image pull policy
   pullPolicy: IfNotPresent
 
diff --git a/infra/charts/feast/requirements.yaml b/infra/charts/feast/requirements.yaml
index adcf4bf9d5f..2ef611c9a0e 100644
--- a/infra/charts/feast/requirements.yaml
+++ b/infra/charts/feast/requirements.yaml
@@ -1,12 +1,12 @@
 dependencies:
 - name: feature-server
   alias: feature-server
-  version: 0.55.0
+  version: 0.56.0
   condition: feature-server.enabled
   repository: https://feast-helm-charts.storage.googleapis.com
 - name: transformation-service
   alias: transformation-service
-  version: 0.55.0
+  version: 0.56.0
   condition: transformation-service.enabled
   repository: https://feast-helm-charts.storage.googleapis.com
 - name: redis
diff --git a/infra/feast-operator/Makefile b/infra/feast-operator/Makefile
index 9b6abd8bd90..9541ed99656 100644
--- a/infra/feast-operator/Makefile
+++ b/infra/feast-operator/Makefile
@@ -3,7 +3,7 @@
 # To re-generate a bundle for another specific version without changing the standard setup, you can:
 # - use the VERSION as arg of the bundle target (e.g make bundle VERSION=0.0.2)
 # - use environment variables to overwrite this value (e.g export VERSION=0.0.2)
-VERSION ?= 0.55.0
+VERSION ?= 0.56.0
 
 # CHANNELS define the bundle channels used in the bundle.
 # Add a new line here if you would like to change its default config. (E.g CHANNELS = "candidate,fast,stable")
diff --git a/infra/feast-operator/api/feastversion/version.go b/infra/feast-operator/api/feastversion/version.go
index 3c89617400f..9279475e53d 100644
--- a/infra/feast-operator/api/feastversion/version.go
+++ b/infra/feast-operator/api/feastversion/version.go
@@ -17,4 +17,4 @@ limitations under the License.
 package feastversion
 
 // Feast release version. Keep on line #20, this is critical to release CI
-const FeastVersion = "0.55.0"
+const FeastVersion = "0.56.0"
diff --git a/infra/feast-operator/api/v1alpha1/featurestore_types.go b/infra/feast-operator/api/v1alpha1/featurestore_types.go
index 191505cc6a6..9250309b1cc 100644
--- a/infra/feast-operator/api/v1alpha1/featurestore_types.go
+++ b/infra/feast-operator/api/v1alpha1/featurestore_types.go
@@ -541,6 +541,7 @@ type OptionalCtrConfigs struct {
 	EnvFrom         *[]corev1.EnvFromSource      `json:"envFrom,omitempty"`
 	ImagePullPolicy *corev1.PullPolicy           `json:"imagePullPolicy,omitempty"`
 	Resources       *corev1.ResourceRequirements `json:"resources,omitempty"`
+	NodeSelector    *map[string]string           `json:"nodeSelector,omitempty"`
 }
 
 // AuthzConfig defines the authorization settings for the deployed Feast services.
diff --git a/infra/feast-operator/api/v1alpha1/zz_generated.deepcopy.go b/infra/feast-operator/api/v1alpha1/zz_generated.deepcopy.go
index 1a893c82cf8..7ea04929b3d 100644
--- a/infra/feast-operator/api/v1alpha1/zz_generated.deepcopy.go
+++ b/infra/feast-operator/api/v1alpha1/zz_generated.deepcopy.go
@@ -768,6 +768,17 @@ func (in *OptionalCtrConfigs) DeepCopyInto(out *OptionalCtrConfigs) {
 		*out = new(v1.ResourceRequirements)
 		(*in).DeepCopyInto(*out)
 	}
+	if in.NodeSelector != nil {
+		in, out := &in.NodeSelector, &out.NodeSelector
+		*out = new(map[string]string)
+		if **in != nil {
+			in, out := *in, *out
+			*out = make(map[string]string, len(*in))
+			for key, val := range *in {
+				(*out)[key] = val
+			}
+		}
+	}
 }
 
 // DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new OptionalCtrConfigs.
diff --git a/infra/feast-operator/bundle/manifests/feast-operator.clusterserviceversion.yaml b/infra/feast-operator/bundle/manifests/feast-operator.clusterserviceversion.yaml
index 9dc7e58cb4e..78205683183 100644
--- a/infra/feast-operator/bundle/manifests/feast-operator.clusterserviceversion.yaml
+++ b/infra/feast-operator/bundle/manifests/feast-operator.clusterserviceversion.yaml
@@ -50,10 +50,10 @@ metadata:
         }
       ]
     capabilities: Basic Install
-    createdAt: "2025-10-14T14:37:31Z"
+    createdAt: "2025-10-27T20:28:39Z"
     operators.operatorframework.io/builder: operator-sdk-v1.38.0
     operators.operatorframework.io/project_layout: go.kubebuilder.io/v4
-  name: feast-operator.v0.55.0
+  name: feast-operator.v0.56.0
   namespace: placeholder
 spec:
   apiservicedefinitions: {}
@@ -225,10 +225,10 @@ spec:
                 - /manager
                 env:
                 - name: RELATED_IMAGE_FEATURE_SERVER
-                  value: quay.io/feastdev/feature-server:0.55.0
+                  value: quay.io/feastdev/feature-server:0.56.0
                 - name: RELATED_IMAGE_CRON_JOB
                   value: quay.io/openshift/origin-cli:4.17
-                image: quay.io/feastdev/feast-operator:0.55.0
+                image: quay.io/feastdev/feast-operator:0.56.0
                 livenessProbe:
                   httpGet:
                     path: /healthz
@@ -318,8 +318,8 @@ spec:
     name: Feast Community
     url: https://lf-aidata.atlassian.net/wiki/spaces/FEAST/
   relatedImages:
-  - image: quay.io/feastdev/feature-server:0.55.0
+  - image: quay.io/feastdev/feature-server:0.56.0
     name: feature-server
   - image: quay.io/openshift/origin-cli:4.17
     name: cron-job
-  version: 0.55.0
+  version: 0.56.0
diff --git a/infra/feast-operator/bundle/manifests/feast.dev_featurestores.yaml b/infra/feast-operator/bundle/manifests/feast.dev_featurestores.yaml
index 5afa2ea3704..9c0c09d141a 100644
--- a/infra/feast-operator/bundle/manifests/feast.dev_featurestores.yaml
+++ b/infra/feast-operator/bundle/manifests/feast.dev_featurestores.yaml
@@ -259,6 +259,10 @@ spec:
                         description: PullPolicy describes a policy for if/when to
                           pull a container image
                         type: string
+                      nodeSelector:
+                        additionalProperties:
+                          type: string
+                        type: object
                       resources:
                         description: ResourceRequirements describes the compute resource
                           requirements.
@@ -1025,6 +1029,10 @@ spec:
                             - error
                             - critical
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
@@ -1480,6 +1488,10 @@ spec:
                             - error
                             - critical
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
@@ -1946,6 +1958,10 @@ spec:
                                 - error
                                 - critical
                                 type: string
+                              nodeSelector:
+                                additionalProperties:
+                                  type: string
+                                type: object
                               resources:
                                 description: ResourceRequirements describes the compute
                                   resource requirements.
@@ -2441,6 +2457,10 @@ spec:
                         - error
                         - critical
                         type: string
+                      nodeSelector:
+                        additionalProperties:
+                          type: string
+                        type: object
                       resources:
                         description: ResourceRequirements describes the compute resource
                           requirements.
@@ -4216,6 +4236,10 @@ spec:
                             description: PullPolicy describes a policy for if/when
                               to pull a container image
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
@@ -4994,6 +5018,10 @@ spec:
                                 - error
                                 - critical
                                 type: string
+                              nodeSelector:
+                                additionalProperties:
+                                  type: string
+                                type: object
                               resources:
                                 description: ResourceRequirements describes the compute
                                   resource requirements.
@@ -5457,6 +5485,10 @@ spec:
                                 - error
                                 - critical
                                 type: string
+                              nodeSelector:
+                                additionalProperties:
+                                  type: string
+                                type: object
                               resources:
                                 description: ResourceRequirements describes the compute
                                   resource requirements.
@@ -5935,6 +5967,10 @@ spec:
                                     - error
                                     - critical
                                     type: string
+                                  nodeSelector:
+                                    additionalProperties:
+                                      type: string
+                                    type: object
                                   resources:
                                     description: ResourceRequirements describes the
                                       compute resource requirements.
@@ -6440,6 +6476,10 @@ spec:
                             - error
                             - critical
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
diff --git a/infra/feast-operator/config/component_metadata.yaml b/infra/feast-operator/config/component_metadata.yaml
index 395624fb21a..cda672ead9a 100644
--- a/infra/feast-operator/config/component_metadata.yaml
+++ b/infra/feast-operator/config/component_metadata.yaml
@@ -1,5 +1,5 @@
 # This file is required to configure Feast release information for ODH/RHOAI Operator
 releases:
   - name: Feast
-    version: 0.55.0
+    version: 0.56.0
     repoUrl: https://github.com/feast-dev/feast
diff --git a/infra/feast-operator/config/crd/bases/feast.dev_featurestores.yaml b/infra/feast-operator/config/crd/bases/feast.dev_featurestores.yaml
index 8debe3639f9..c964d46c27d 100644
--- a/infra/feast-operator/config/crd/bases/feast.dev_featurestores.yaml
+++ b/infra/feast-operator/config/crd/bases/feast.dev_featurestores.yaml
@@ -259,6 +259,10 @@ spec:
                         description: PullPolicy describes a policy for if/when to
                           pull a container image
                         type: string
+                      nodeSelector:
+                        additionalProperties:
+                          type: string
+                        type: object
                       resources:
                         description: ResourceRequirements describes the compute resource
                           requirements.
@@ -1025,6 +1029,10 @@ spec:
                             - error
                             - critical
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
@@ -1480,6 +1488,10 @@ spec:
                             - error
                             - critical
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
@@ -1946,6 +1958,10 @@ spec:
                                 - error
                                 - critical
                                 type: string
+                              nodeSelector:
+                                additionalProperties:
+                                  type: string
+                                type: object
                               resources:
                                 description: ResourceRequirements describes the compute
                                   resource requirements.
@@ -2441,6 +2457,10 @@ spec:
                         - error
                         - critical
                         type: string
+                      nodeSelector:
+                        additionalProperties:
+                          type: string
+                        type: object
                       resources:
                         description: ResourceRequirements describes the compute resource
                           requirements.
@@ -4216,6 +4236,10 @@ spec:
                             description: PullPolicy describes a policy for if/when
                               to pull a container image
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
@@ -4994,6 +5018,10 @@ spec:
                                 - error
                                 - critical
                                 type: string
+                              nodeSelector:
+                                additionalProperties:
+                                  type: string
+                                type: object
                               resources:
                                 description: ResourceRequirements describes the compute
                                   resource requirements.
@@ -5457,6 +5485,10 @@ spec:
                                 - error
                                 - critical
                                 type: string
+                              nodeSelector:
+                                additionalProperties:
+                                  type: string
+                                type: object
                               resources:
                                 description: ResourceRequirements describes the compute
                                   resource requirements.
@@ -5935,6 +5967,10 @@ spec:
                                     - error
                                     - critical
                                     type: string
+                                  nodeSelector:
+                                    additionalProperties:
+                                      type: string
+                                    type: object
                                   resources:
                                     description: ResourceRequirements describes the
                                       compute resource requirements.
@@ -6440,6 +6476,10 @@ spec:
                             - error
                             - critical
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
diff --git a/infra/feast-operator/config/default/related_image_fs_patch.yaml b/infra/feast-operator/config/default/related_image_fs_patch.yaml
index b7ed2b05900..30cd7d3616f 100644
--- a/infra/feast-operator/config/default/related_image_fs_patch.yaml
+++ b/infra/feast-operator/config/default/related_image_fs_patch.yaml
@@ -2,7 +2,7 @@
   path: "/spec/template/spec/containers/0/env/0"
   value:
     name: RELATED_IMAGE_FEATURE_SERVER
-    value: quay.io/feastdev/feature-server:0.55.0
+    value: quay.io/feastdev/feature-server:0.56.0
 - op: replace
   path: "/spec/template/spec/containers/0/env/1"
   value:
diff --git a/infra/feast-operator/config/manager/kustomization.yaml b/infra/feast-operator/config/manager/kustomization.yaml
index be172b92a24..80aaa3faf28 100644
--- a/infra/feast-operator/config/manager/kustomization.yaml
+++ b/infra/feast-operator/config/manager/kustomization.yaml
@@ -5,4 +5,4 @@ kind: Kustomization
 images:
 - name: controller
   newName: quay.io/feastdev/feast-operator
-  newTag: 0.55.0
+  newTag: 0.56.0
diff --git a/infra/feast-operator/config/overlays/odh/params.env b/infra/feast-operator/config/overlays/odh/params.env
index c048b0151db..b112bb2d854 100644
--- a/infra/feast-operator/config/overlays/odh/params.env
+++ b/infra/feast-operator/config/overlays/odh/params.env
@@ -1,3 +1,3 @@
-RELATED_IMAGE_FEAST_OPERATOR=quay.io/feastdev/feast-operator:0.55.0
-RELATED_IMAGE_FEATURE_SERVER=quay.io/feastdev/feature-server:0.55.0
+RELATED_IMAGE_FEAST_OPERATOR=quay.io/feastdev/feast-operator:0.56.0
+RELATED_IMAGE_FEATURE_SERVER=quay.io/feastdev/feature-server:0.56.0
 RELATED_IMAGE_CRON_JOB=quay.io/openshift/origin-cli:4.17
diff --git a/infra/feast-operator/config/overlays/rhoai/params.env b/infra/feast-operator/config/overlays/rhoai/params.env
index e39233f168c..f548227235d 100644
--- a/infra/feast-operator/config/overlays/rhoai/params.env
+++ b/infra/feast-operator/config/overlays/rhoai/params.env
@@ -1,3 +1,3 @@
-RELATED_IMAGE_FEAST_OPERATOR=quay.io/feastdev/feast-operator:0.55.0
-RELATED_IMAGE_FEATURE_SERVER=quay.io/feastdev/feature-server:0.55.0
+RELATED_IMAGE_FEAST_OPERATOR=quay.io/feastdev/feast-operator:0.56.0
+RELATED_IMAGE_FEATURE_SERVER=quay.io/feastdev/feature-server:0.56.0
 RELATED_IMAGE_CRON_JOB=registry.redhat.io/openshift4/ose-cli@sha256:bc35a9fc663baf0d6493cc57e89e77a240a36c43cf38fb78d8e61d3b87cf5cc5
\ No newline at end of file
diff --git a/infra/feast-operator/dist/install.yaml b/infra/feast-operator/dist/install.yaml
index 9efa8044a29..58886675ec1 100644
--- a/infra/feast-operator/dist/install.yaml
+++ b/infra/feast-operator/dist/install.yaml
@@ -267,6 +267,10 @@ spec:
                         description: PullPolicy describes a policy for if/when to
                           pull a container image
                         type: string
+                      nodeSelector:
+                        additionalProperties:
+                          type: string
+                        type: object
                       resources:
                         description: ResourceRequirements describes the compute resource
                           requirements.
@@ -1033,6 +1037,10 @@ spec:
                             - error
                             - critical
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
@@ -1488,6 +1496,10 @@ spec:
                             - error
                             - critical
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
@@ -1954,6 +1966,10 @@ spec:
                                 - error
                                 - critical
                                 type: string
+                              nodeSelector:
+                                additionalProperties:
+                                  type: string
+                                type: object
                               resources:
                                 description: ResourceRequirements describes the compute
                                   resource requirements.
@@ -2449,6 +2465,10 @@ spec:
                         - error
                         - critical
                         type: string
+                      nodeSelector:
+                        additionalProperties:
+                          type: string
+                        type: object
                       resources:
                         description: ResourceRequirements describes the compute resource
                           requirements.
@@ -4224,6 +4244,10 @@ spec:
                             description: PullPolicy describes a policy for if/when
                               to pull a container image
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
@@ -5002,6 +5026,10 @@ spec:
                                 - error
                                 - critical
                                 type: string
+                              nodeSelector:
+                                additionalProperties:
+                                  type: string
+                                type: object
                               resources:
                                 description: ResourceRequirements describes the compute
                                   resource requirements.
@@ -5465,6 +5493,10 @@ spec:
                                 - error
                                 - critical
                                 type: string
+                              nodeSelector:
+                                additionalProperties:
+                                  type: string
+                                type: object
                               resources:
                                 description: ResourceRequirements describes the compute
                                   resource requirements.
@@ -5943,6 +5975,10 @@ spec:
                                     - error
                                     - critical
                                     type: string
+                                  nodeSelector:
+                                    additionalProperties:
+                                      type: string
+                                    type: object
                                   resources:
                                     description: ResourceRequirements describes the
                                       compute resource requirements.
@@ -6448,6 +6484,10 @@ spec:
                             - error
                             - critical
                             type: string
+                          nodeSelector:
+                            additionalProperties:
+                              type: string
+                            type: object
                           resources:
                             description: ResourceRequirements describes the compute
                               resource requirements.
@@ -8443,10 +8483,10 @@ spec:
         - /manager
         env:
         - name: RELATED_IMAGE_FEATURE_SERVER
-          value: quay.io/feastdev/feature-server:0.55.0
+          value: quay.io/feastdev/feature-server:0.56.0
         - name: RELATED_IMAGE_CRON_JOB
           value: quay.io/openshift/origin-cli:4.17
-        image: quay.io/feastdev/feast-operator:0.55.0
+        image: quay.io/feastdev/feast-operator:0.56.0
         livenessProbe:
           httpGet:
             path: /healthz
diff --git a/infra/feast-operator/dist/operator-e2e-tests b/infra/feast-operator/dist/operator-e2e-tests
index 5eb52e2a90a..2a8e2a02352 100755
Binary files a/infra/feast-operator/dist/operator-e2e-tests and b/infra/feast-operator/dist/operator-e2e-tests differ
diff --git a/infra/feast-operator/docs/api/markdown/ref.md b/infra/feast-operator/docs/api/markdown/ref.md
index 68978a08cf0..fac7ebfa784 100644
--- a/infra/feast-operator/docs/api/markdown/ref.md
+++ b/infra/feast-operator/docs/api/markdown/ref.md
@@ -46,6 +46,7 @@ _Appears in:_
 | `envFrom` _[EnvFromSource](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#envfromsource-v1-core)_ |  |
 | `imagePullPolicy` _[PullPolicy](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#pullpolicy-v1-core)_ |  |
 | `resources` _[ResourceRequirements](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#resourcerequirements-v1-core)_ |  |
+| `nodeSelector` _map[string]string_ |  |
 
 
 #### CronJobContainerConfigs
@@ -64,6 +65,7 @@ _Appears in:_
 | `envFrom` _[EnvFromSource](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#envfromsource-v1-core)_ |  |
 | `imagePullPolicy` _[PullPolicy](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#pullpolicy-v1-core)_ |  |
 | `resources` _[ResourceRequirements](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#resourcerequirements-v1-core)_ |  |
+| `nodeSelector` _map[string]string_ |  |
 | `commands` _string array_ | Array of commands to be executed (in order) against a Feature Store deployment.
 Defaults to "feast apply" & "feast materialize-incremental $(date -u +'%Y-%m-%dT%H:%M:%S')" |
 
@@ -566,6 +568,7 @@ _Appears in:_
 | `envFrom` _[EnvFromSource](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#envfromsource-v1-core)_ |  |
 | `imagePullPolicy` _[PullPolicy](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#pullpolicy-v1-core)_ |  |
 | `resources` _[ResourceRequirements](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#resourcerequirements-v1-core)_ |  |
+| `nodeSelector` _map[string]string_ |  |
 
 
 #### PvcConfig
@@ -688,6 +691,7 @@ _Appears in:_
 | `envFrom` _[EnvFromSource](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#envfromsource-v1-core)_ |  |
 | `imagePullPolicy` _[PullPolicy](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#pullpolicy-v1-core)_ |  |
 | `resources` _[ResourceRequirements](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#resourcerequirements-v1-core)_ |  |
+| `nodeSelector` _map[string]string_ |  |
 | `tls` _[TlsConfigs](#tlsconfigs)_ |  |
 | `logLevel` _string_ | LogLevel sets the logging level for the server
 Allowed values: "debug", "info", "warning", "error", "critical". |
@@ -750,6 +754,7 @@ _Appears in:_
 | `envFrom` _[EnvFromSource](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#envfromsource-v1-core)_ |  |
 | `imagePullPolicy` _[PullPolicy](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#pullpolicy-v1-core)_ |  |
 | `resources` _[ResourceRequirements](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.30/#resourcerequirements-v1-core)_ |  |
+| `nodeSelector` _map[string]string_ |  |
 | `tls` _[TlsConfigs](#tlsconfigs)_ |  |
 | `logLevel` _string_ | LogLevel sets the logging level for the server
 Allowed values: "debug", "info", "warning", "error", "critical". |
diff --git a/infra/feast-operator/internal/controller/services/services.go b/infra/feast-operator/internal/controller/services/services.go
index 5b70d6e1911..3b14f9c49db 100644
--- a/infra/feast-operator/internal/controller/services/services.go
+++ b/infra/feast-operator/internal/controller/services/services.go
@@ -412,6 +412,7 @@ func (feast *FeastServices) setPod(podSpec *corev1.PodSpec) error {
 	feast.mountPvcConfigs(podSpec)
 	feast.mountEmptyDirVolumes(podSpec)
 	feast.mountUserDefinedVolumes(podSpec)
+	feast.applyNodeSelector(podSpec)
 
 	return nil
 }
@@ -793,6 +794,56 @@ func (feast *FeastServices) getLogLevelForType(feastType FeastServiceType) *stri
 	return nil
 }
 
+func (feast *FeastServices) getNodeSelectorForType(feastType FeastServiceType) *map[string]string {
+	if serviceConfigs := feast.getServerConfigs(feastType); serviceConfigs != nil {
+		return serviceConfigs.ContainerConfigs.OptionalCtrConfigs.NodeSelector
+	}
+	return nil
+}
+
+func (feast *FeastServices) applyNodeSelector(podSpec *corev1.PodSpec) {
+	// Merge node selectors from all services
+	mergedNodeSelector := make(map[string]string)
+
+	// Check all service types for node selector configuration
+	allServiceTypes := append(feastServerTypes, UIFeastType)
+	for _, feastType := range allServiceTypes {
+		if selector := feast.getNodeSelectorForType(feastType); selector != nil && len(*selector) > 0 {
+			for k, v := range *selector {
+				mergedNodeSelector[k] = v
+			}
+		}
+	}
+
+	// If no service has node selector configured, we're done
+	if len(mergedNodeSelector) == 0 {
+		return
+	}
+
+	// Merge with any existing node selectors (from ops team or other sources)
+	// This preserves pre-existing selectors while adding operator requirements
+	finalNodeSelector := feast.mergeNodeSelectors(podSpec.NodeSelector, mergedNodeSelector)
+	podSpec.NodeSelector = finalNodeSelector
+}
+
+// mergeNodeSelectors merges existing and operator node selectors
+// Existing selectors are preserved, operator selectors can override existing keys
+func (feast *FeastServices) mergeNodeSelectors(existing, operator map[string]string) map[string]string {
+	merged := make(map[string]string)
+
+	// Start with existing selectors (from ops team or other sources)
+	for k, v := range existing {
+		merged[k] = v
+	}
+
+	// Add/override with operator selectors
+	for k, v := range operator {
+		merged[k] = v
+	}
+
+	return merged
+}
+
 // GetObjectMeta returns the feast k8s object metadata with type
 func (feast *FeastServices) GetObjectMeta() metav1.ObjectMeta {
 	return metav1.ObjectMeta{Name: GetFeastName(feast.Handler.FeatureStore), Namespace: feast.Handler.FeatureStore.Namespace}
diff --git a/infra/feast-operator/internal/controller/services/services_test.go b/infra/feast-operator/internal/controller/services/services_test.go
index 0c43aff5954..14509fe9933 100644
--- a/infra/feast-operator/internal/controller/services/services_test.go
+++ b/infra/feast-operator/internal/controller/services/services_test.go
@@ -203,4 +203,193 @@ var _ = Describe("Registry Service", func() {
 			Expect(ports[1].Name).To(Equal(string(RegistryFeastType) + "-rest"))
 		})
 	})
+
+	Describe("NodeSelector Configuration", func() {
+		It("should apply NodeSelector to pod spec when configured", func() {
+			// Set NodeSelector for registry service
+			nodeSelector := map[string]string{
+				"kubernetes.io/os": "linux",
+				"node-type":        "compute",
+			}
+			featureStore.Spec.Services.Registry.Local.Server.ContainerConfigs.OptionalCtrConfigs.NodeSelector = &nodeSelector
+			Expect(k8sClient.Update(ctx, featureStore)).To(Succeed())
+			Expect(feast.ApplyDefaults()).To(Succeed())
+			applySpecToStatus(featureStore)
+			feast.refreshFeatureStore(ctx, typeNamespacedName)
+
+			// Create deployment and verify NodeSelector is applied
+			deployment := feast.initFeastDeploy()
+			Expect(deployment).NotTo(BeNil())
+			Expect(feast.setDeployment(deployment)).To(Succeed())
+
+			// Verify NodeSelector is applied to pod spec
+			expectedNodeSelector := map[string]string{
+				"kubernetes.io/os": "linux",
+				"node-type":        "compute",
+			}
+			Expect(deployment.Spec.Template.Spec.NodeSelector).To(Equal(expectedNodeSelector))
+		})
+
+		It("should merge NodeSelectors from multiple services", func() {
+			// Set NodeSelector for registry service
+			registryNodeSelector := map[string]string{
+				"kubernetes.io/os": "linux",
+				"node-type":        "compute",
+			}
+			featureStore.Spec.Services.Registry.Local.Server.ContainerConfigs.OptionalCtrConfigs.NodeSelector = &registryNodeSelector
+
+			// Set NodeSelector for online store service
+			onlineNodeSelector := map[string]string{
+				"node-type": "online",
+				"zone":      "us-west-1a",
+			}
+			featureStore.Spec.Services.OnlineStore = &feastdevv1alpha1.OnlineStore{
+				Server: &feastdevv1alpha1.ServerConfigs{
+					ContainerConfigs: feastdevv1alpha1.ContainerConfigs{
+						DefaultCtrConfigs: feastdevv1alpha1.DefaultCtrConfigs{
+							Image: ptr("test-image"),
+						},
+						OptionalCtrConfigs: feastdevv1alpha1.OptionalCtrConfigs{
+							NodeSelector: &onlineNodeSelector,
+						},
+					},
+				},
+			}
+
+			Expect(k8sClient.Update(ctx, featureStore)).To(Succeed())
+			Expect(feast.ApplyDefaults()).To(Succeed())
+			applySpecToStatus(featureStore)
+			feast.refreshFeatureStore(ctx, typeNamespacedName)
+
+			// Create deployment and verify merged NodeSelector is applied
+			deployment := feast.initFeastDeploy()
+			Expect(deployment).NotTo(BeNil())
+			Expect(feast.setDeployment(deployment)).To(Succeed())
+
+			// Verify NodeSelector merges all service selectors (online overrides registry for node-type)
+			expectedNodeSelector := map[string]string{
+				"kubernetes.io/os": "linux",
+				"node-type":        "online",
+				"zone":             "us-west-1a",
+			}
+			Expect(deployment.Spec.Template.Spec.NodeSelector).To(Equal(expectedNodeSelector))
+		})
+
+		It("should merge operator NodeSelector with existing selectors (mutating webhook scenario)", func() {
+			// Set NodeSelector for UI service
+			uiNodeSelector := map[string]string{
+				"node-type": "ui",
+			}
+			featureStore.Spec.Services.UI = &feastdevv1alpha1.ServerConfigs{
+				ContainerConfigs: feastdevv1alpha1.ContainerConfigs{
+					DefaultCtrConfigs: feastdevv1alpha1.DefaultCtrConfigs{
+						Image: ptr("test-image"),
+					},
+					OptionalCtrConfigs: feastdevv1alpha1.OptionalCtrConfigs{
+						NodeSelector: &uiNodeSelector,
+					},
+				},
+			}
+
+			Expect(k8sClient.Update(ctx, featureStore)).To(Succeed())
+			Expect(feast.ApplyDefaults()).To(Succeed())
+			applySpecToStatus(featureStore)
+			feast.refreshFeatureStore(ctx, typeNamespacedName)
+
+			// Create deployment first
+			deployment := feast.initFeastDeploy()
+			Expect(deployment).NotTo(BeNil())
+			Expect(feast.setDeployment(deployment)).To(Succeed())
+
+			// Simulate a mutating webhook or admission controller adding node selectors
+			// This would happen after the operator creates the pod spec but before scheduling
+			existingNodeSelector := map[string]string{
+				"team":        "ml",
+				"environment": "prod",
+			}
+			deployment.Spec.Template.Spec.NodeSelector = existingNodeSelector
+
+			// Apply the node selector logic again to test merging
+			// This simulates the operator reconciling and re-applying node selectors
+			feast.applyNodeSelector(&deployment.Spec.Template.Spec)
+
+			// Verify NodeSelector merges existing and operator selectors
+			expectedNodeSelector := map[string]string{
+				"team":        "ml",
+				"environment": "prod",
+				"node-type":   "ui",
+			}
+			Expect(deployment.Spec.Template.Spec.NodeSelector).To(Equal(expectedNodeSelector))
+		})
+
+		It("should apply UI service NodeSelector when UI has highest precedence", func() {
+			// Set NodeSelector for online service
+			onlineNodeSelector := map[string]string{
+				"node-type": "online",
+			}
+			featureStore.Spec.Services.OnlineStore = &feastdevv1alpha1.OnlineStore{
+				Server: &feastdevv1alpha1.ServerConfigs{
+					ContainerConfigs: feastdevv1alpha1.ContainerConfigs{
+						DefaultCtrConfigs: feastdevv1alpha1.DefaultCtrConfigs{
+							Image: ptr("test-image"),
+						},
+						OptionalCtrConfigs: feastdevv1alpha1.OptionalCtrConfigs{
+							NodeSelector: &onlineNodeSelector,
+						},
+					},
+				},
+			}
+
+			// Set NodeSelector for UI service (should win)
+			uiNodeSelector := map[string]string{
+				"node-type": "ui",
+				"zone":      "us-east-1",
+			}
+			featureStore.Spec.Services.UI = &feastdevv1alpha1.ServerConfigs{
+				ContainerConfigs: feastdevv1alpha1.ContainerConfigs{
+					DefaultCtrConfigs: feastdevv1alpha1.DefaultCtrConfigs{
+						Image: ptr("test-image"),
+					},
+					OptionalCtrConfigs: feastdevv1alpha1.OptionalCtrConfigs{
+						NodeSelector: &uiNodeSelector,
+					},
+				},
+			}
+
+			Expect(k8sClient.Update(ctx, featureStore)).To(Succeed())
+			Expect(feast.ApplyDefaults()).To(Succeed())
+			applySpecToStatus(featureStore)
+			feast.refreshFeatureStore(ctx, typeNamespacedName)
+
+			// Create deployment and verify UI service selector is applied
+			deployment := feast.initFeastDeploy()
+			Expect(deployment).NotTo(BeNil())
+			Expect(feast.setDeployment(deployment)).To(Succeed())
+
+			// Verify NodeSelector is applied with UI service's selector (UI wins)
+			expectedNodeSelector := map[string]string{
+				"node-type": "ui",
+				"zone":      "us-east-1",
+			}
+			Expect(deployment.Spec.Template.Spec.NodeSelector).To(Equal(expectedNodeSelector))
+		})
+
+		It("should handle empty NodeSelector gracefully", func() {
+			// Set empty NodeSelector
+			emptyNodeSelector := map[string]string{}
+			featureStore.Spec.Services.Registry.Local.Server.ContainerConfigs.OptionalCtrConfigs.NodeSelector = &emptyNodeSelector
+			Expect(k8sClient.Update(ctx, featureStore)).To(Succeed())
+			Expect(feast.ApplyDefaults()).To(Succeed())
+			applySpecToStatus(featureStore)
+			feast.refreshFeatureStore(ctx, typeNamespacedName)
+
+			// Create deployment and verify no NodeSelector is applied (empty selector)
+			deployment := feast.initFeastDeploy()
+			Expect(deployment).NotTo(BeNil())
+			Expect(feast.setDeployment(deployment)).To(Succeed())
+
+			// Verify no NodeSelector is applied (empty selector)
+			Expect(deployment.Spec.Template.Spec.NodeSelector).To(BeEmpty())
+		})
+	})
 })
diff --git a/java/pom.xml b/java/pom.xml
index 59793c2cabf..d9625cecf49 100644
--- a/java/pom.xml
+++ b/java/pom.xml
@@ -35,7 +35,7 @@
     </modules>
 
     <properties>
-        <revision>0.55.0</revision>
+        <revision>0.56.0</revision>
         <github.url>https://github.com/feast-dev/feast</github.url>
 
         <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
diff --git a/protos/feast/core/FeatureView.proto b/protos/feast/core/FeatureView.proto
index 9ea33b33fb7..6306d425be3 100644
--- a/protos/feast/core/FeatureView.proto
+++ b/protos/feast/core/FeatureView.proto
@@ -36,7 +36,7 @@ message FeatureView {
     FeatureViewMeta meta = 2;
 }
 
-// Next available id: 16
+// Next available id: 17
 // TODO(adchia): refactor common fields from this and ODFV into separate metadata proto
 message FeatureViewSpec {
     // Name of the feature view. Must be unique. Not updated.
@@ -51,18 +51,9 @@ message FeatureViewSpec {
     // List of specifications for each feature defined as part of this feature view.
     repeated FeatureSpecV2 features = 4;
 
-    // List of specifications for each entity defined as part of this feature view.
-    repeated FeatureSpecV2 entity_columns = 12;
-
-    // Description of the feature view.
-    string description = 10;
-
     // User defined metadata
     map<string,string> tags = 5;
 
-    // Owner of the feature view.
-    string owner = 11;
-
     // Features in this feature view can only be retrieved from online serving
     // younger than ttl. Ttl is measured as the duration of time between
     // the feature's event timestamp and when the feature is retrieved
@@ -71,13 +62,23 @@ message FeatureViewSpec {
 
     // Batch/Offline DataSource where this view can retrieve offline feature data.
     DataSource batch_source = 7;
-    // Streaming DataSource from where this view can consume "online" feature data.
-    DataSource stream_source = 9;
 
     // Whether these features should be served online or not
     // This is also used to determine whether the features should be written to the online store
     bool online = 8;
 
+    // Streaming DataSource from where this view can consume "online" feature data.
+    DataSource stream_source = 9;
+
+    // Description of the feature view.
+    string description = 10;
+
+    // Owner of the feature view.
+    string owner = 11;
+
+    // List of specifications for each entity defined as part of this feature view.
+    repeated FeatureSpecV2 entity_columns = 12;
+
     // Whether these features should be written to the offline store
     bool offline = 13;
 
@@ -85,6 +86,9 @@ message FeatureViewSpec {
 
     // Feature transformation for batch feature views
     FeatureTransformationV2 feature_transformation = 15;
+
+    // The transformation mode (e.g., "python", "pandas", "spark", "sql", "ray")
+    string mode = 16;
 }
 
 message FeatureViewMeta {
diff --git a/protos/feast/core/Transformation.proto b/protos/feast/core/Transformation.proto
index 7033f553f16..68a8b48229e 100644
--- a/protos/feast/core/Transformation.proto
+++ b/protos/feast/core/Transformation.proto
@@ -15,6 +15,9 @@ message UserDefinedFunctionV2 {
 
     // The string representation of the udf
     string body_text = 3;
+
+    // The transformation mode (e.g., "python", "pandas", "ray", "spark", "sql")
+    string mode = 4;
 }
 
 // A feature transformation executed as a user-defined function
diff --git a/sdk/python/docs/source/feast.infra.compute_engines.local.backends.rst b/sdk/python/docs/source/feast.infra.compute_engines.local.backends.rst
index 39205f3c4df..69eeed70bb5 100644
--- a/sdk/python/docs/source/feast.infra.compute_engines.local.backends.rst
+++ b/sdk/python/docs/source/feast.infra.compute_engines.local.backends.rst
@@ -7,7 +7,7 @@ Submodules
 feast.infra.compute\_engines.local.backends.base module
 -------------------------------------------------------
 
-.. automodule:: feast.infra.compute_engines.local.backends.base
+.. automodule:: feast.infra.compute_engines.backends.base
    :members:
    :undoc-members:
    :show-inheritance:
@@ -15,7 +15,7 @@ feast.infra.compute\_engines.local.backends.base module
 feast.infra.compute\_engines.local.backends.factory module
 ----------------------------------------------------------
 
-.. automodule:: feast.infra.compute_engines.local.backends.factory
+.. automodule:: feast.infra.compute_engines.backends.factory
    :members:
    :undoc-members:
    :show-inheritance:
@@ -23,7 +23,7 @@ feast.infra.compute\_engines.local.backends.factory module
 feast.infra.compute\_engines.local.backends.pandas\_backend module
 ------------------------------------------------------------------
 
-.. automodule:: feast.infra.compute_engines.local.backends.pandas_backend
+.. automodule:: feast.infra.compute_engines.backends.pandas_backend
    :members:
    :undoc-members:
    :show-inheritance:
@@ -31,7 +31,7 @@ feast.infra.compute\_engines.local.backends.pandas\_backend module
 feast.infra.compute\_engines.local.backends.polars\_backend module
 ------------------------------------------------------------------
 
-.. automodule:: feast.infra.compute_engines.local.backends.polars_backend
+.. automodule:: feast.infra.compute_engines.backends.polars_backend
    :members:
    :undoc-members:
    :show-inheritance:
@@ -39,7 +39,7 @@ feast.infra.compute\_engines.local.backends.polars\_backend module
 Module contents
 ---------------
 
-.. automodule:: feast.infra.compute_engines.local.backends
+.. automodule:: feast.infra.compute_engines.backends
    :members:
    :undoc-members:
    :show-inheritance:
diff --git a/sdk/python/docs/source/feast.infra.compute_engines.local.rst b/sdk/python/docs/source/feast.infra.compute_engines.local.rst
index 6525199e6dc..d6ce47cb140 100644
--- a/sdk/python/docs/source/feast.infra.compute_engines.local.rst
+++ b/sdk/python/docs/source/feast.infra.compute_engines.local.rst
@@ -7,7 +7,7 @@ Subpackages
 .. toctree::
    :maxdepth: 4
 
-   feast.infra.compute_engines.local.backends
+   feast.infra.compute_engines.backends
 
 Submodules
 ----------
diff --git a/sdk/python/feast/api/registry/rest/metrics.py b/sdk/python/feast/api/registry/rest/metrics.py
index 32253e85aca..58dc7156144 100644
--- a/sdk/python/feast/api/registry/rest/metrics.py
+++ b/sdk/python/feast/api/registry/rest/metrics.py
@@ -98,8 +98,8 @@ def count_resources_for_project(project_name: str):
                 features = {"features": []}
             try:
                 feature_views = grpc_call(
-                    grpc_handler.ListFeatureViews,
-                    RegistryServer_pb2.ListFeatureViewsRequest(
+                    grpc_handler.ListAllFeatureViews,
+                    RegistryServer_pb2.ListAllFeatureViewsRequest(
                         project=project_name, allow_cache=allow_cache
                     ),
                 )
diff --git a/sdk/python/feast/batch_feature_view.py b/sdk/python/feast/batch_feature_view.py
index c168aaeec10..3f3e1bf20ec 100644
--- a/sdk/python/feast/batch_feature_view.py
+++ b/sdk/python/feast/batch_feature_view.py
@@ -57,7 +57,6 @@ class BatchFeatureView(FeatureView):
     """
 
     name: str
-    mode: Union[TransformationMode, str]
     entities: List[str]
     ttl: Optional[timedelta]
     source: DataSource
@@ -136,6 +135,7 @@ def __init__(
             schema=schema,
             source=source,  # type: ignore[arg-type]
             sink_source=sink_source,
+            mode=mode,
         )
 
     def get_feature_transformation(self) -> Optional[Transformation]:
@@ -145,7 +145,8 @@ def get_feature_transformation(self) -> Optional[Transformation]:
             TransformationMode.PANDAS,
             TransformationMode.PYTHON,
             TransformationMode.SQL,
-        ) or self.mode in ("pandas", "python", "sql"):
+            TransformationMode.RAY,
+        ) or self.mode in ("pandas", "python", "sql", "ray"):
             return Transformation(
                 mode=self.mode, udf=self.udf, udf_string=self.udf_string or ""
             )
diff --git a/sdk/python/feast/cli/cli.py b/sdk/python/feast/cli/cli.py
index 1bdf1f5ff85..91fa2a92606 100644
--- a/sdk/python/feast/cli/cli.py
+++ b/sdk/python/feast/cli/cli.py
@@ -411,6 +411,7 @@ def materialize_incremental_command(ctx: click.Context, end_ts: str, views: List
             "couchbase",
             "milvus",
             "ray",
+            "ray_rag",
         ],
         case_sensitive=False,
     ),
diff --git a/sdk/python/feast/feature_server.py b/sdk/python/feast/feature_server.py
index 0cc90b294d8..fee7e56e9c1 100644
--- a/sdk/python/feast/feature_server.py
+++ b/sdk/python/feast/feature_server.py
@@ -120,27 +120,26 @@ class SaveDocumentRequest(BaseModel):
     data: dict
 
 
-def _get_features(
+async def _get_features(
     request: Union[GetOnlineFeaturesRequest, GetOnlineDocumentsRequest],
     store: "feast.FeatureStore",
 ):
     if request.feature_service:
-        feature_service = store.get_feature_service(
-            request.feature_service, allow_cache=True
+        feature_service = await run_in_threadpool(
+            store.get_feature_service, request.feature_service, allow_cache=True
         )
         assert_permissions(
             resource=feature_service, actions=[AuthzedAction.READ_ONLINE]
         )
         features = feature_service  # type: ignore
     else:
-        all_feature_views, all_on_demand_feature_views = (
-            utils._get_feature_views_to_use(
-                store.registry,
-                store.project,
-                request.features,
-                allow_cache=True,
-                hide_dummy_entity=False,
-            )
+        all_feature_views, all_on_demand_feature_views = await run_in_threadpool(
+            utils._get_feature_views_to_use,
+            store.registry,
+            store.project,
+            request.features,
+            allow_cache=True,
+            hide_dummy_entity=False,
         )
         for feature_view in all_feature_views:
             assert_permissions(
@@ -230,7 +229,7 @@ async def lifespan(app: FastAPI):
     )
     async def get_online_features(request: GetOnlineFeaturesRequest) -> Dict[str, Any]:
         # Initialize parameters for FeatureStore.get_online_features(...) call
-        features = await run_in_threadpool(_get_features, request, store)
+        features = await _get_features(request, store)
 
         read_params = dict(
             features=features,
@@ -265,7 +264,7 @@ async def retrieve_online_documents(
             "This endpoint is in alpha and will be moved to /get-online-features when stable."
         )
         # Initialize parameters for FeatureStore.retrieve_online_documents_v2(...) call
-        features = await run_in_threadpool(_get_features, request, store)
+        features = await _get_features(request, store)
 
         read_params = dict(features=features, query=request.query, top_k=request.top_k)
         if request.api_version == 2 and request.query_string is not None:
@@ -342,26 +341,31 @@ async def push(request: PushFeaturesRequest) -> None:
         else:
             store.push(**push_params)
 
-    def _get_feast_object(
+    async def _get_feast_object(
         feature_view_name: str, allow_registry_cache: bool
     ) -> FeastObject:
         try:
-            return store.get_stream_feature_view(  # type: ignore
-                feature_view_name, allow_registry_cache=allow_registry_cache
+            return await run_in_threadpool(
+                store.get_stream_feature_view,
+                feature_view_name,
+                allow_registry_cache=allow_registry_cache,
             )
         except FeatureViewNotFoundException:
-            return store.get_feature_view(  # type: ignore
-                feature_view_name, allow_registry_cache=allow_registry_cache
+            return await run_in_threadpool(
+                store.get_feature_view,
+                feature_view_name,
+                allow_registry_cache=allow_registry_cache,
             )
 
     @app.post("/write-to-online-store", dependencies=[Depends(inject_user_details)])
-    def write_to_online_store(request: WriteToFeatureStoreRequest) -> None:
+    async def write_to_online_store(request: WriteToFeatureStoreRequest) -> None:
         df = pd.DataFrame(request.df)
         feature_view_name = request.feature_view_name
         allow_registry_cache = request.allow_registry_cache
-        resource = _get_feast_object(feature_view_name, allow_registry_cache)
+        resource = await _get_feast_object(feature_view_name, allow_registry_cache)
         assert_permissions(resource=resource, actions=[AuthzedAction.WRITE_ONLINE])
-        store.write_to_online_store(
+        await run_in_threadpool(
+            store.write_to_online_store,
             feature_view_name=feature_view_name,
             df=df,
             allow_registry_cache=allow_registry_cache,
@@ -428,10 +432,11 @@ async def chat_ui():
         return Response(content=content, media_type="text/html")
 
     @app.post("/materialize", dependencies=[Depends(inject_user_details)])
-    def materialize(request: MaterializeRequest) -> None:
+    async def materialize(request: MaterializeRequest) -> None:
         for feature_view in request.feature_views or []:
+            resource = await _get_feast_object(feature_view, True)
             assert_permissions(
-                resource=_get_feast_object(feature_view, True),
+                resource=resource,
                 actions=[AuthzedAction.WRITE_ONLINE],
             )
 
@@ -450,7 +455,8 @@ def materialize(request: MaterializeRequest) -> None:
             start_date = utils.make_tzaware(parser.parse(request.start_ts))
             end_date = utils.make_tzaware(parser.parse(request.end_ts))
 
-        store.materialize(
+        await run_in_threadpool(
+            store.materialize,
             start_date,
             end_date,
             request.feature_views,
@@ -458,14 +464,17 @@ def materialize(request: MaterializeRequest) -> None:
         )
 
     @app.post("/materialize-incremental", dependencies=[Depends(inject_user_details)])
-    def materialize_incremental(request: MaterializeIncrementalRequest) -> None:
+    async def materialize_incremental(request: MaterializeIncrementalRequest) -> None:
         for feature_view in request.feature_views or []:
+            resource = await _get_feast_object(feature_view, True)
             assert_permissions(
-                resource=_get_feast_object(feature_view, True),
+                resource=resource,
                 actions=[AuthzedAction.WRITE_ONLINE],
             )
-        store.materialize_incremental(
-            utils.make_tzaware(parser.parse(request.end_ts)), request.feature_views
+        await run_in_threadpool(
+            store.materialize_incremental,
+            utils.make_tzaware(parser.parse(request.end_ts)),
+            request.feature_views,
         )
 
     @app.exception_handler(Exception)
diff --git a/sdk/python/feast/feature_store.py b/sdk/python/feast/feature_store.py
index 611ad6dde85..7a0f362c8c7 100644
--- a/sdk/python/feast/feature_store.py
+++ b/sdk/python/feast/feature_store.py
@@ -1073,6 +1073,17 @@ def apply(
 
         self._registry.commit()
 
+        # Refresh the registry cache to ensure that changes are immediately visible
+        # This is especially important for UI and other clients that may be reading
+        # from the registry, as it ensures they see the updated state without waiting
+        # for the cache TTL to expire.
+        #
+        # Behavior by cache_mode:
+        # - sync mode: Immediate consistency - refresh after apply
+        # - thread mode: Eventual consistency - skip refresh, background thread handles it
+        if self.config.registry.cache_mode == "sync":
+            self.refresh_registry()
+
     def teardown(self):
         """Tears down all local and cloud resources for the feature store."""
         tables: List[FeatureView] = []
diff --git a/sdk/python/feast/feature_view.py b/sdk/python/feast/feature_view.py
index 1e57b56b8c5..a9406657a51 100644
--- a/sdk/python/feast/feature_view.py
+++ b/sdk/python/feast/feature_view.py
@@ -39,6 +39,7 @@
 from feast.protos.feast.core.Transformation_pb2 import (
     FeatureTransformationV2 as FeatureTransformationProto,
 )
+from feast.transformation.mode import TransformationMode
 from feast.types import from_value_type
 from feast.value_type import ValueType
 
@@ -86,6 +87,9 @@ class FeatureView(BaseFeatureView):
         tags: A dictionary of key-value pairs to store arbitrary metadata.
         owner: The owner of the feature view, typically the email of the primary
             maintainer.
+        mode: The transformation mode for feature transformations. Only meaningful when
+            transformations are applied. Choose from TransformationMode enum values
+            (e.g., PYTHON, PANDAS, RAY, SQL, SPARK, SUBSTRAIT).
     """
 
     name: str
@@ -102,6 +106,7 @@ class FeatureView(BaseFeatureView):
     tags: Dict[str, str]
     owner: str
     materialization_intervals: List[Tuple[datetime, datetime]]
+    mode: Optional[Union["TransformationMode", str]]
 
     def __init__(
         self,
@@ -117,6 +122,7 @@ def __init__(
         description: str = "",
         tags: Optional[Dict[str, str]] = None,
         owner: str = "",
+        mode: Optional[Union["TransformationMode", str]] = None,
     ):
         """
         Creates a FeatureView object.
@@ -140,6 +146,8 @@ def __init__(
             tags (optional): A dictionary of key-value pairs to store arbitrary metadata.
             owner (optional): The owner of the feature view, typically the email of the
                 primary maintainer.
+            mode (optional): The transformation mode for feature transformations. Only meaningful
+                when transformations are applied. Choose from TransformationMode enum values.
 
         Raises:
             ValueError: A field mapping conflicts with an Entity or a Feature.
@@ -148,6 +156,7 @@ def __init__(
         self.entities = [e.name for e in entities] if entities else [DUMMY_ENTITY_NAME]
         self.ttl = ttl
         schema = schema or []
+        self.mode = mode
 
         # Normalize source
         self.stream_source = None
@@ -252,6 +261,7 @@ def __init__(
         )
         self.online = online
         self.offline = offline
+        self.mode = mode
         self.materialization_intervals = []
 
     def __hash__(self):
@@ -439,6 +449,14 @@ def to_proto_spec(
                     substrait_transformation=transformation_proto,
                 )
 
+        mode_str = ""
+        if self.mode:
+            mode_str = (
+                self.mode.value
+                if isinstance(self.mode, TransformationMode)
+                else self.mode
+            )
+
         return FeatureViewSpecProto(
             name=self.name,
             entities=self.entities,
@@ -454,6 +472,7 @@ def to_proto_spec(
             stream_source=stream_source_proto,
             source_views=source_view_protos,
             feature_transformation=feature_transformation_proto,
+            mode=mode_str,
         )
 
     def to_proto_meta(self):
@@ -527,6 +546,7 @@ def _from_proto_internal(
 
         if has_transformation and cls == FeatureView:
             from feast.batch_feature_view import BatchFeatureView
+            from feast.transformation.factory import get_transformation_class_from_type
             from feast.transformation.python_transformation import PythonTransformation
             from feast.transformation.substrait_transformation import (
                 SubstraitTransformation,
@@ -538,14 +558,30 @@ def _from_proto_internal(
             transformation = None
 
             if feature_transformation_proto.HasField("user_defined_function"):
-                transformation = PythonTransformation.from_proto(
-                    feature_transformation_proto.user_defined_function
-                )
+                udf_proto = feature_transformation_proto.user_defined_function
+                if udf_proto.mode:
+                    try:
+                        transformation_class = get_transformation_class_from_type(
+                            udf_proto.mode
+                        )
+                        transformation = transformation_class.from_proto(udf_proto)
+                    except (ValueError, KeyError):
+                        transformation = PythonTransformation.from_proto(udf_proto)
+                else:
+                    transformation = PythonTransformation.from_proto(udf_proto)
             elif feature_transformation_proto.HasField("substrait_transformation"):
                 transformation = SubstraitTransformation.from_proto(
                     feature_transformation_proto.substrait_transformation
                 )
 
+            mode: Union[TransformationMode, str]
+            if feature_view_proto.spec.mode:
+                mode = feature_view_proto.spec.mode
+            elif transformation and hasattr(transformation, "mode"):
+                mode = transformation.mode
+            else:
+                mode = TransformationMode.PYTHON
+
             feature_view: FeatureView = BatchFeatureView(  # type: ignore[assignment]
                 name=feature_view_proto.spec.name,
                 description=feature_view_proto.spec.description,
@@ -560,9 +596,14 @@ def _from_proto_internal(
                 ),
                 source=source_views if source_views else batch_source,  # type: ignore[arg-type]
                 sink_source=batch_source if source_views else None,
+                mode=mode,
                 feature_transformation=transformation,
             )
         else:
+            mode_from_spec = (
+                feature_view_proto.spec.mode if feature_view_proto.spec.mode else None
+            )
+
             feature_view = cls(  # type: ignore[assignment]
                 name=feature_view_proto.spec.name,
                 description=feature_view_proto.spec.description,
@@ -577,6 +618,7 @@ def _from_proto_internal(
                 ),
                 source=source_views if source_views else batch_source,
                 sink_source=batch_source if source_views else None,
+                mode=mode_from_spec,
             )
         if stream_source:
             feature_view.stream_source = stream_source
diff --git a/sdk/python/feast/infra/compute_engines/local/backends/__init__.py b/sdk/python/feast/infra/compute_engines/backends/__init__.py
similarity index 100%
rename from sdk/python/feast/infra/compute_engines/local/backends/__init__.py
rename to sdk/python/feast/infra/compute_engines/backends/__init__.py
diff --git a/sdk/python/feast/infra/compute_engines/local/backends/base.py b/sdk/python/feast/infra/compute_engines/backends/base.py
similarity index 100%
rename from sdk/python/feast/infra/compute_engines/local/backends/base.py
rename to sdk/python/feast/infra/compute_engines/backends/base.py
diff --git a/sdk/python/feast/infra/compute_engines/local/backends/factory.py b/sdk/python/feast/infra/compute_engines/backends/factory.py
similarity index 84%
rename from sdk/python/feast/infra/compute_engines/local/backends/factory.py
rename to sdk/python/feast/infra/compute_engines/backends/factory.py
index 6d3774f6393..ffe969f3003 100644
--- a/sdk/python/feast/infra/compute_engines/local/backends/factory.py
+++ b/sdk/python/feast/infra/compute_engines/backends/factory.py
@@ -3,8 +3,8 @@
 import pandas as pd
 import pyarrow
 
-from feast.infra.compute_engines.local.backends.base import DataFrameBackend
-from feast.infra.compute_engines.local.backends.pandas_backend import PandasBackend
+from feast.infra.compute_engines.backends.base import DataFrameBackend
+from feast.infra.compute_engines.backends.pandas_backend import PandasBackend
 
 
 class BackendFactory:
@@ -46,7 +46,7 @@ def _is_polars(entity_df) -> bool:
 
     @staticmethod
     def _get_polars_backend():
-        from feast.infra.compute_engines.local.backends.polars_backend import (
+        from feast.infra.compute_engines.backends.polars_backend import (
             PolarsBackend,
         )
 
diff --git a/sdk/python/feast/infra/compute_engines/local/backends/pandas_backend.py b/sdk/python/feast/infra/compute_engines/backends/pandas_backend.py
similarity index 93%
rename from sdk/python/feast/infra/compute_engines/local/backends/pandas_backend.py
rename to sdk/python/feast/infra/compute_engines/backends/pandas_backend.py
index 76ddd688424..8ea5a4a9213 100644
--- a/sdk/python/feast/infra/compute_engines/local/backends/pandas_backend.py
+++ b/sdk/python/feast/infra/compute_engines/backends/pandas_backend.py
@@ -3,7 +3,7 @@
 import pandas as pd
 import pyarrow as pa
 
-from feast.infra.compute_engines.local.backends.base import DataFrameBackend
+from feast.infra.compute_engines.backends.base import DataFrameBackend
 
 
 class PandasBackend(DataFrameBackend):
diff --git a/sdk/python/feast/infra/compute_engines/local/backends/polars_backend.py b/sdk/python/feast/infra/compute_engines/backends/polars_backend.py
similarity index 94%
rename from sdk/python/feast/infra/compute_engines/local/backends/polars_backend.py
rename to sdk/python/feast/infra/compute_engines/backends/polars_backend.py
index 352ffecdab8..92e348c3652 100644
--- a/sdk/python/feast/infra/compute_engines/local/backends/polars_backend.py
+++ b/sdk/python/feast/infra/compute_engines/backends/polars_backend.py
@@ -3,7 +3,7 @@
 import polars as pl
 import pyarrow as pa
 
-from feast.infra.compute_engines.local.backends.base import DataFrameBackend
+from feast.infra.compute_engines.backends.base import DataFrameBackend
 
 
 class PolarsBackend(DataFrameBackend):
diff --git a/sdk/python/feast/infra/compute_engines/feature_builder.py b/sdk/python/feast/infra/compute_engines/feature_builder.py
index fbea3a85d26..8510b676c07 100644
--- a/sdk/python/feast/infra/compute_engines/feature_builder.py
+++ b/sdk/python/feast/infra/compute_engines/feature_builder.py
@@ -154,6 +154,15 @@ def get_column_info(
         )
         field_mapping = self.get_field_mapping(self.task.feature_view)
 
+        # For feature views with transformations that need access to all source columns,
+        # we need to read ALL source columns, not just the output feature columns.
+        # This is specifically for transformations that create new columns or need raw data.
+        mode = getattr(getattr(view, "feature_transformation", None), "mode", None)
+        if mode == "ray" or getattr(mode, "value", None) == "ray":
+            # Signal to read all columns by passing empty list for feature_cols
+            # The transformation will produce the output columns defined in the schema
+            feature_cols = []
+
         return ColumnInfo(
             join_keys=join_keys,
             feature_cols=feature_cols,
diff --git a/sdk/python/feast/infra/compute_engines/local/compute.py b/sdk/python/feast/infra/compute_engines/local/compute.py
index 556468f5e1d..26f537da7cf 100644
--- a/sdk/python/feast/infra/compute_engines/local/compute.py
+++ b/sdk/python/feast/infra/compute_engines/local/compute.py
@@ -12,10 +12,10 @@
     MaterializationTask,
 )
 from feast.infra.common.retrieval_task import HistoricalRetrievalTask
+from feast.infra.compute_engines.backends.base import DataFrameBackend
+from feast.infra.compute_engines.backends.factory import BackendFactory
 from feast.infra.compute_engines.base import ComputeEngine
 from feast.infra.compute_engines.dag.context import ExecutionContext
-from feast.infra.compute_engines.local.backends.base import DataFrameBackend
-from feast.infra.compute_engines.local.backends.factory import BackendFactory
 from feast.infra.compute_engines.local.feature_builder import LocalFeatureBuilder
 from feast.infra.compute_engines.local.job import (
     LocalMaterializationJob,
diff --git a/sdk/python/feast/infra/compute_engines/local/feature_builder.py b/sdk/python/feast/infra/compute_engines/local/feature_builder.py
index 9b2306c0f01..a98573621fb 100644
--- a/sdk/python/feast/infra/compute_engines/local/feature_builder.py
+++ b/sdk/python/feast/infra/compute_engines/local/feature_builder.py
@@ -2,8 +2,8 @@
 
 from feast.infra.common.materialization_job import MaterializationTask
 from feast.infra.common.retrieval_task import HistoricalRetrievalTask
+from feast.infra.compute_engines.backends.base import DataFrameBackend
 from feast.infra.compute_engines.feature_builder import FeatureBuilder
-from feast.infra.compute_engines.local.backends.base import DataFrameBackend
 from feast.infra.compute_engines.local.nodes import (
     LocalAggregationNode,
     LocalDedupNode,
diff --git a/sdk/python/feast/infra/compute_engines/local/nodes.py b/sdk/python/feast/infra/compute_engines/local/nodes.py
index 870a098261d..985a089daae 100644
--- a/sdk/python/feast/infra/compute_engines/local/nodes.py
+++ b/sdk/python/feast/infra/compute_engines/local/nodes.py
@@ -5,11 +5,11 @@
 
 from feast import BatchFeatureView, StreamFeatureView
 from feast.data_source import DataSource
+from feast.infra.compute_engines.backends.base import DataFrameBackend
 from feast.infra.compute_engines.dag.context import ColumnInfo, ExecutionContext
 from feast.infra.compute_engines.dag.model import DAGFormat
 from feast.infra.compute_engines.dag.node import DAGNode
 from feast.infra.compute_engines.local.arrow_table_value import ArrowTableValue
-from feast.infra.compute_engines.local.backends.base import DataFrameBackend
 from feast.infra.compute_engines.local.local_node import LocalNode
 from feast.infra.compute_engines.utils import (
     create_offline_store_retrieval_job,
diff --git a/sdk/python/feast/infra/compute_engines/ray/compute.py b/sdk/python/feast/infra/compute_engines/ray/compute.py
index 24d98cae7fb..a5c1b3caab5 100644
--- a/sdk/python/feast/infra/compute_engines/ray/compute.py
+++ b/sdk/python/feast/infra/compute_engines/ray/compute.py
@@ -2,8 +2,6 @@
 from datetime import datetime
 from typing import Sequence, Union
 
-import ray
-
 from feast import (
     BatchFeatureView,
     Entity,
@@ -26,6 +24,10 @@
 )
 from feast.infra.compute_engines.ray.utils import write_to_online_store
 from feast.infra.offline_stores.offline_store import RetrievalJob
+from feast.infra.ray_initializer import (
+    ensure_ray_initialized,
+    get_ray_wrapper,
+)
 from feast.infra.registry.base_registry import BaseRegistry
 
 logger = logging.getLogger(__name__)
@@ -58,37 +60,7 @@ def __init__(
 
     def _ensure_ray_initialized(self):
         """Ensure Ray is initialized with proper configuration."""
-        if not ray.is_initialized():
-            if self.config.ray_address:
-                ray.init(
-                    address=self.config.ray_address,
-                    ignore_reinit_error=True,
-                    include_dashboard=False,
-                )
-            else:
-                ray_init_args = {
-                    "ignore_reinit_error": True,
-                    "include_dashboard": False,
-                }
-
-                # Add configuration from ray_conf if provided
-                if self.config.ray_conf:
-                    ray_init_args.update(self.config.ray_conf)
-
-                ray.init(**ray_init_args)
-
-        # Configure Ray context for optimal performance
-        from ray.data.context import DatasetContext
-
-        ctx = DatasetContext.get_current()
-        ctx.enable_tensor_extension_casting = False
-
-        # Log Ray cluster information
-        cluster_resources = ray.cluster_resources()
-        logger.info(
-            f"Ray cluster initialized with {cluster_resources.get('CPU', 0)} CPUs, "
-            f"{cluster_resources.get('memory', 0) / (1024**3):.1f}GB memory"
-        )
+        ensure_ray_initialized(self.config)
 
     def update(
         self,
@@ -230,7 +202,8 @@ def _materialize_from_offline_store(
 
                 # Write to sink_source using Ray data
                 try:
-                    ray_dataset = ray.data.from_arrow(arrow_table)
+                    ray_wrapper = get_ray_wrapper()
+                    ray_dataset = ray_wrapper.from_arrow(arrow_table)
                     ray_dataset.write_parquet(sink_source.path)
                 except Exception as e:
                     logger.error(
diff --git a/sdk/python/feast/infra/compute_engines/ray/config.py b/sdk/python/feast/infra/compute_engines/ray/config.py
index c6d74d262dd..bb6b63a05c5 100644
--- a/sdk/python/feast/infra/compute_engines/ray/config.py
+++ b/sdk/python/feast/infra/compute_engines/ray/config.py
@@ -46,9 +46,6 @@ class RayComputeEngineConfig(FeastConfigBaseModel):
     enable_optimization: bool = True
     """Enable automatic performance optimizations."""
 
-    execution_timeout_seconds: Optional[int] = None
-    """Timeout for job execution in seconds."""
-
     @property
     def window_size_timedelta(self) -> timedelta:
         """Convert window size string to timedelta."""
@@ -64,3 +61,19 @@ def window_size_timedelta(self) -> timedelta:
         else:
             # Default to 1 hour
             return timedelta(hours=1)
+
+    # KubeRay/CodeFlare SDK configurations
+    use_kuberay: Optional[bool] = None
+    """Whether to use KubeRay/CodeFlare SDK for Ray cluster management"""
+
+    cluster_name: Optional[str] = None
+    """Name of the KubeRay cluster to connect to (required for KubeRay mode)"""
+
+    auth_token: Optional[str] = None
+    """Authentication token for Ray cluster connection (for secure clusters)"""
+
+    kuberay_conf: Optional[Dict[str, Any]] = None
+    """KubeRay/CodeFlare configuration parameters (passed to CodeFlare SDK)"""
+
+    enable_ray_logging: bool = False
+    """Enable Ray progress bars and verbose logging"""
diff --git a/sdk/python/feast/infra/compute_engines/ray/feature_builder.py b/sdk/python/feast/infra/compute_engines/ray/feature_builder.py
index 07c5c6f1113..49a957da183 100644
--- a/sdk/python/feast/infra/compute_engines/ray/feature_builder.py
+++ b/sdk/python/feast/infra/compute_engines/ray/feature_builder.py
@@ -161,6 +161,7 @@ def build_output_nodes(self, view, final_node):
             name="output",
             feature_view=view,
             inputs=[final_node],
+            config=self.config,
         )
 
         self.nodes.append(node)
@@ -275,6 +276,7 @@ def _build_materialization_plan(self) -> ExecutionPlan:
                 name=f"{view.name}:write",
                 feature_view=view,
                 inputs=[processing_node],
+                config=self.config,
             )
 
             view_to_write_node[view.name] = write_node
diff --git a/sdk/python/feast/infra/compute_engines/ray/job.py b/sdk/python/feast/infra/compute_engines/ray/job.py
index b2e88f1d5c5..06eea4e5d88 100644
--- a/sdk/python/feast/infra/compute_engines/ray/job.py
+++ b/sdk/python/feast/infra/compute_engines/ray/job.py
@@ -5,7 +5,6 @@
 
 import pandas as pd
 import pyarrow as pa
-import ray
 from ray.data import Dataset
 
 from feast import OnDemandFeatureView
@@ -21,6 +20,7 @@
 from feast.infra.compute_engines.dag.value import DAGValue
 from feast.infra.offline_stores.file_source import SavedDatasetFileStorage
 from feast.infra.offline_stores.offline_store import RetrievalJob, RetrievalMetadata
+from feast.infra.ray_initializer import get_ray_wrapper
 from feast.repo_config import RepoConfig
 from feast.saved_dataset import SavedDatasetStorage
 
@@ -69,10 +69,11 @@ def _ensure_executed(self) -> DAGValue:
                     self._result_dataset = result.data
                 else:
                     # If result is not a Ray Dataset, convert it
+                    ray_wrapper = get_ray_wrapper()
                     if isinstance(result.data, pd.DataFrame):
-                        self._result_dataset = ray.data.from_pandas(result.data)
+                        self._result_dataset = ray_wrapper.from_pandas(result.data)
                     elif isinstance(result.data, pa.Table):
-                        self._result_dataset = ray.data.from_arrow(result.data)
+                        self._result_dataset = ray_wrapper.from_arrow(result.data)
                     else:
                         raise ValueError(
                             f"Unsupported result type: {type(result.data)}"
diff --git a/sdk/python/feast/infra/compute_engines/ray/nodes.py b/sdk/python/feast/infra/compute_engines/ray/nodes.py
index eaf48847113..32126a9e42f 100644
--- a/sdk/python/feast/infra/compute_engines/ray/nodes.py
+++ b/sdk/python/feast/infra/compute_engines/ray/nodes.py
@@ -23,6 +23,7 @@
     write_to_online_store,
 )
 from feast.infra.compute_engines.utils import create_offline_store_retrieval_job
+from feast.infra.ray_initializer import get_ray_wrapper
 from feast.infra.ray_shared_utils import (
     apply_field_mapping,
     broadcast_join,
@@ -72,10 +73,12 @@ def execute(self, context: ExecutionContext) -> DAGValue:
             else:
                 try:
                     arrow_table = retrieval_job.to_arrow()
-                    ray_dataset = ray.data.from_arrow(arrow_table)
+                    ray_wrapper = get_ray_wrapper()
+                    ray_dataset = ray_wrapper.from_arrow(arrow_table)
                 except Exception:
                     df = retrieval_job.to_df()
-                    ray_dataset = ray.data.from_pandas(df)
+                    ray_wrapper = get_ray_wrapper()
+                    ray_dataset = ray_wrapper.from_pandas(df)
 
             field_mapping = getattr(self.source, "field_mapping", None)
             if field_mapping:
@@ -130,7 +133,8 @@ def execute(self, context: ExecutionContext) -> DAGValue:
 
         entity_df = context.entity_df
         if isinstance(entity_df, pd.DataFrame):
-            entity_dataset = ray.data.from_pandas(entity_df)
+            ray_wrapper = get_ray_wrapper()
+            entity_dataset = ray_wrapper.from_pandas(entity_df)
         else:
             entity_dataset = entity_df
 
@@ -169,7 +173,9 @@ def join_with_aggregated_features(batch: pd.DataFrame) -> pd.DataFrame:
                 return result
 
             joined_dataset = entity_dataset.map_batches(
-                join_with_aggregated_features, batch_format="pandas"
+                join_with_aggregated_features,
+                batch_format="pandas",
+                concurrency=self.config.max_workers or 12,
             )
         else:
             if feature_size <= self.config.broadcast_join_threshold_mb * 1024 * 1024:
@@ -270,8 +276,8 @@ def apply_filters(batch: pd.DataFrame) -> pd.DataFrame:
                     else:
                         # Use current time for TTL calculation (real-time retrieval)
                         # Check if timestamp column is timezone-aware
-                        if pd.api.types.is_datetime64tz_dtype(
-                            filtered_batch[timestamp_col]
+                        if isinstance(
+                            filtered_batch[timestamp_col].dtype, pd.DatetimeTZDtype
                         ):
                             # Use timezone-aware current time
                             current_time = datetime.now(timezone.utc)
@@ -423,7 +429,8 @@ def _fallback_pandas_aggregation(self, dataset: Dataset, agg_dict: dict) -> Data
                 result_df = result_df.reset_index()
 
             # Convert back to Ray Dataset
-            return ray.data.from_pandas(result_df)
+            ray_wrapper = get_ray_wrapper()
+            return ray_wrapper.from_pandas(result_df)
         else:
             return dataset
 
@@ -512,31 +519,59 @@ def execute(self, context: ExecutionContext) -> DAGValue:
         input_value.assert_format(DAGFormat.RAY)
         dataset: Dataset = input_value.data
 
-        transformation_serialized = None
-        if hasattr(self.transformation, "udf") and callable(self.transformation.udf):
-            transformation_serialized = dill.dumps(self.transformation.udf)
-        elif callable(self.transformation):
-            transformation_serialized = dill.dumps(self.transformation)
+        # Check transformation mode
+        from feast.transformation.mode import TransformationMode
 
-        @safe_batch_processor
-        def apply_transformation_with_serialized_udf(
-            batch: pd.DataFrame,
-        ) -> pd.DataFrame:
-            """Apply the transformation using pre-serialized UDF."""
-            if transformation_serialized:
-                transformation_func = dill.loads(transformation_serialized)
-                transformed_batch = transformation_func(batch)
+        transformation_mode = getattr(
+            self.transformation, "mode", TransformationMode.PYTHON
+        )
+        is_ray_native = transformation_mode in (TransformationMode.RAY, "ray")
+        if is_ray_native:
+            transformation_func = None
+            if hasattr(self.transformation, "udf") and callable(
+                self.transformation.udf
+            ):
+                transformation_func = self.transformation.udf
+            elif callable(self.transformation):
+                transformation_func = self.transformation
+
+            if transformation_func:
+                transformed_dataset = transformation_func(dataset)
             else:
                 logger.warning(
-                    "No serialized transformation available, returning original batch"
+                    "No transformation function available in RAY mode, returning original dataset"
                 )
-                transformed_batch = batch
+                transformed_dataset = dataset
+        else:
+            transformation_serialized = None
+            if hasattr(self.transformation, "udf") and callable(
+                self.transformation.udf
+            ):
+                transformation_serialized = dill.dumps(self.transformation.udf)
+            elif callable(self.transformation):
+                transformation_serialized = dill.dumps(self.transformation)
 
-            return transformed_batch
+            @safe_batch_processor
+            def apply_transformation_with_serialized_udf(
+                batch: pd.DataFrame,
+            ) -> pd.DataFrame:
+                """Apply the transformation using pre-serialized UDF."""
+                if transformation_serialized:
+                    transformation_func = dill.loads(transformation_serialized)
+                    transformed_batch = transformation_func(batch)
+                else:
+                    logger.warning(
+                        "No serialized transformation available, returning original batch"
+                    )
+                    transformed_batch = batch
 
-        transformed_dataset = dataset.map_batches(
-            apply_transformation_with_serialized_udf, batch_format="pandas"
-        )
+                return transformed_batch
+
+            transformed_dataset = dataset.map_batches(
+                apply_transformation_with_serialized_udf,
+                batch_format="pandas",
+                concurrency=self.config.max_workers or 12,
+            )
 
         return DAGValue(
             data=transformed_dataset,
@@ -593,7 +628,9 @@ def apply_transformation(batch: pd.DataFrame) -> pd.DataFrame:
                     return transformation_func(batch)
 
                 transformed_dataset = parent_value.data.map_batches(
-                    apply_transformation
+                    apply_transformation,
+                    batch_format="pandas",
+                    concurrency=self.config.max_workers or 12,
                 )
                 return DAGValue(
                     data=transformed_dataset,
@@ -625,9 +662,11 @@ def __init__(
         name: str,
         feature_view: Union[BatchFeatureView, StreamFeatureView, FeatureView],
         inputs=None,
+        config: Optional[RayComputeEngineConfig] = None,
     ):
         super().__init__(name, inputs=inputs)
         self.feature_view = feature_view
+        self.config = config
 
     def execute(self, context: ExecutionContext) -> DAGValue:
         """Execute the write operation."""
@@ -671,7 +710,9 @@ def write_batch_with_serialized_artifacts(batch: pd.DataFrame) -> pd.DataFrame:
             return batch
 
         written_dataset = dataset.map_batches(
-            write_batch_with_serialized_artifacts, batch_format="pandas"
+            write_batch_with_serialized_artifacts,
+            batch_format="pandas",
+            concurrency=self.config.max_workers if self.config else 12,
         )
         written_dataset = written_dataset.materialize()
 
diff --git a/sdk/python/feast/infra/feature_servers/multicloud/requirements.txt b/sdk/python/feast/infra/feature_servers/multicloud/requirements.txt
index 27bf1536bc4..4b3c6f959f0 100644
--- a/sdk/python/feast/infra/feature_servers/multicloud/requirements.txt
+++ b/sdk/python/feast/infra/feature_servers/multicloud/requirements.txt
@@ -1,2 +1,2 @@
 # keep VERSION on line #2, this is critical to release CI
-feast[minimal] == 0.55.0
+feast[minimal] == 0.56.0
diff --git a/sdk/python/feast/infra/offline_stores/contrib/clickhouse_offline_store/clickhouse.py b/sdk/python/feast/infra/offline_stores/contrib/clickhouse_offline_store/clickhouse.py
index bca6339fb15..5e8cf3d9053 100644
--- a/sdk/python/feast/infra/offline_stores/contrib/clickhouse_offline_store/clickhouse.py
+++ b/sdk/python/feast/infra/offline_stores/contrib/clickhouse_offline_store/clickhouse.py
@@ -191,6 +191,43 @@ def pull_latest_from_table_or_query(
             on_demand_feature_views=None,
         )
 
+    @staticmethod
+    def pull_all_from_table_or_query(
+        config: RepoConfig,
+        data_source: DataSource,
+        join_key_columns: List[str],
+        feature_name_columns: List[str],
+        timestamp_field: str,
+        created_timestamp_column: Optional[str] = None,
+        start_date: Optional[datetime] = None,
+        end_date: Optional[datetime] = None,
+    ) -> RetrievalJob:
+        assert isinstance(config.offline_store, ClickhouseOfflineStoreConfig)
+        assert isinstance(data_source, ClickhouseSource)
+
+        from_expression = data_source.get_table_query_string()
+
+        timestamp_fields = [timestamp_field]
+
+        if created_timestamp_column:
+            timestamp_fields.append(created_timestamp_column)
+
+        field_string = ", ".join(
+            join_key_columns + feature_name_columns + timestamp_fields
+        )
+
+        query = f"""
+            SELECT {field_string}
+            FROM {from_expression}
+            WHERE {timestamp_field} BETWEEN parseDateTimeBestEffort('{start_date}') AND parseDateTimeBestEffort('{end_date}')
+        """
+
+        return ClickhouseRetrievalJob(
+            query=query,
+            config=config,
+            full_feature_names=False,
+        )
+
 
 class ClickhouseRetrievalJob(PostgreSQLRetrievalJob):
     def _to_df_internal(self, timeout: Optional[int] = None) -> pd.DataFrame:
diff --git a/sdk/python/feast/infra/offline_stores/contrib/ray_offline_store/ray.py b/sdk/python/feast/infra/offline_stores/contrib/ray_offline_store/ray.py
index 1ec2853cf95..98247c6c0e0 100644
--- a/sdk/python/feast/infra/offline_stores/contrib/ray_offline_store/ray.py
+++ b/sdk/python/feast/infra/offline_stores/contrib/ray_offline_store/ray.py
@@ -11,7 +11,6 @@
 import pandas as pd
 import pyarrow as pa
 import ray
-import ray.data
 from ray.data import Dataset
 from ray.data.context import DatasetContext
 
@@ -39,6 +38,10 @@
     get_pyarrow_schema_from_batch_source,
     infer_event_timestamp_from_entity_df,
 )
+from feast.infra.ray_initializer import (
+    ensure_ray_initialized,
+    get_ray_wrapper,
+)
 from feast.infra.ray_shared_utils import (
     _build_required_columns,
     apply_field_mapping,
@@ -338,6 +341,19 @@ class RayOfflineStoreConfig(FeastConfigBaseModel):
     # Ray configuration for resource management (memory, CPU limits)
     ray_conf: Optional[Dict[str, Any]] = None
 
+    # KubeRay/CodeFlare SDK configurations
+    use_kuberay: Optional[bool] = None
+    """Whether to use KubeRay/CodeFlare SDK for Ray cluster management"""
+
+    cluster_name: Optional[str] = None
+    """Name of the KubeRay cluster to connect to (required for KubeRay mode)"""
+
+    auth_token: Optional[str] = None
+    """Authentication token for Ray cluster connection (for secure clusters)"""
+
+    kuberay_conf: Optional[Dict[str, Any]] = None
+    """KubeRay/CodeFlare configuration parameters (passed to CodeFlare SDK)"""
+
 
 class RayResourceManager:
     """
@@ -350,10 +366,18 @@ def __init__(self, config: Optional[RayOfflineStoreConfig] = None) -> None:
         Initialize the resource manager with cluster resource information.
         """
         self.config = config or RayOfflineStoreConfig()
+
+        if not ray.is_initialized():
+            self.cluster_resources = {"CPU": 4, "memory": 8 * 1024**3}
+            self.available_memory = 8 * 1024**3
+            self.available_cpus = 4
+            self.num_nodes = 1
+            return
+
         self.cluster_resources = ray.cluster_resources()
         self.available_memory = self.cluster_resources.get("memory", 8 * 1024**3)
         self.available_cpus = int(self.cluster_resources.get("CPU", 4))
-        self.num_nodes = len(ray.nodes()) if ray.is_initialized() else 1
+        self.num_nodes = len(ray.nodes())
 
     def configure_ray_context(self) -> None:
         """
@@ -367,7 +391,8 @@ def configure_ray_context(self) -> None:
         else:
             ctx.target_shuffle_buffer_size = 512 * 1024**2
             ctx.target_max_block_size = 128 * 1024**2
-        ctx.min_parallelism = self.available_cpus
+
+        ctx.read_op_min_num_blocks = self.available_cpus
         multiplier = (
             self.config.max_parallelism_multiplier
             if self.config.max_parallelism_multiplier is not None
@@ -457,8 +482,8 @@ def optimize_dataset_for_join(self, ds: Dataset, join_keys: List[str]) -> Datase
         if not join_keys:
             # For datasets without join keys, use simple repartitioning
             return ds.repartition(num_blocks=optimal_partitions)
-        # For datasets with join keys, use shuffle for better distribution
-        return ds.random_shuffle(num_blocks=optimal_partitions)
+        # For datasets with join keys, repartition then shuffle for better distribution
+        return ds.repartition(num_blocks=optimal_partitions).random_shuffle()
 
     def _manual_point_in_time_join(
         self,
@@ -919,7 +944,7 @@ def _create_metadata(self) -> RetrievalMetadata:
         else:
             try:
                 result = self._resolve()
-                if isinstance(result, Dataset):
+                if is_ray_data(result):
                     timestamp_col = _safe_infer_event_timestamp_column(
                         result, "event_timestamp"
                     )
@@ -964,11 +989,12 @@ def _get_ray_dataset(self) -> Dataset:
             return self._cached_dataset
 
         result = self._resolve()
-        if isinstance(result, Dataset):
+        if is_ray_data(result):
             self._cached_dataset = result
             return result
         elif isinstance(result, pd.DataFrame):
-            self._cached_dataset = ray.data.from_pandas(result)
+            ray_wrapper = get_ray_wrapper()
+            self._cached_dataset = ray_wrapper.from_pandas(result)
             return self._cached_dataset
         else:
             raise ValueError(f"Unsupported result type: {type(result)}")
@@ -1225,82 +1251,13 @@ def _suppress_ray_logging() -> None:
     @staticmethod
     def _ensure_ray_initialized(config: Optional[RepoConfig] = None) -> None:
         """Ensure Ray is initialized with proper configuration."""
-        ray_config = None
-        if config and hasattr(config, "offline_store"):
-            ray_config = config.offline_store
-            if isinstance(ray_config, RayOfflineStoreConfig):
-                if not ray_config.enable_ray_logging:
-                    RayOfflineStore._suppress_ray_logging()
-
-        if not ray.is_initialized():
-            ray_init_kwargs: Dict[str, Any] = {
-                "ignore_reinit_error": True,
-                "include_dashboard": False,
-            }
-
-            if (
-                ray_config
-                and isinstance(ray_config, RayOfflineStoreConfig)
-                and not ray_config.enable_ray_logging
-            ):
-                ray_init_kwargs.update(
-                    {
-                        "log_to_driver": False,
-                        "logging_level": "ERROR",
-                    }
-                )
-
-            if config and hasattr(config, "offline_store"):
-                if isinstance(ray_config, RayOfflineStoreConfig):
-                    if ray_config.ray_address:
-                        ray_init_kwargs["address"] = ray_config.ray_address
-                    else:
-                        ray_init_kwargs.update(
-                            {
-                                "_node_ip_address": os.getenv(
-                                    "RAY_NODE_IP", "127.0.0.1"
-                                ),
-                                "num_cpus": os.cpu_count() or 4,
-                            }
-                        )
-
-                    if ray_config.ray_conf:
-                        ray_init_kwargs.update(ray_config.ray_conf)
-                else:
-                    pass  # Use default initialization
-
-            ray.init(**ray_init_kwargs)
-
-        ctx = DatasetContext.get_current()
-        ctx.shuffle_strategy = "sort"  # type: ignore
-        ctx.enable_tensor_extension_casting = False
-
-        if (
-            ray_config
-            and isinstance(ray_config, RayOfflineStoreConfig)
-            and not ray_config.enable_ray_logging
-        ):
-            RayOfflineStore._suppress_ray_logging()
-
-        if ray.is_initialized():
-            cluster_resources = ray.cluster_resources()
-            if (
-                not ray_config
-                or not isinstance(ray_config, RayOfflineStoreConfig)
-                or ray_config.enable_ray_logging
-            ):
-                logger.info(
-                    f"Ray cluster initialized with {cluster_resources.get('CPU', 0)} CPUs, "
-                    f"{cluster_resources.get('memory', 0) / (1024**3):.1f}GB memory"
-                )
+        ensure_ray_initialized(config)
 
     def _init_ray(self, config: RepoConfig) -> None:
         ray_config = config.offline_store
         assert isinstance(ray_config, RayOfflineStoreConfig)
-        RayOfflineStore._ensure_ray_initialized(config)
 
-        if not ray_config.enable_ray_logging:
-            RayOfflineStore._suppress_ray_logging()
+        RayOfflineStore._ensure_ray_initialized(config)
 
         if self._resource_manager is None:
             self._resource_manager = RayResourceManager(ray_config)
@@ -1378,12 +1335,13 @@ def offline_write_batch(
         batch_source_path = feature_view.batch_source.file_options.uri
         feature_path = FileSource.get_uri_for_file_path(repo_path, batch_source_path)
 
-        ds = ray.data.from_arrow(table)
+        ray_wrapper = get_ray_wrapper()
+        ds = ray_wrapper.from_arrow(table)
 
         try:
             if feature_path.endswith(".parquet"):
                 if os.path.exists(feature_path):
-                    existing_ds = ray.data.read_parquet(feature_path)
+                    existing_ds = ray_wrapper.read_parquet(feature_path)
                     combined_ds = existing_ds.union(ds)
                     combined_ds.write_parquet(feature_path)
                 else:
@@ -1408,7 +1366,7 @@ def offline_write_batch(
                     df.to_parquet(feature_path, index=False)
             else:
                 os.makedirs(feature_path, exist_ok=True)
-                ds_fallback = ray.data.from_pandas(df)
+                ds_fallback = ray_wrapper.from_pandas(df)
                 ds_fallback.write_parquet(feature_path)
 
             if progress:
@@ -1443,15 +1401,21 @@ def _process_filtered_batch(
             return _handle_empty_dataframe_case(
                 join_key_columns, feature_name_columns, timestamp_columns
             )
-        all_required_columns = _build_required_columns(
-            join_key_columns, feature_name_columns, timestamp_columns
-        )
+
         if not join_key_columns:
             batch[DUMMY_ENTITY_ID] = DUMMY_ENTITY_VAL
-        available_columns = [
-            col for col in all_required_columns if col in batch.columns
-        ]
-        batch = batch[available_columns]
+
+        # If feature_name_columns is empty, it means "keep all columns" (for transformations)
+        # Otherwise, filter to only the requested columns
+        if feature_name_columns:
+            all_required_columns = _build_required_columns(
+                join_key_columns, feature_name_columns, timestamp_columns
+            )
+            available_columns = [
+                col for col in all_required_columns if col in batch.columns
+            ]
+            batch = batch[available_columns]
+
         if (
             "event_timestamp" not in batch.columns
             and timestamp_field_mapped != "event_timestamp"
@@ -1473,8 +1437,22 @@ def _load_and_filter_dataset(
     ) -> pd.DataFrame:
         try:
             field_mapping = getattr(data_source, "field_mapping", None)
+
+            if not feature_name_columns:
+                columns_to_read = None
+            else:
+                columns_to_read = list(
+                    set(join_key_columns + feature_name_columns + [timestamp_field])
+                )
+                if created_timestamp_column:
+                    columns_to_read.append(created_timestamp_column)
+
             ds = RayOfflineStore._create_filtered_dataset(
-                source_path, timestamp_field, start_date, end_date
+                source_path,
+                timestamp_field,
+                start_date,
+                end_date,
+                columns=columns_to_read,
             )
             df = ds.to_pandas()
             if field_mapping:
@@ -1523,8 +1501,22 @@ def _load_and_filter_dataset_ray(
     ) -> Dataset:
         try:
             field_mapping = getattr(data_source, "field_mapping", None)
+
+            if not feature_name_columns:
+                columns_to_read = None
+            else:
+                columns_to_read = list(
+                    set(join_key_columns + feature_name_columns + [timestamp_field])
+                )
+                if created_timestamp_column:
+                    columns_to_read.append(created_timestamp_column)
+
             ds = RayOfflineStore._create_filtered_dataset(
-                source_path, timestamp_field, start_date, end_date
+                source_path,
+                timestamp_field,
+                start_date,
+                end_date,
+                columns=columns_to_read,
             )
             if field_mapping:
                 ds = apply_field_mapping(ds, field_mapping)
@@ -1776,10 +1768,11 @@ def write_logged_features(
         absolute_path = FileSource.get_uri_for_file_path(repo_path, destination.path)
 
         try:
+            ray_wrapper = get_ray_wrapper()
             if isinstance(data, Path):
-                ds = ray.data.read_parquet(str(data))
+                ds = ray_wrapper.read_parquet(str(data))
             else:
-                ds = ray.data.from_arrow(data)
+                ds = ray_wrapper.from_arrow(data)
 
                 # Normalize feature timestamp precision to seconds to match test expectations during write
                 # Note: Don't normalize __log_timestamp as it's used for time range filtering
@@ -1829,9 +1822,11 @@ def _create_filtered_dataset(
         timestamp_field: str,
         start_date: Optional[datetime] = None,
         end_date: Optional[datetime] = None,
+        columns: Optional[List[str]] = None,
     ) -> Dataset:
         """Helper method to create a filtered dataset based on timestamp range."""
-        ds = ray.data.read_parquet(source_path)
+        ray_wrapper = get_ray_wrapper()
+        ds = ray_wrapper.read_parquet(source_path, columns=columns)
 
         try:
             col_names = ds.schema().names
@@ -1888,11 +1883,12 @@ def get_historical_features(
         store._init_ray(config)
 
         # Load entity_df as Ray dataset for distributed processing
+        ray_wrapper = get_ray_wrapper()
         if isinstance(entity_df, str):
-            entity_ds = ray.data.read_csv(entity_df)
+            entity_ds = ray_wrapper.read_csv(entity_df)
             entity_df_sample = entity_ds.limit(1000).to_pandas()
         else:
-            entity_ds = ray.data.from_pandas(entity_df)
+            entity_ds = ray_wrapper.from_pandas(entity_df)
             entity_df_sample = entity_df.copy()
 
         entity_ds = ensure_timestamp_compatibility(entity_ds, ["event_timestamp"])
@@ -1940,9 +1936,12 @@ def get_historical_features(
 
             entities = fv.entities or []
             entity_objs = [registry.get_entity(e, project) for e in entities]
-            original_join_keys, _, timestamp_field, created_col = _get_column_names(
-                fv, entity_objs
-            )
+            (
+                original_join_keys,
+                reverse_mapped_feature_names,
+                timestamp_field,
+                created_col,
+            ) = _get_column_names(fv, entity_objs)
 
             if fv.projection.join_key_map:
                 join_keys = [
@@ -1952,11 +1951,12 @@ def get_historical_features(
             else:
                 join_keys = original_join_keys
 
-            requested_feats = [ref.split(":", 1)[1] for ref in fv_feature_refs]
+            # Get the logical feature names from refs
+            logical_requested_feats = [ref.split(":", 1)[1] for ref in fv_feature_refs]
 
             available_feature_names = [f.name for f in fv.features]
             missing_feats = [
-                f for f in requested_feats if f not in available_feature_names
+                f for f in logical_requested_feats if f not in available_feature_names
             ]
             if missing_feats:
                 raise KeyError(
@@ -1964,16 +1964,37 @@ def get_historical_features(
                     f"(available: {available_feature_names})"
                 )
 
+            # Build reverse field mapping to get actual source column names
+            reverse_field_mapping = {}
+            if fv.batch_source.field_mapping:
+                reverse_field_mapping = {
+                    v: k for k, v in fv.batch_source.field_mapping.items()
+                }
+
+            # Map logical feature names to actual source column names
+            requested_feats = [
+                reverse_field_mapping.get(feat, feat)
+                for feat in logical_requested_feats
+            ]
+
             source_info = resolve_feature_view_source_with_fallback(
                 fv, config, is_materialization=False
             )
 
             # Read from the resolved data source
             source_path = store._get_source_path(source_info.data_source, config)
-            feature_ds = ray.data.read_parquet(source_path)
-            logger.info(
-                f"Reading feature view {fv.name}: {source_info.source_description}"
-            )
+
+            if not source_info.has_transformation:
+                required_feature_columns = set(
+                    original_join_keys + requested_feats + [timestamp_field]
+                )
+                if created_col:
+                    required_feature_columns.add(created_col)
+                feature_ds = ray_wrapper.read_parquet(
+                    source_path, columns=list(required_feature_columns)
+                )
+            else:
+                feature_ds = ray_wrapper.read_parquet(source_path)
 
             # Apply transformation if available
             if source_info.has_transformation and source_info.transformation_func:
@@ -2012,10 +2033,23 @@ def apply_transformation_with_serialized_func(
             field_mapping = getattr(fv.batch_source, "field_mapping", None)
             if field_mapping:
                 feature_ds = apply_field_mapping(feature_ds, field_mapping)
-                join_keys = [field_mapping.get(k, k) for k in join_keys]
+                # Update original_join_keys to logical names after forward mapping
+                original_join_keys = [
+                    field_mapping.get(k, k) for k in original_join_keys
+                ]
+                # Recompute join_keys from updated original_join_keys
+                if fv.projection.join_key_map:
+                    join_keys = [
+                        fv.projection.join_key_map.get(key, key)
+                        for key in original_join_keys
+                    ]
+                else:
+                    join_keys = original_join_keys
                 timestamp_field = field_mapping.get(timestamp_field, timestamp_field)
                 if created_col:
                     created_col = field_mapping.get(created_col, created_col)
+                # Also map requested_feats back to logical names after forward mapping
+                requested_feats = [field_mapping.get(f, f) for f in requested_feats]
 
             if (
                 timestamp_field != "event_timestamp"
diff --git a/sdk/python/feast/infra/offline_stores/contrib/trino_offline_store/trino.py b/sdk/python/feast/infra/offline_stores/contrib/trino_offline_store/trino.py
index fd126e87db6..aa4cb2c8a60 100644
--- a/sdk/python/feast/infra/offline_stores/contrib/trino_offline_store/trino.py
+++ b/sdk/python/feast/infra/offline_stores/contrib/trino_offline_store/trino.py
@@ -372,6 +372,8 @@ def get_historical_features(
         )
 
         # Generate the Trino SQL query from the query context
+        if type(entity_df) is str:
+            table_reference = f"({entity_df})"
         query = offline_utils.build_point_in_time_query(
             query_context,
             left_table_query_string=table_reference,
@@ -454,9 +456,7 @@ def _upload_entity_df_and_get_entity_schema(
 ) -> Dict[str, np.dtype]:
     """Uploads a Pandas entity dataframe into a Trino table and returns the resulting table"""
     if type(entity_df) is str:
-        client.execute_query(f"CREATE TABLE {table_name} AS ({entity_df})")
-
-        results = client.execute_query(f"SELECT * FROM {table_name} LIMIT 1")
+        results = client.execute_query(f"SELECT * FROM ({entity_df}) LIMIT 1")
 
         limited_entity_df = pd.DataFrame(
             data=results.data, columns=results.columns_names
diff --git a/sdk/python/feast/infra/offline_stores/remote.py b/sdk/python/feast/infra/offline_stores/remote.py
index a5f50c7b45c..abe75ca57e5 100644
--- a/sdk/python/feast/infra/offline_stores/remote.py
+++ b/sdk/python/feast/infra/offline_stores/remote.py
@@ -197,6 +197,7 @@ def get_historical_features(
         registry: BaseRegistry,
         project: str,
         full_feature_names: bool = False,
+        **kwargs,
     ) -> RemoteRetrievalJob:
         assert isinstance(config.offline_store, RemoteOfflineStoreConfig)
 
@@ -219,6 +220,15 @@ def get_historical_features(
             "name_aliases": name_aliases,
         }
 
+        # Extract and serialize start_date/end_date for remote transmission
+        start_date = kwargs.get("start_date", None)
+        end_date = kwargs.get("end_date", None)
+
+        if start_date is not None:
+            api_parameters["start_date"] = start_date.isoformat()
+        if end_date is not None:
+            api_parameters["end_date"] = end_date.isoformat()
+
         return RemoteRetrievalJob(
             client=client,
             api=OfflineStore.get_historical_features.__name__,
diff --git a/sdk/python/feast/infra/online_stores/dynamodb.py b/sdk/python/feast/infra/online_stores/dynamodb.py
index e60796b2963..c577159884d 100644
--- a/sdk/python/feast/infra/online_stores/dynamodb.py
+++ b/sdk/python/feast/infra/online_stores/dynamodb.py
@@ -108,15 +108,24 @@ class DynamoDBOnlineStore(OnlineStore):
     Attributes:
         _dynamodb_client: Boto3 DynamoDB client.
         _dynamodb_resource: Boto3 DynamoDB resource.
+        _aioboto_session: Async boto session.
+        _aioboto_client: Async boto client.
+        _aioboto_context_stack: Async context stack.
     """
 
     _dynamodb_client = None
     _dynamodb_resource = None
 
+    def __init__(self):
+        super().__init__()
+        self._aioboto_session = None
+        self._aioboto_client = None
+        self._aioboto_context_stack = None
+
     async def initialize(self, config: RepoConfig):
         online_config = config.online_store
 
-        await _get_aiodynamodb_client(
+        await self._get_aiodynamodb_client(
             online_config.region,
             online_config.max_pool_connections,
             online_config.keepalive_timeout,
@@ -127,7 +136,59 @@ async def initialize(self, config: RepoConfig):
         )
 
     async def close(self):
-        await _aiodynamodb_close()
+        await self._aiodynamodb_close()
+
+    def _get_aioboto_session(self):
+        if self._aioboto_session is None:
+            logger.debug("initializing the aiobotocore session")
+            self._aioboto_session = session.get_session()
+        return self._aioboto_session
+
+    async def _get_aiodynamodb_client(
+        self,
+        region: str,
+        max_pool_connections: int,
+        keepalive_timeout: float,
+        connect_timeout: Union[int, float],
+        read_timeout: Union[int, float],
+        total_max_retry_attempts: Union[int, None],
+        retry_mode: Union[Literal["legacy", "standard", "adaptive"], None],
+    ):
+        if self._aioboto_client is None:
+            logger.debug("initializing the aiobotocore dynamodb client")
+
+            retries: Dict[str, Any] = {}
+            if total_max_retry_attempts is not None:
+                retries["total_max_attempts"] = total_max_retry_attempts
+            if retry_mode is not None:
+                retries["mode"] = retry_mode
+
+            client_context = self._get_aioboto_session().create_client(
+                "dynamodb",
+                region_name=region,
+                config=AioConfig(
+                    max_pool_connections=max_pool_connections,
+                    connect_timeout=connect_timeout,
+                    read_timeout=read_timeout,
+                    retries=retries if retries else None,
+                    connector_args={"keepalive_timeout": keepalive_timeout},
+                ),
+            )
+            self._aioboto_context_stack = contextlib.AsyncExitStack()
+            self._aioboto_client = (
+                await self._aioboto_context_stack.enter_async_context(client_context)
+            )
+        return self._aioboto_client
+
+    async def _aiodynamodb_close(self):
+        if self._aioboto_client:
+            await self._aioboto_client.close()
+            self._aioboto_client = None
+        if self._aioboto_context_stack:
+            await self._aioboto_context_stack.aclose()
+            self._aioboto_context_stack = None
+        if self._aioboto_session:
+            self._aioboto_session = None
 
     @property
     def async_supported(self) -> SupportedAsyncMethods:
@@ -249,7 +310,18 @@ def update(
             # tags won't be updated in the create_table call if the table already exists
             if do_tag_updates[table_name]:
                 tags = self._table_tags(online_config, table_instance)
-                self._update_tags(dynamodb_client, table_name, tags)
+                try:
+                    self._update_tags(dynamodb_client, table_name, tags)
+                except ClientError as ce:
+                    # If tag update fails with AccessDeniedException, log warning and continue
+                    # This allows Feast to work in environments where IAM roles don't have
+                    # dynamodb:TagResource and dynamodb:UntagResource permissions
+                    if ce.response["Error"]["Code"] == "AccessDeniedException":
+                        logger.warning(
+                            f"Unable to update tags for table {table_name} due to insufficient permissions."
+                        )
+                    else:
+                        raise
 
         for table_to_delete in tables_to_delete:
             _delete_table_idempotent(
@@ -351,7 +423,7 @@ async def online_write_batch_async(
             _to_client_write_item(config, entity_key, features, timestamp)
             for entity_key, features, timestamp, _ in _latest_data_to_write(data)
         ]
-        client = await _get_aiodynamodb_client(
+        client = await self._get_aiodynamodb_client(
             online_config.region,
             online_config.max_pool_connections,
             online_config.keepalive_timeout,
@@ -462,7 +534,7 @@ def to_tbl_resp(raw_client_response):
             batches.append(batch)
             entity_id_batches.append(entity_id_batch)
 
-        client = await _get_aiodynamodb_client(
+        client = await self._get_aiodynamodb_client(
             online_config.region,
             online_config.max_pool_connections,
             online_config.keepalive_timeout,
@@ -616,66 +688,7 @@ def _to_client_batch_get_payload(online_config, table_name, batch):
         }
 
 
-_aioboto_session = None
-_aioboto_client = None
-_aioboto_context_stack = None
-
-
-def _get_aioboto_session():
-    global _aioboto_session
-    if _aioboto_session is None:
-        logger.debug("initializing the aiobotocore session")
-        _aioboto_session = session.get_session()
-    return _aioboto_session
-
-
-async def _get_aiodynamodb_client(
-    region: str,
-    max_pool_connections: int,
-    keepalive_timeout: float,
-    connect_timeout: Union[int, float],
-    read_timeout: Union[int, float],
-    total_max_retry_attempts: Union[int, None],
-    retry_mode: Union[Literal["legacy", "standard", "adaptive"], None],
-):
-    global _aioboto_client, _aioboto_context_stack
-    if _aioboto_client is None:
-        logger.debug("initializing the aiobotocore dynamodb client")
-
-        retries: Dict[str, Any] = {}
-        if total_max_retry_attempts is not None:
-            retries["total_max_attempts"] = total_max_retry_attempts
-        if retry_mode is not None:
-            retries["mode"] = retry_mode
-
-        client_context = _get_aioboto_session().create_client(
-            "dynamodb",
-            region_name=region,
-            config=AioConfig(
-                max_pool_connections=max_pool_connections,
-                connect_timeout=connect_timeout,
-                read_timeout=read_timeout,
-                retries=retries if retries else None,
-                connector_args={"keepalive_timeout": keepalive_timeout},
-            ),
-        )
-        _aioboto_context_stack = contextlib.AsyncExitStack()
-        _aioboto_client = await _aioboto_context_stack.enter_async_context(
-            client_context
-        )
-    return _aioboto_client
-
-
-async def _aiodynamodb_close():
-    global _aioboto_client, _aioboto_session, _aioboto_context_stack
-    if _aioboto_client:
-        await _aioboto_client.close()
-        _aioboto_client = None
-    if _aioboto_context_stack:
-        await _aioboto_context_stack.aclose()
-        _aioboto_context_stack = None
-    if _aioboto_session:
-        _aioboto_session = None
+# Global async client functions removed - now using instance methods
 
 
 def _initialize_dynamodb_client(
diff --git a/sdk/python/feast/infra/ray_initializer.py b/sdk/python/feast/infra/ray_initializer.py
new file mode 100644
index 00000000000..eea21eaa321
--- /dev/null
+++ b/sdk/python/feast/infra/ray_initializer.py
@@ -0,0 +1,660 @@
+# Copyright 2025 The Feast Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+Centralized Ray Initialization Module for Feast.
+
+This module combines configuration management and initialization logic for a
+complete, self-contained Ray setup system.
+"""
+
+import logging
+import os
+from enum import Enum
+from typing import Any, Dict, List, Optional, Union
+
+import ray
+from ray.data.context import DatasetContext
+
+logger = logging.getLogger(__name__)
+
+
+class RayExecutionMode(Enum):
+    """Ray execution modes supported by Feast."""
+
+    LOCAL = "local"
+    REMOTE = "remote"
+    KUBERAY = "kuberay"
+
+
+class RayConfigManager:
+    """
+    Manages Ray configuration and execution mode determination.
+
+    Supports three main scenarios:
+    1. Local Ray: Single-machine development and testing
+    2. Remote Ray: Connect to existing Ray standalone cluster
+    3. KubeRay: Ray on Kubernetes with CodeFlare SDK
+
+    The manager determines execution mode based on configuration precedence:
+    1. Environment variable FEAST_RAY_EXECUTION_MODE (highest)
+    2. KubeRay mode (use_kuberay=True or cluster_name specified)
+    3. Remote mode (ray_address specified)
+    4. Local mode (default fallback)
+    """
+
+    def __init__(self, config: Optional[Union[Dict[str, Any], object]] = None):
+        """
+        Initialize Ray configuration manager.
+
+        Args:
+            config: Ray configuration (RayOfflineStoreConfig, RayComputeEngineConfig, or dict)
+        """
+        self.config = config or {}
+        self._execution_mode: Optional[RayExecutionMode] = None
+        self._codeflare_config: Optional[Dict[str, Any]] = None
+
+    def determine_execution_mode(self) -> RayExecutionMode:
+        """
+        Determine the appropriate Ray execution mode based on configuration.
+
+        Precedence (highest to lowest):
+        1. Environment variable FEAST_RAY_EXECUTION_MODE (explicit override)
+        2. KubeRay mode (use_kuberay=True or cluster_name specified)
+        3. Remote mode (ray_address specified)
+        4. Local mode (default fallback)
+
+        Returns:
+            RayExecutionMode enum value
+        """
+        if self._execution_mode is not None:
+            return self._execution_mode
+
+        # 1. Check environment variable override first (highest precedence)
+        env_mode = os.getenv("FEAST_RAY_EXECUTION_MODE", "").lower()
+        if env_mode in ["local", "remote", "kuberay"]:
+            self._execution_mode = RayExecutionMode(env_mode)
+            logger.info(
+                f"Ray execution mode set via FEAST_RAY_EXECUTION_MODE: {env_mode}"
+            )
+            return self._execution_mode
+
+        # 2. Check for KubeRay configuration (second highest precedence)
+        use_kuberay = self._get_config_value("use_kuberay")
+
+        # Check for cluster_name in kuberay_conf
+        kuberay_conf = self._get_config_value("kuberay_conf", {}) or {}
+        cluster_name = kuberay_conf.get("cluster_name")
+
+        # Environment variables can enable KubeRay
+        if os.getenv("FEAST_USE_KUBERAY", "").lower() == "true":
+            use_kuberay = True
+        if os.getenv("FEAST_RAY_CLUSTER_NAME"):
+            cluster_name = os.getenv("FEAST_RAY_CLUSTER_NAME")
+
+        # KubeRay takes precedence over remote/local if configured
+        if use_kuberay or cluster_name:
+            self._execution_mode = RayExecutionMode.KUBERAY
+            reason = []
+            if use_kuberay:
+                reason.append("use_kuberay=True")
+            if cluster_name:
+                reason.append(f"cluster_name='{cluster_name}'")
+            logger.info(f"Ray execution mode: KubeRay ({', '.join(reason)})")
+            return self._execution_mode
+
+        # 3. Check for remote Ray configuration (third precedence)
+        ray_address = self._get_config_value("ray_address") or os.getenv("RAY_ADDRESS")
+
+        if ray_address:
+            self._execution_mode = RayExecutionMode.REMOTE
+            logger.info(f"Ray execution mode: Remote (ray_address='{ray_address}')")
+            return self._execution_mode
+
+        # 4. Default to local Ray (lowest precedence - fallback)
+        self._execution_mode = RayExecutionMode.LOCAL
+        logger.info(
+            "Ray execution mode: Local (default - no KubeRay or remote configuration found)"
+        )
+        return self._execution_mode
+
+    def get_kuberay_config(self) -> Dict[str, Any]:
+        """
+        Get KubeRay/CodeFlare SDK configuration.
+
+        Returns:
+            Dictionary of KubeRay configuration with passthrough settings
+        """
+        if self._codeflare_config is not None:
+            return self._codeflare_config
+
+        # Get passthrough configuration from kuberay_conf first
+        kuberay_conf = self._get_config_value("kuberay_conf", {}) or {}
+
+        config = {
+            "use_kuberay": (
+                os.getenv("FEAST_USE_KUBERAY", "").lower() == "true"
+                or self._get_config_value("use_kuberay", False)
+            ),
+            # Get values from kuberay_conf or environment variables
+            "cluster_name": (
+                os.getenv("FEAST_RAY_CLUSTER_NAME") or kuberay_conf.get("cluster_name")
+            ),
+            "namespace": (
+                os.getenv("FEAST_RAY_NAMESPACE")
+                or kuberay_conf.get("namespace", "default")
+            ),
+        }
+
+        # Add authentication configuration from kuberay_conf or environment variables
+        auth_token = (
+            os.getenv("FEAST_RAY_AUTH_TOKEN")
+            or os.getenv("RAY_AUTH_TOKEN")
+            or kuberay_conf.get("auth_token")
+        )
+        if auth_token:
+            config["auth_token"] = auth_token
+
+        # Add authentication server URL
+        auth_server = (
+            os.getenv("FEAST_RAY_AUTH_SERVER")
+            or os.getenv("RAY_AUTH_SERVER")
+            or kuberay_conf.get("auth_server")
+        )
+        if auth_server:
+            config["auth_server"] = auth_server
+
+        # Add skip TLS verification setting
+        skip_tls = os.getenv(
+            "FEAST_RAY_SKIP_TLS", ""
+        ).lower() == "true" or kuberay_conf.get("skip_tls", False)
+        config["skip_tls"] = skip_tls
+
+        # Add any additional configuration from kuberay_conf
+        for key, value in kuberay_conf.items():
+            if key not in config:  # Don't override already processed keys
+                config[key] = value
+
+        self._codeflare_config = config
+        return config
+
+    def _get_config_value(self, key: str, default: Any = None) -> Any:
+        """
+        Get configuration value from config object or dictionary.
+
+        Args:
+            key: Configuration key
+            default: Default value if key not found
+
+        Returns:
+            Configuration value
+        """
+        if hasattr(self.config, key):
+            return getattr(self.config, key)
+        elif isinstance(self.config, dict):
+            return self.config.get(key, default)
+        else:
+            return default
+
+
+class StandardRayWrapper:
+    """Wrapper for Ray Native operations."""
+
+    def read_parquet(self, path: Union[str, List[str]], **kwargs) -> Any:
+        """Read parquet files using standard Ray."""
+        return ray.data.read_parquet(path, **kwargs)
+
+    def read_csv(self, path: Union[str, List[str]], **kwargs) -> Any:
+        """Read CSV files using standard Ray."""
+        return ray.data.read_csv(path, **kwargs)
+
+    def from_pandas(self, df: Any) -> Any:
+        """Create dataset from pandas DataFrame using standard Ray."""
+        return ray.data.from_pandas(df)
+
+    def from_arrow(self, table: Any) -> Any:
+        """Create dataset from Arrow table using standard Ray."""
+        return ray.data.from_arrow(table)
+
+
+class CodeFlareRayWrapper:
+    """Wrapper for Ray operations on KubeRay clusters using CodeFlare SDK."""
+
+    def __init__(
+        self,
+        cluster_name: str,
+        namespace: str,
+        auth_token: str,
+        auth_server: str,
+        skip_tls: bool = False,
+        enable_logging: bool = False,
+    ):
+        """Initialize CodeFlare Ray wrapper with cluster connection parameters."""
+        self.cluster_name = cluster_name
+        self.namespace = namespace
+        self.auth_token = auth_token
+        self.auth_server = auth_server
+        self.skip_tls = skip_tls
+        self.enable_logging = enable_logging
+        self.cluster = None
+
+        # Authenticate and setup Ray connection
+        self._authenticate_codeflare()
+        self._setup_ray_connection()
+
+    def _authenticate_codeflare(self):
+        """Authenticate with CodeFlare SDK."""
+        try:
+            from codeflare_sdk import TokenAuthentication
+
+            auth = TokenAuthentication(
+                token=self.auth_token,
+                server=self.auth_server,
+                skip_tls=self.skip_tls,
+            )
+            auth.login()
+        except Exception as e:
+            logger.error(f"CodeFlare authentication failed: {e}")
+            raise
+
+    def _setup_ray_connection(self):
+        """Setup Ray connection to KubeRay cluster using TLS certificates."""
+        try:
+            from codeflare_sdk import generate_cert, get_cluster
+
+            self.cluster = get_cluster(
+                cluster_name=self.cluster_name, namespace=self.namespace
+            )
+            if self.cluster is None:
+                raise RuntimeError(
+                    f"Failed to find KubeRay cluster '{self.cluster_name}' in namespace '{self.namespace}'"
+                )
+            generate_cert.generate_tls_cert(self.cluster_name, self.namespace)
+            generate_cert.export_env(self.cluster_name, self.namespace)
+
+            cluster_uri = self.cluster.cluster_uri()
+            runtime_env = {
+                "pip": ["feast"],
+                "env_vars": {"RAY_DISABLE_IMPORT_WARNING": "1"},
+            }
+
+            ray.shutdown()
+
+            logging_level = "INFO" if self.enable_logging else "ERROR"
+
+            ray.init(
+                address=cluster_uri,
+                ignore_reinit_error=True,
+                logging_level=logging_level,
+                log_to_driver=self.enable_logging,
+                runtime_env=runtime_env,
+            )
+
+            logger.info(f"Ray connected successfully to cluster: {self.cluster_name}")
+
+        except Exception as e:
+            logger.error(f"Ray connection failed: {e}")
+            raise
+
+    # Ray Data API methods - wrapped in @ray.remote to execute on cluster workers
+    def read_parquet(self, path: Union[str, List[str]], **kwargs) -> Any:
+        """Read parquet files - runs remotely on KubeRay cluster workers."""
+        from feast.infra.ray_shared_utils import RemoteDatasetProxy
+
+        @ray.remote
+        def _remote_read_parquet(file_path, read_kwargs):
+            import ray
+
+            return ray.data.read_parquet(file_path, **read_kwargs)
+
+        return RemoteDatasetProxy(_remote_read_parquet.remote(path, kwargs))
+
+    def read_csv(self, path: Union[str, List[str]], **kwargs) -> Any:
+        """Read CSV files - runs remotely on KubeRay cluster workers."""
+        from feast.infra.ray_shared_utils import RemoteDatasetProxy
+
+        @ray.remote
+        def _remote_read_csv(file_path, read_kwargs):
+            import ray
+
+            return ray.data.read_csv(file_path, **read_kwargs)
+
+        return RemoteDatasetProxy(_remote_read_csv.remote(path, kwargs))
+
+    def from_pandas(self, df: Any) -> Any:
+        """Create dataset from pandas DataFrame - runs remotely on KubeRay cluster workers."""
+        from feast.infra.ray_shared_utils import RemoteDatasetProxy
+
+        @ray.remote
+        def _remote_from_pandas(dataframe):
+            import ray
+
+            return ray.data.from_pandas(dataframe)
+
+        return RemoteDatasetProxy(_remote_from_pandas.remote(df))
+
+    def from_arrow(self, table: Any) -> Any:
+        """Create dataset from Arrow table - runs remotely on KubeRay cluster workers."""
+        from feast.infra.ray_shared_utils import RemoteDatasetProxy
+
+        @ray.remote
+        def _remote_from_arrow(arrow_table):
+            import ray
+
+            return ray.data.from_arrow(arrow_table)
+
+        return RemoteDatasetProxy(_remote_from_arrow.remote(table))
+
+
+# Global state tracking
+_ray_initialized = False
+_ray_wrapper: Optional[Union[StandardRayWrapper, CodeFlareRayWrapper]] = None
+
+
+def _suppress_ray_logging() -> None:
+    """Suppress Ray and Ray Data logging completely."""
+    import warnings
+
+    # Suppress Ray warnings
+    warnings.filterwarnings("ignore", category=DeprecationWarning, module="ray")
+    warnings.filterwarnings("ignore", category=UserWarning, module="ray")
+
+    # Set environment variables to suppress Ray output
+    os.environ["RAY_DISABLE_IMPORT_WARNING"] = "1"
+    os.environ["RAY_SUPPRESS_UNVERIFIED_TLS_WARNING"] = "1"
+    os.environ["RAY_LOG_LEVEL"] = "ERROR"
+    os.environ["RAY_DATA_LOG_LEVEL"] = "ERROR"
+    os.environ["RAY_DISABLE_PROGRESS_BARS"] = "1"
+
+    # Suppress all Ray-related loggers
+    ray_loggers = [
+        "ray",
+        "ray.data",
+        "ray.data.dataset",
+        "ray.data.context",
+        "ray.data._internal.streaming_executor",
+        "ray.data._internal.execution",
+        "ray.data._internal",
+        "ray.tune",
+        "ray.serve",
+        "ray.util",
+        "ray._private",
+    ]
+    for logger_name in ray_loggers:
+        logging.getLogger(logger_name).setLevel(logging.ERROR)
+
+    # Configure DatasetContext to disable progress bars
+    try:
+        ctx = DatasetContext.get_current()
+        ctx.enable_progress_bars = False
+        if hasattr(ctx, "verbose_progress"):
+            ctx.verbose_progress = False
+    except Exception:
+        pass  # Ignore if Ray Data is not available
+
+
+def _initialize_local_ray(config: Any, enable_logging: bool = False) -> None:
+    """
+    Initialize Ray in local mode.
+
+    Args:
+        config: Configuration object (RayOfflineStoreConfig or RayComputeEngineConfig)
+        enable_logging: Whether to enable Ray logging
+    """
+    logger.info("Initializing Ray in LOCAL mode")
+
+    ray_init_kwargs: Dict[str, Any] = {
+        "ignore_reinit_error": True,
+        "include_dashboard": False,
+    }
+
+    if enable_logging:
+        ray_init_kwargs.update(
+            {
+                "log_to_driver": True,
+                "logging_level": "INFO",
+            }
+        )
+    else:
+        ray_init_kwargs.update(
+            {
+                "log_to_driver": False,
+                "logging_level": "ERROR",
+            }
+        )
+        _suppress_ray_logging()
+
+    # Add local configuration
+    ray_init_kwargs.update(
+        {
+            "_node_ip_address": os.getenv("RAY_NODE_IP", "127.0.0.1"),
+            "num_cpus": os.cpu_count() or 4,
+        }
+    )
+
+    # Merge with user-provided ray_conf if available
+    if hasattr(config, "ray_conf") and config.ray_conf:
+        ray_init_kwargs.update(config.ray_conf)
+
+    # Initialize Ray
+    ray.init(**ray_init_kwargs)
+
+    # Configure DatasetContext
+    ctx = DatasetContext.get_current()
+    ctx.shuffle_strategy = "sort"  # type: ignore
+    ctx.enable_tensor_extension_casting = False
+
+    # Log cluster info
+    if enable_logging:
+        cluster_resources = ray.cluster_resources()
+        logger.info(
+            f"Ray local cluster initialized with {cluster_resources.get('CPU', 0)} CPUs, "
+            f"{cluster_resources.get('memory', 0) / (1024**3):.1f}GB memory"
+        )
+
+
+def _initialize_remote_ray(config: Any, enable_logging: bool = False) -> None:
+    """
+    Initialize Ray in remote mode (connect to existing Ray cluster).
+
+    Args:
+        config: Configuration object with ray_address
+        enable_logging: Whether to enable Ray logging
+    """
+    ray_address = getattr(config, "ray_address", None)
+    if not ray_address:
+        ray_address = os.getenv("RAY_ADDRESS")
+
+    if not ray_address:
+        raise ValueError("ray_address must be specified for remote Ray mode")
+
+    logger.info(f"Initializing Ray in REMOTE mode, connecting to: {ray_address}")
+
+    ray_init_kwargs: Dict[str, Any] = {
+        "address": ray_address,
+        "ignore_reinit_error": True,
+        "include_dashboard": False,
+    }
+
+    if enable_logging:
+        ray_init_kwargs.update(
+            {
+                "log_to_driver": True,
+                "logging_level": "INFO",
+            }
+        )
+    else:
+        ray_init_kwargs.update(
+            {
+                "log_to_driver": False,
+                "logging_level": "ERROR",
+            }
+        )
+        _suppress_ray_logging()
+
+    # Merge with user-provided ray_conf if available
+    if hasattr(config, "ray_conf") and config.ray_conf:
+        ray_init_kwargs.update(config.ray_conf)
+
+    # Initialize Ray
+    ray.init(**ray_init_kwargs)
+
+    # Configure DatasetContext
+    ctx = DatasetContext.get_current()
+    ctx.shuffle_strategy = "sort"  # type: ignore
+    ctx.enable_tensor_extension_casting = False
+
+    # Log cluster info
+    if enable_logging:
+        cluster_resources = ray.cluster_resources()
+        logger.info(
+            f"Ray remote cluster initialized with {cluster_resources.get('CPU', 0)} CPUs, "
+            f"{cluster_resources.get('memory', 0) / (1024**3):.1f}GB memory"
+        )
+
+
+def _initialize_kuberay(config: Any, enable_logging: bool = False) -> None:
+    """
+    Initialize Ray in KubeRay mode using CodeFlare SDK.
+
+    Args:
+        config: Configuration object with KubeRay settings
+        enable_logging: Whether to enable Ray logging
+    """
+    global _ray_wrapper
+
+    logger.info("Initializing Ray in KUBERAY mode using CodeFlare SDK")
+
+    if not enable_logging:
+        _suppress_ray_logging()
+
+    # Get KubeRay configuration
+    config_manager = RayConfigManager(config)
+    kuberay_config = config_manager.get_kuberay_config()
+
+    # Initialize CodeFlare Ray wrapper - this connects to the cluster
+    _ray_wrapper = CodeFlareRayWrapper(
+        cluster_name=kuberay_config["cluster_name"],
+        namespace=kuberay_config["namespace"],
+        auth_token=kuberay_config["auth_token"],
+        auth_server=kuberay_config["auth_server"],
+        skip_tls=kuberay_config.get("skip_tls", False),
+        enable_logging=enable_logging,
+    )
+
+    logger.info("KubeRay cluster connection established via CodeFlare SDK")
+
+
+def ensure_ray_initialized(
+    config: Optional[Any] = None, force_reinit: bool = False
+) -> None:
+    """
+    Ensure Ray is initialized with appropriate configuration.
+
+    This is the main entry point for Ray initialization across all Feast components.
+    It automatically detects the execution mode and initializes Ray accordingly.
+
+    Args:
+        config: Configuration object (RayOfflineStoreConfig, RayComputeEngineConfig, or RepoConfig)
+        force_reinit: If True, reinitialize Ray even if already initialized
+
+    Raises:
+        ValueError: If configuration is invalid or required parameters are missing
+    """
+    global _ray_initialized
+
+    # Check if already initialized
+    if _ray_initialized and not force_reinit:
+        logger.debug("Ray already initialized, skipping initialization")
+        return
+
+    # Extract Ray-specific config if RepoConfig is provided
+    ray_config = config
+    if config and hasattr(config, "offline_store"):
+        ray_config = config.offline_store
+    elif config and hasattr(config, "batch_engine"):
+        ray_config = config.batch_engine
+
+    # Determine enable_logging setting
+    enable_logging = (
+        getattr(ray_config, "enable_ray_logging", False) if ray_config else False
+    )
+
+    # Use RayConfigManager to determine execution mode
+    config_manager = RayConfigManager(ray_config)
+    execution_mode = config_manager.determine_execution_mode()
+
+    logger.info(f"Ray execution mode detected: {execution_mode.value}")
+
+    # Check if Ray is already initialized (from external source)
+    if ray.is_initialized() and not force_reinit:
+        logger.info("Ray is already initialized externally, using existing cluster")
+        # Configure DatasetContext even if Ray is already initialized
+        ctx = DatasetContext.get_current()
+        ctx.shuffle_strategy = "sort"  # type: ignore
+        ctx.enable_tensor_extension_casting = False
+        if not enable_logging:
+            _suppress_ray_logging()
+        _ray_initialized = True
+        return
+
+    # Initialize based on execution mode
+    try:
+        if execution_mode == RayExecutionMode.KUBERAY:
+            _initialize_kuberay(ray_config, enable_logging)
+        elif execution_mode == RayExecutionMode.REMOTE:
+            _initialize_remote_ray(ray_config, enable_logging)
+        else:  # LOCAL
+            _initialize_local_ray(ray_config, enable_logging)
+
+        _ray_initialized = True
+        logger.info(f"Ray initialized successfully in {execution_mode.value} mode")
+
+    except Exception as e:
+        logger.error(f"Failed to initialize Ray in {execution_mode.value} mode: {e}")
+        raise
+
+
+def get_ray_wrapper() -> Union[StandardRayWrapper, CodeFlareRayWrapper]:
+    """
+    Get the appropriate Ray wrapper based on current initialization mode.
+
+    Returns:
+        StandardRayWrapper for local/remote modes, CodeFlareRayWrapper for KubeRay mode
+    """
+    global _ray_wrapper
+
+    if _ray_wrapper is None:
+        # Return a standard Ray wrapper for local/remote modes
+        _ray_wrapper = StandardRayWrapper()
+
+    return _ray_wrapper
+
+
+def is_ray_initialized() -> bool:
+    """Check if Ray has been initialized via this module."""
+    return _ray_initialized
+
+
+def shutdown_ray() -> None:
+    """Shutdown Ray and reset initialization state."""
+    global _ray_initialized, _ray_wrapper
+
+    if ray.is_initialized():
+        logger.info("Shutting down Ray")
+        ray.shutdown()
+
+    _ray_initialized = False
+    _ray_wrapper = None
+    logger.info("Ray shutdown complete")
diff --git a/sdk/python/feast/infra/ray_shared_utils.py b/sdk/python/feast/infra/ray_shared_utils.py
index 9e9254fbfae..9614623294f 100644
--- a/sdk/python/feast/infra/ray_shared_utils.py
+++ b/sdk/python/feast/infra/ray_shared_utils.py
@@ -49,7 +49,12 @@ def to_arrow(self) -> pa.Table:
 
         @ray.remote
         def _remote_to_arrow(dataset):
-            return dataset.to_arrow()
+            arrow_refs = dataset.to_arrow_refs()
+            if arrow_refs:
+                tables = ray.get(arrow_refs)
+                return pa.concat_tables(tables)
+            else:
+                return pa.Table.from_pydict({})
 
         result_ref = _remote_to_arrow.remote(self._dataset_ref)
         return ray.get(result_ref)
@@ -124,6 +129,16 @@ def _remote_take(dataset, num):
         result_ref = _remote_take.remote(self._dataset_ref, n)
         return ray.get(result_ref)
 
+    def size_bytes(self) -> int:
+        """Execute size_bytes remotely and return result."""
+
+        @ray.remote
+        def _remote_size_bytes(dataset):
+            return dataset.size_bytes()
+
+        result_ref = _remote_size_bytes.remote(self._dataset_ref)
+        return ray.get(result_ref)
+
     def __getattr__(self, name):
         """Catch any method calls that we haven't explicitly implemented."""
         raise AttributeError(f"RemoteDatasetProxy has no attribute '{name}'")
diff --git a/sdk/python/feast/infra/registry/contrib/hdfs/__init__.py b/sdk/python/feast/infra/registry/contrib/hdfs/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/sdk/python/feast/infra/registry/contrib/hdfs/hdfs_registry_store.py b/sdk/python/feast/infra/registry/contrib/hdfs/hdfs_registry_store.py
new file mode 100644
index 00000000000..f4c4193d569
--- /dev/null
+++ b/sdk/python/feast/infra/registry/contrib/hdfs/hdfs_registry_store.py
@@ -0,0 +1,121 @@
+import json
+import uuid
+from pathlib import Path, PurePosixPath
+from typing import Optional
+from urllib.parse import urlparse
+
+from pyarrow import fs
+
+from feast.infra.registry.registry_store import RegistryStore
+from feast.protos.feast.core.Registry_pb2 import Registry as RegistryProto
+from feast.repo_config import RegistryConfig
+from feast.utils import _utc_now
+
+
+class HDFSRegistryStore(RegistryStore):
+    """HDFS implementation of RegistryStore.
+    registryConfig.path should be a hdfs path like hdfs://namenode:8020/path/to/registry.db
+    """
+
+    def __init__(self, registry_config: RegistryConfig, repo_path: Path):
+        try:
+            from pyarrow.fs import HadoopFileSystem
+        except ImportError as e:
+            from feast.errors import FeastExtrasDependencyImportError
+
+            raise FeastExtrasDependencyImportError(
+                "pyarrow.fs.HadoopFileSystem", str(e)
+            )
+        uri = registry_config.path
+        self._uri = urlparse(uri)
+        if self._uri.scheme != "hdfs":
+            raise ValueError(
+                f"Unsupported scheme {self._uri.scheme} in HDFS path {uri}"
+            )
+        self._hdfs = HadoopFileSystem(self._uri.hostname, self._uri.port or 8020)
+        self._path = PurePosixPath(self._uri.path)
+
+    def get_registry_proto(self):
+        registry_proto = RegistryProto()
+        if _check_hdfs_path_exists(self._hdfs, str(self._path)):
+            with self._hdfs.open_input_file(str(self._path)) as f:
+                registry_proto.ParseFromString(f.read())
+            return registry_proto
+        raise FileNotFoundError(
+            f'Registry not found at path "{self._uri.geturl()}". Have you run "feast apply"?'
+        )
+
+    def update_registry_proto(self, registry_proto: RegistryProto):
+        self._write_registry(registry_proto)
+
+    def teardown(self):
+        if _check_hdfs_path_exists(self._hdfs, str(self._path)):
+            self._hdfs.delete_file(str(self._path))
+        else:
+            # Nothing to do
+            pass
+
+    def _write_registry(self, registry_proto: RegistryProto):
+        """Write registry protobuf to HDFS."""
+        registry_proto.version_id = str(uuid.uuid4())
+        registry_proto.last_updated.FromDatetime(_utc_now())
+
+        dir_path = self._path.parent
+        if not _check_hdfs_path_exists(self._hdfs, str(dir_path)):
+            self._hdfs.create_dir(str(dir_path), recursive=True)
+
+        with self._hdfs.open_output_stream(str(self._path)) as f:
+            f.write(registry_proto.SerializeToString())
+
+    def set_project_metadata(self, project: str, key: str, value: str):
+        """Set a custom project metadata key-value pair in the registry (HDFS backend)."""
+        registry_proto = self.get_registry_proto()
+        found = False
+
+        for pm in registry_proto.project_metadata:
+            if pm.project == project:
+                # Load JSON metadata from project_uuid
+                try:
+                    meta = json.loads(pm.project_uuid) if pm.project_uuid else {}
+                except Exception:
+                    meta = {}
+
+                if not isinstance(meta, dict):
+                    meta = {}
+
+                meta[key] = value
+                pm.project_uuid = json.dumps(meta)
+                found = True
+                break
+
+        if not found:
+            # Create new ProjectMetadata entry
+            from feast.project_metadata import ProjectMetadata
+
+            pm = ProjectMetadata(project_name=project)
+            pm.project_uuid = json.dumps({key: value})
+            registry_proto.project_metadata.append(pm.to_proto())
+
+        # Write back
+        self.update_registry_proto(registry_proto)
+
+    def get_project_metadata(self, project: str, key: str) -> Optional[str]:
+        """Get custom project metadata key from registry (HDFS backend)."""
+        registry_proto = self.get_registry_proto()
+
+        for pm in registry_proto.project_metadata:
+            if pm.project == project:
+                try:
+                    meta = json.loads(pm.project_uuid) if pm.project_uuid else {}
+                except Exception:
+                    meta = {}
+
+                if not isinstance(meta, dict):
+                    return None
+                return meta.get(key, None)
+        return None
+
+
+def _check_hdfs_path_exists(hdfs, path: str) -> bool:
+    info = hdfs.get_file_info([path])[0]
+    return info.type != fs.FileType.NotFound
diff --git a/sdk/python/feast/infra/registry/registry.py b/sdk/python/feast/infra/registry/registry.py
index 38f79f84e7a..9a021744dd1 100644
--- a/sdk/python/feast/infra/registry/registry.py
+++ b/sdk/python/feast/infra/registry/registry.py
@@ -62,12 +62,14 @@
     "S3RegistryStore": "feast.infra.registry.s3.S3RegistryStore",
     "FileRegistryStore": "feast.infra.registry.file.FileRegistryStore",
     "AzureRegistryStore": "feast.infra.registry.contrib.azure.azure_registry_store.AzBlobRegistryStore",
+    "HDFSRegistryStore": "feast.infra.registry.contrib.hdfs.hdfs_registry_store.HDFSRegistryStore",
 }
 
 REGISTRY_STORE_CLASS_FOR_SCHEME = {
     "gs": "GCSRegistryStore",
     "s3": "S3RegistryStore",
     "file": "FileRegistryStore",
+    "hdfs": "HDFSRegistryStore",
     "": "FileRegistryStore",
 }
 
@@ -143,7 +145,7 @@ def get_registry_store_class_from_scheme(registry_path: str):
     if uri.scheme not in REGISTRY_STORE_CLASS_FOR_SCHEME:
         raise Exception(
             f"Registry path {registry_path} has unsupported scheme {uri.scheme}. "
-            f"Supported schemes are file, s3 and gs."
+            f"Supported schemes are file, s3, gs and hdfs."
         )
     else:
         registry_store_type = REGISTRY_STORE_CLASS_FOR_SCHEME[uri.scheme]
diff --git a/sdk/python/feast/infra/registry/sql.py b/sdk/python/feast/infra/registry/sql.py
index fd4119a966f..103b1f6c0a6 100644
--- a/sdk/python/feast/infra/registry/sql.py
+++ b/sdk/python/feast/infra/registry/sql.py
@@ -234,9 +234,6 @@ class SqlRegistryConfig(RegistryConfig):
     sqlalchemy_config_kwargs: Dict[str, Any] = {"echo": False}
     """ Dict[str, Any]: Extra arguments to pass to SQLAlchemy.create_engine. """
 
-    cache_mode: StrictStr = "sync"
-    """ str: Cache mode type, Possible options are sync and thread(asynchronous caching using threading library)"""
-
     thread_pool_executor_worker_count: StrictInt = 0
     """ int: Number of worker threads to use for asynchronous caching in SQL Registry. If set to 0, it doesn't use ThreadPoolExecutor. """
 
diff --git a/sdk/python/feast/offline_server.py b/sdk/python/feast/offline_server.py
index 776a0dfb96d..6bc573888fc 100644
--- a/sdk/python/feast/offline_server.py
+++ b/sdk/python/feast/offline_server.py
@@ -449,6 +449,17 @@ def get_historical_features(self, command: dict, key: Optional[str] = None):
                 resource=feature_view, actions=[AuthzedAction.READ_OFFLINE]
             )
 
+        # Extract and deserialize start_date/end_date if present
+        kwargs = {}
+        if "start_date" in command and command["start_date"] is not None:
+            kwargs["start_date"] = utils.make_tzaware(
+                datetime.fromisoformat(command["start_date"])
+            )
+        if "end_date" in command and command["end_date"] is not None:
+            kwargs["end_date"] = utils.make_tzaware(
+                datetime.fromisoformat(command["end_date"])
+            )
+
         retJob = self.offline_store.get_historical_features(
             config=self.store.config,
             feature_views=feature_views,
@@ -457,6 +468,7 @@ def get_historical_features(self, command: dict, key: Optional[str] = None):
             registry=self.store.registry,
             project=project,
             full_feature_names=full_feature_names,
+            **kwargs,
         )
 
         return retJob
diff --git a/sdk/python/feast/protos/feast/core/FeatureView_pb2.py b/sdk/python/feast/protos/feast/core/FeatureView_pb2.py
index b7032bc6a00..9a59255375f 100644
--- a/sdk/python/feast/protos/feast/core/FeatureView_pb2.py
+++ b/sdk/python/feast/protos/feast/core/FeatureView_pb2.py
@@ -19,7 +19,7 @@
 from feast.protos.feast.core import Transformation_pb2 as feast_dot_core_dot_Transformation__pb2
 
 
-DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x1c\x66\x65\x61st/core/FeatureView.proto\x12\nfeast.core\x1a\x1egoogle/protobuf/duration.proto\x1a\x1fgoogle/protobuf/timestamp.proto\x1a\x1b\x66\x65\x61st/core/DataSource.proto\x1a\x18\x66\x65\x61st/core/Feature.proto\x1a\x1f\x66\x65\x61st/core/Transformation.proto\"c\n\x0b\x46\x65\x61tureView\x12)\n\x04spec\x18\x01 \x01(\x0b\x32\x1b.feast.core.FeatureViewSpec\x12)\n\x04meta\x18\x02 \x01(\x0b\x32\x1b.feast.core.FeatureViewMeta\"\xc6\x04\n\x0f\x46\x65\x61tureViewSpec\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0f\n\x07project\x18\x02 \x01(\t\x12\x10\n\x08\x65ntities\x18\x03 \x03(\t\x12+\n\x08\x66\x65\x61tures\x18\x04 \x03(\x0b\x32\x19.feast.core.FeatureSpecV2\x12\x31\n\x0e\x65ntity_columns\x18\x0c \x03(\x0b\x32\x19.feast.core.FeatureSpecV2\x12\x13\n\x0b\x64\x65scription\x18\n \x01(\t\x12\x33\n\x04tags\x18\x05 \x03(\x0b\x32%.feast.core.FeatureViewSpec.TagsEntry\x12\r\n\x05owner\x18\x0b \x01(\t\x12&\n\x03ttl\x18\x06 \x01(\x0b\x32\x19.google.protobuf.Duration\x12,\n\x0c\x62\x61tch_source\x18\x07 \x01(\x0b\x32\x16.feast.core.DataSource\x12-\n\rstream_source\x18\t \x01(\x0b\x32\x16.feast.core.DataSource\x12\x0e\n\x06online\x18\x08 \x01(\x08\x12\x0f\n\x07offline\x18\r \x01(\x08\x12\x31\n\x0csource_views\x18\x0e \x03(\x0b\x32\x1b.feast.core.FeatureViewSpec\x12\x43\n\x16\x66\x65\x61ture_transformation\x18\x0f \x01(\x0b\x32#.feast.core.FeatureTransformationV2\x1a+\n\tTagsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\"\xcc\x01\n\x0f\x46\x65\x61tureViewMeta\x12\x35\n\x11\x63reated_timestamp\x18\x01 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12:\n\x16last_updated_timestamp\x18\x02 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12\x46\n\x19materialization_intervals\x18\x03 \x03(\x0b\x32#.feast.core.MaterializationInterval\"w\n\x17MaterializationInterval\x12.\n\nstart_time\x18\x01 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12,\n\x08\x65nd_time\x18\x02 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\"@\n\x0f\x46\x65\x61tureViewList\x12-\n\x0c\x66\x65\x61tureviews\x18\x01 \x03(\x0b\x32\x17.feast.core.FeatureViewBU\n\x10\x66\x65\x61st.proto.coreB\x10\x46\x65\x61tureViewProtoZ/github.com/feast-dev/feast/go/protos/feast/coreb\x06proto3')
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x1c\x66\x65\x61st/core/FeatureView.proto\x12\nfeast.core\x1a\x1egoogle/protobuf/duration.proto\x1a\x1fgoogle/protobuf/timestamp.proto\x1a\x1b\x66\x65\x61st/core/DataSource.proto\x1a\x18\x66\x65\x61st/core/Feature.proto\x1a\x1f\x66\x65\x61st/core/Transformation.proto\"c\n\x0b\x46\x65\x61tureView\x12)\n\x04spec\x18\x01 \x01(\x0b\x32\x1b.feast.core.FeatureViewSpec\x12)\n\x04meta\x18\x02 \x01(\x0b\x32\x1b.feast.core.FeatureViewMeta\"\xd4\x04\n\x0f\x46\x65\x61tureViewSpec\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0f\n\x07project\x18\x02 \x01(\t\x12\x10\n\x08\x65ntities\x18\x03 \x03(\t\x12+\n\x08\x66\x65\x61tures\x18\x04 \x03(\x0b\x32\x19.feast.core.FeatureSpecV2\x12\x33\n\x04tags\x18\x05 \x03(\x0b\x32%.feast.core.FeatureViewSpec.TagsEntry\x12&\n\x03ttl\x18\x06 \x01(\x0b\x32\x19.google.protobuf.Duration\x12,\n\x0c\x62\x61tch_source\x18\x07 \x01(\x0b\x32\x16.feast.core.DataSource\x12\x0e\n\x06online\x18\x08 \x01(\x08\x12-\n\rstream_source\x18\t \x01(\x0b\x32\x16.feast.core.DataSource\x12\x13\n\x0b\x64\x65scription\x18\n \x01(\t\x12\r\n\x05owner\x18\x0b \x01(\t\x12\x31\n\x0e\x65ntity_columns\x18\x0c \x03(\x0b\x32\x19.feast.core.FeatureSpecV2\x12\x0f\n\x07offline\x18\r \x01(\x08\x12\x31\n\x0csource_views\x18\x0e \x03(\x0b\x32\x1b.feast.core.FeatureViewSpec\x12\x43\n\x16\x66\x65\x61ture_transformation\x18\x0f \x01(\x0b\x32#.feast.core.FeatureTransformationV2\x12\x0c\n\x04mode\x18\x10 \x01(\t\x1a+\n\tTagsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\"\xcc\x01\n\x0f\x46\x65\x61tureViewMeta\x12\x35\n\x11\x63reated_timestamp\x18\x01 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12:\n\x16last_updated_timestamp\x18\x02 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12\x46\n\x19materialization_intervals\x18\x03 \x03(\x0b\x32#.feast.core.MaterializationInterval\"w\n\x17MaterializationInterval\x12.\n\nstart_time\x18\x01 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12,\n\x08\x65nd_time\x18\x02 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\"@\n\x0f\x46\x65\x61tureViewList\x12-\n\x0c\x66\x65\x61tureviews\x18\x01 \x03(\x0b\x32\x17.feast.core.FeatureViewBU\n\x10\x66\x65\x61st.proto.coreB\x10\x46\x65\x61tureViewProtoZ/github.com/feast-dev/feast/go/protos/feast/coreb\x06proto3')
 
 _globals = globals()
 _builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
@@ -32,13 +32,13 @@
   _globals['_FEATUREVIEW']._serialized_start=197
   _globals['_FEATUREVIEW']._serialized_end=296
   _globals['_FEATUREVIEWSPEC']._serialized_start=299
-  _globals['_FEATUREVIEWSPEC']._serialized_end=881
-  _globals['_FEATUREVIEWSPEC_TAGSENTRY']._serialized_start=838
-  _globals['_FEATUREVIEWSPEC_TAGSENTRY']._serialized_end=881
-  _globals['_FEATUREVIEWMETA']._serialized_start=884
-  _globals['_FEATUREVIEWMETA']._serialized_end=1088
-  _globals['_MATERIALIZATIONINTERVAL']._serialized_start=1090
-  _globals['_MATERIALIZATIONINTERVAL']._serialized_end=1209
-  _globals['_FEATUREVIEWLIST']._serialized_start=1211
-  _globals['_FEATUREVIEWLIST']._serialized_end=1275
+  _globals['_FEATUREVIEWSPEC']._serialized_end=895
+  _globals['_FEATUREVIEWSPEC_TAGSENTRY']._serialized_start=852
+  _globals['_FEATUREVIEWSPEC_TAGSENTRY']._serialized_end=895
+  _globals['_FEATUREVIEWMETA']._serialized_start=898
+  _globals['_FEATUREVIEWMETA']._serialized_end=1102
+  _globals['_MATERIALIZATIONINTERVAL']._serialized_start=1104
+  _globals['_MATERIALIZATIONINTERVAL']._serialized_end=1223
+  _globals['_FEATUREVIEWLIST']._serialized_start=1225
+  _globals['_FEATUREVIEWLIST']._serialized_end=1289
 # @@protoc_insertion_point(module_scope)
diff --git a/sdk/python/feast/protos/feast/core/FeatureView_pb2.pyi b/sdk/python/feast/protos/feast/core/FeatureView_pb2.pyi
index d90d8b7e419..30a0bcf5679 100644
--- a/sdk/python/feast/protos/feast/core/FeatureView_pb2.pyi
+++ b/sdk/python/feast/protos/feast/core/FeatureView_pb2.pyi
@@ -58,7 +58,7 @@ class FeatureView(google.protobuf.message.Message):
 global___FeatureView = FeatureView
 
 class FeatureViewSpec(google.protobuf.message.Message):
-    """Next available id: 16
+    """Next available id: 17
     TODO(adchia): refactor common fields from this and ODFV into separate metadata proto
     """
 
@@ -83,17 +83,18 @@ class FeatureViewSpec(google.protobuf.message.Message):
     PROJECT_FIELD_NUMBER: builtins.int
     ENTITIES_FIELD_NUMBER: builtins.int
     FEATURES_FIELD_NUMBER: builtins.int
-    ENTITY_COLUMNS_FIELD_NUMBER: builtins.int
-    DESCRIPTION_FIELD_NUMBER: builtins.int
     TAGS_FIELD_NUMBER: builtins.int
-    OWNER_FIELD_NUMBER: builtins.int
     TTL_FIELD_NUMBER: builtins.int
     BATCH_SOURCE_FIELD_NUMBER: builtins.int
-    STREAM_SOURCE_FIELD_NUMBER: builtins.int
     ONLINE_FIELD_NUMBER: builtins.int
+    STREAM_SOURCE_FIELD_NUMBER: builtins.int
+    DESCRIPTION_FIELD_NUMBER: builtins.int
+    OWNER_FIELD_NUMBER: builtins.int
+    ENTITY_COLUMNS_FIELD_NUMBER: builtins.int
     OFFLINE_FIELD_NUMBER: builtins.int
     SOURCE_VIEWS_FIELD_NUMBER: builtins.int
     FEATURE_TRANSFORMATION_FIELD_NUMBER: builtins.int
+    MODE_FIELD_NUMBER: builtins.int
     name: builtins.str
     """Name of the feature view. Must be unique. Not updated."""
     project: builtins.str
@@ -105,15 +106,8 @@ class FeatureViewSpec(google.protobuf.message.Message):
     def features(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[feast.core.Feature_pb2.FeatureSpecV2]:
         """List of specifications for each feature defined as part of this feature view."""
     @property
-    def entity_columns(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[feast.core.Feature_pb2.FeatureSpecV2]:
-        """List of specifications for each entity defined as part of this feature view."""
-    description: builtins.str
-    """Description of the feature view."""
-    @property
     def tags(self) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]:
         """User defined metadata"""
-    owner: builtins.str
-    """Owner of the feature view."""
     @property
     def ttl(self) -> google.protobuf.duration_pb2.Duration:
         """Features in this feature view can only be retrieved from online serving
@@ -124,20 +118,29 @@ class FeatureViewSpec(google.protobuf.message.Message):
     @property
     def batch_source(self) -> feast.core.DataSource_pb2.DataSource:
         """Batch/Offline DataSource where this view can retrieve offline feature data."""
-    @property
-    def stream_source(self) -> feast.core.DataSource_pb2.DataSource:
-        """Streaming DataSource from where this view can consume "online" feature data."""
     online: builtins.bool
     """Whether these features should be served online or not
     This is also used to determine whether the features should be written to the online store
     """
+    @property
+    def stream_source(self) -> feast.core.DataSource_pb2.DataSource:
+        """Streaming DataSource from where this view can consume "online" feature data."""
+    description: builtins.str
+    """Description of the feature view."""
+    owner: builtins.str
+    """Owner of the feature view."""
+    @property
+    def entity_columns(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[feast.core.Feature_pb2.FeatureSpecV2]:
+        """List of specifications for each entity defined as part of this feature view."""
     offline: builtins.bool
     """Whether these features should be written to the offline store"""
     @property
     def source_views(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___FeatureViewSpec]: ...
     @property
     def feature_transformation(self) -> feast.core.Transformation_pb2.FeatureTransformationV2:
-        """Feature transformation (UDF or Substrait) for batch feature views"""
+        """Feature transformation for batch feature views"""
+    mode: builtins.str
+    """The transformation mode (e.g., "python", "pandas", "ray", "spark", "sql")"""
     def __init__(
         self,
         *,
@@ -145,20 +148,21 @@ class FeatureViewSpec(google.protobuf.message.Message):
         project: builtins.str = ...,
         entities: collections.abc.Iterable[builtins.str] | None = ...,
         features: collections.abc.Iterable[feast.core.Feature_pb2.FeatureSpecV2] | None = ...,
-        entity_columns: collections.abc.Iterable[feast.core.Feature_pb2.FeatureSpecV2] | None = ...,
-        description: builtins.str = ...,
         tags: collections.abc.Mapping[builtins.str, builtins.str] | None = ...,
-        owner: builtins.str = ...,
         ttl: google.protobuf.duration_pb2.Duration | None = ...,
         batch_source: feast.core.DataSource_pb2.DataSource | None = ...,
-        stream_source: feast.core.DataSource_pb2.DataSource | None = ...,
         online: builtins.bool = ...,
+        stream_source: feast.core.DataSource_pb2.DataSource | None = ...,
+        description: builtins.str = ...,
+        owner: builtins.str = ...,
+        entity_columns: collections.abc.Iterable[feast.core.Feature_pb2.FeatureSpecV2] | None = ...,
         offline: builtins.bool = ...,
         source_views: collections.abc.Iterable[global___FeatureViewSpec] | None = ...,
         feature_transformation: feast.core.Transformation_pb2.FeatureTransformationV2 | None = ...,
+        mode: builtins.str = ...,
     ) -> None: ...
     def HasField(self, field_name: typing_extensions.Literal["batch_source", b"batch_source", "feature_transformation", b"feature_transformation", "stream_source", b"stream_source", "ttl", b"ttl"]) -> builtins.bool: ...
-    def ClearField(self, field_name: typing_extensions.Literal["batch_source", b"batch_source", "description", b"description", "entities", b"entities", "entity_columns", b"entity_columns", "feature_transformation", b"feature_transformation", "features", b"features", "name", b"name", "offline", b"offline", "online", b"online", "owner", b"owner", "project", b"project", "source_views", b"source_views", "stream_source", b"stream_source", "tags", b"tags", "ttl", b"ttl"]) -> None: ...
+    def ClearField(self, field_name: typing_extensions.Literal["batch_source", b"batch_source", "description", b"description", "entities", b"entities", "entity_columns", b"entity_columns", "feature_transformation", b"feature_transformation", "features", b"features", "mode", b"mode", "name", b"name", "offline", b"offline", "online", b"online", "owner", b"owner", "project", b"project", "source_views", b"source_views", "stream_source", b"stream_source", "tags", b"tags", "ttl", b"ttl"]) -> None: ...
 
 global___FeatureViewSpec = FeatureViewSpec
 
diff --git a/sdk/python/feast/protos/feast/core/Transformation_pb2.py b/sdk/python/feast/protos/feast/core/Transformation_pb2.py
index 9fd11d3026b..c322bc1925c 100644
--- a/sdk/python/feast/protos/feast/core/Transformation_pb2.py
+++ b/sdk/python/feast/protos/feast/core/Transformation_pb2.py
@@ -14,7 +14,7 @@
 
 
 
-DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x1f\x66\x65\x61st/core/Transformation.proto\x12\nfeast.core\"F\n\x15UserDefinedFunctionV2\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0c\n\x04\x62ody\x18\x02 \x01(\x0c\x12\x11\n\tbody_text\x18\x03 \x01(\t\"\xba\x01\n\x17\x46\x65\x61tureTransformationV2\x12\x42\n\x15user_defined_function\x18\x01 \x01(\x0b\x32!.feast.core.UserDefinedFunctionV2H\x00\x12I\n\x18substrait_transformation\x18\x02 \x01(\x0b\x32%.feast.core.SubstraitTransformationV2H\x00\x42\x10\n\x0etransformation\"J\n\x19SubstraitTransformationV2\x12\x16\n\x0esubstrait_plan\x18\x01 \x01(\x0c\x12\x15\n\ribis_function\x18\x02 \x01(\x0c\x42_\n\x10\x66\x65\x61st.proto.coreB\x1a\x46\x65\x61tureTransformationProtoZ/github.com/feast-dev/feast/go/protos/feast/coreb\x06proto3')
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x1f\x66\x65\x61st/core/Transformation.proto\x12\nfeast.core\"T\n\x15UserDefinedFunctionV2\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0c\n\x04\x62ody\x18\x02 \x01(\x0c\x12\x11\n\tbody_text\x18\x03 \x01(\t\x12\x0c\n\x04mode\x18\x04 \x01(\t\"\xba\x01\n\x17\x46\x65\x61tureTransformationV2\x12\x42\n\x15user_defined_function\x18\x01 \x01(\x0b\x32!.feast.core.UserDefinedFunctionV2H\x00\x12I\n\x18substrait_transformation\x18\x02 \x01(\x0b\x32%.feast.core.SubstraitTransformationV2H\x00\x42\x10\n\x0etransformation\"J\n\x19SubstraitTransformationV2\x12\x16\n\x0esubstrait_plan\x18\x01 \x01(\x0c\x12\x15\n\ribis_function\x18\x02 \x01(\x0c\x42_\n\x10\x66\x65\x61st.proto.coreB\x1a\x46\x65\x61tureTransformationProtoZ/github.com/feast-dev/feast/go/protos/feast/coreb\x06proto3')
 
 _globals = globals()
 _builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
@@ -23,9 +23,9 @@
   _globals['DESCRIPTOR']._options = None
   _globals['DESCRIPTOR']._serialized_options = b'\n\020feast.proto.coreB\032FeatureTransformationProtoZ/github.com/feast-dev/feast/go/protos/feast/core'
   _globals['_USERDEFINEDFUNCTIONV2']._serialized_start=47
-  _globals['_USERDEFINEDFUNCTIONV2']._serialized_end=117
-  _globals['_FEATURETRANSFORMATIONV2']._serialized_start=120
-  _globals['_FEATURETRANSFORMATIONV2']._serialized_end=306
-  _globals['_SUBSTRAITTRANSFORMATIONV2']._serialized_start=308
-  _globals['_SUBSTRAITTRANSFORMATIONV2']._serialized_end=382
+  _globals['_USERDEFINEDFUNCTIONV2']._serialized_end=131
+  _globals['_FEATURETRANSFORMATIONV2']._serialized_start=134
+  _globals['_FEATURETRANSFORMATIONV2']._serialized_end=320
+  _globals['_SUBSTRAITTRANSFORMATIONV2']._serialized_start=322
+  _globals['_SUBSTRAITTRANSFORMATIONV2']._serialized_end=396
 # @@protoc_insertion_point(module_scope)
diff --git a/sdk/python/feast/protos/feast/core/Transformation_pb2.pyi b/sdk/python/feast/protos/feast/core/Transformation_pb2.pyi
index 1120c447e01..fb56ab5bc73 100644
--- a/sdk/python/feast/protos/feast/core/Transformation_pb2.pyi
+++ b/sdk/python/feast/protos/feast/core/Transformation_pb2.pyi
@@ -22,20 +22,24 @@ class UserDefinedFunctionV2(google.protobuf.message.Message):
     NAME_FIELD_NUMBER: builtins.int
     BODY_FIELD_NUMBER: builtins.int
     BODY_TEXT_FIELD_NUMBER: builtins.int
+    MODE_FIELD_NUMBER: builtins.int
     name: builtins.str
     """The function name"""
     body: builtins.bytes
     """The python-syntax function body (serialized by dill)"""
     body_text: builtins.str
     """The string representation of the udf"""
+    mode: builtins.str
+    """The transformation mode (e.g., "python", "pandas", "ray", "spark", "sql")"""
     def __init__(
         self,
         *,
         name: builtins.str = ...,
         body: builtins.bytes = ...,
         body_text: builtins.str = ...,
+        mode: builtins.str = ...,
     ) -> None: ...
-    def ClearField(self, field_name: typing_extensions.Literal["body", b"body", "body_text", b"body_text", "name", b"name"]) -> None: ...
+    def ClearField(self, field_name: typing_extensions.Literal["body", b"body", "body_text", b"body_text", "mode", b"mode", "name", b"name"]) -> None: ...
 
 global___UserDefinedFunctionV2 = UserDefinedFunctionV2
 
diff --git a/sdk/python/feast/repo_config.py b/sdk/python/feast/repo_config.py
index 395720304de..895002948f1 100644
--- a/sdk/python/feast/repo_config.py
+++ b/sdk/python/feast/repo_config.py
@@ -152,6 +152,12 @@ class RegistryConfig(FeastBaseModel):
      set to infinity by setting TTL to 0 seconds, which means the cache will only be loaded once and will never
      expire. Users can manually refresh the cache by calling feature_store.refresh_registry() """
 
+    cache_mode: StrictStr = "sync"
+    """str: Cache mode type. Possible options are 'sync' (immediate refresh after each write operation) and
+     'thread' (asynchronous background refresh at cache_ttl_seconds intervals). In 'sync' mode, registry changes
+     are immediately visible. In 'thread' mode, changes may take up to
+     cache_ttl_seconds to be visible."""
+
     s3_additional_kwargs: Optional[Dict[str, str]] = None
     """ Dict[str, str]: Extra arguments to pass to boto3 when writing the registry file to S3. """
 
diff --git a/sdk/python/feast/stream_feature_view.py b/sdk/python/feast/stream_feature_view.py
index 7225be4b7ec..ff6d603333d 100644
--- a/sdk/python/feast/stream_feature_view.py
+++ b/sdk/python/feast/stream_feature_view.py
@@ -157,6 +157,7 @@ def __init__(
             owner=owner,
             schema=schema,
             source=source,  # type: ignore[arg-type]
+            mode=mode,
             sink_source=sink_source,
         )
 
diff --git a/sdk/python/feast/templates/ray_rag/README.md b/sdk/python/feast/templates/ray_rag/README.md
new file mode 100644
index 00000000000..e1289826c6a
--- /dev/null
+++ b/sdk/python/feast/templates/ray_rag/README.md
@@ -0,0 +1,181 @@
+# Feast Ray RAG Template - Batch Embedding at scale for RAG with Ray
+
+RAG (Retrieval-Augmented Generation) template using Feast with Ray for distributed processing and Milvus for vector search.
+
+## 🚀 What This Template Provides
+
+- **🎬 Sample IMDB Data**: 10 curated movies included for quick demos
+- **⚡ Ray Distributed Processing**: Parallel embedding generation across workers
+- **🔍 Vector Search**: Milvus integration for semantic similarity
+- **🎯 Complete Pipeline**: Data → Embeddings → Search in one workflow
+- **📦 Ready to Scale**: Easy upgrade to full dataset (48K+ movies) if needed
+
+## 📁 Template Structure
+
+```
+ray_rag/
+├── feature_repo/
+│   ├── feature_store.yaml      # Ray + Milvus configuration
+│   ├── example_repo.py         # Feature definitions with Ray UDF
+│   ├── test_workflow.py        # End-to-end demo
+│   └── data/                   
+│       └── raw_movies.parquet  # Sample IMDB dataset (10 movies)
+├── bootstrap.py                # Template initialization
+└── README.md
+```
+
+## 🚦 Quick Start
+
+### 1. Initialize Template
+
+```bash
+feast init -t ray_rag my_rag_project
+cd my_rag_project/feature_repo
+```
+
+The template includes a sample dataset with 10 movies for quick testing.
+
+### 2. Install Dependencies
+
+```bash
+# Core dependencies
+pip install feast[ray] sentence-transformers
+```
+
+### 3. Apply Feature Definitions
+
+```bash
+feast apply
+```
+
+### 4. Materialize Features
+
+```bash
+# Generate embeddings for sample movies
+feast materialize --disable-event-timestamp 
+```
+
+### 5. Test the Pipeline
+
+```bash
+python test_workflow.py
+```
+
+Expected output with sample dataset:
+- ✅ 10 embeddings materialized
+- ✅ Vector search working with relevant results
+- ✅ Similarity scores for relevant matches
+
+
+## 📊 Architecture
+
+```
+Raw Data (IMDB CSV)
+    ↓
+Ray Offline Store (Distributed I/O)
+    ↓
+Ray Compute Engine (Parallel Embedding Generation)
+    ↓  
+Milvus Online Store (Vector Search)
+    ↓
+RAG Application
+```
+
+
+## 🎬 Example Workflow
+
+```python
+from feast import FeatureStore
+from sentence_transformers import SentenceTransformer
+
+# 1. Initialize
+store = FeatureStore(repo_path=".")
+
+# 2. Materialize (embeddings generated in parallel)
+store.materialize_incremental(end_date)
+
+# 3. Search using Feast API
+model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
+query_embedding = model.encode(["sci-fi movie about space"])[0].tolist()
+
+results = store.retrieve_online_documents_v2(
+    features=[
+        "document_embeddings:embedding",
+        "document_embeddings:movie_name",
+        "document_embeddings:movie_director",
+    ],
+    query=query_embedding,
+    top_k=5,
+).to_dict()
+
+# Display results with metadata
+for i in range(len(results["document_id_pk"])):
+    print(f"{i+1}. {results['movie_name'][i]}")
+    print(f"   Director: {results['movie_director'][i]}")
+    print(f"   Distance: {results['distance'][i]:.3f}")
+```
+
+## 📥 Using the Full IMDB Dataset (Optional)
+
+The template includes a small sample dataset (10 movies) for quick testing. To work with the full dataset containing 48K+ movies:
+
+### Option 1: Download via Kaggle API
+
+1. **Setup Kaggle credentials:**
+   ```bash
+   # Get API credentials from https://www.kaggle.com/account
+   # Place kaggle.json in ~/.kaggle/
+   chmod 600 ~/.kaggle/kaggle.json
+   ```
+
+2. **Install Kaggle API and download dataset:**
+   ```bash
+   pip install kaggle
+   
+   # Download to your feature_repo/data directory
+   cd feature_repo
+   kaggle datasets download -d yashgupta24/48000-movies-dataset -p ./data --unzip
+   ```
+
+3. **Convert to parquet format:**
+   ```python
+   import pandas as pd
+   import pyarrow as pa
+   import pyarrow.parquet as pq
+   from pathlib import Path
+   
+   # Read the CSV file (filename may vary)
+   data_path = Path("./data")
+   csv_files = list(data_path.glob("*.csv"))
+   df = pd.read_csv(csv_files[0])
+   
+   # Convert DatePublished to datetime with UTC timezone
+   df = df.dropna(subset=["DatePublished"])
+   df["DatePublished"] = pd.to_datetime(df["DatePublished"], errors="coerce", utc=True)
+   
+   # Write to parquet
+   table = pa.Table.from_pandas(df)
+   pq.write_table(table, data_path / "raw_movies.parquet")
+   print(f"✅ Converted {len(df)} movies to parquet format")
+   ```
+
+4. **Run the full pipeline:**
+   ```bash
+   feast apply
+   feast materialize --disable-event-timestamp
+   python test_workflow.py
+   ```
+
+### Option 2: Use Your Own Dataset
+
+Replace `feature_repo/data/raw_movies.parquet` with your own dataset. Required schema:
+
+- `id`: Unique identifier (string)
+- `Name`: Movie name (string)
+- `Description`: Movie description for embedding (string)
+- `Director`: Director name (string)
+- `Genres`: Comma-separated genres (string)
+- `RatingValue`: Rating score (float)
+- `DatePublished`: Publication date (datetime with UTC timezone)
+
+The Ray embedding pipeline will automatically process your dataset in parallel.
diff --git a/sdk/python/feast/templates/ray_rag/__init__.py b/sdk/python/feast/templates/ray_rag/__init__.py
new file mode 100644
index 00000000000..e0a1678e04e
--- /dev/null
+++ b/sdk/python/feast/templates/ray_rag/__init__.py
@@ -0,0 +1 @@
+# Ray RAG Template for Feast
diff --git a/sdk/python/feast/templates/ray_rag/bootstrap.py b/sdk/python/feast/templates/ray_rag/bootstrap.py
new file mode 100644
index 00000000000..752cee0a5c8
--- /dev/null
+++ b/sdk/python/feast/templates/ray_rag/bootstrap.py
@@ -0,0 +1,90 @@
+import pathlib
+
+import pandas as pd
+import pyarrow as pa
+import pyarrow.parquet as pq
+
+from feast.file_utils import replace_str_in_file
+
+
+def bootstrap():
+    repo_path = pathlib.Path(__file__).parent.absolute() / "feature_repo"
+    project_name = pathlib.Path(__file__).parent.absolute().name
+    data_path = repo_path / "data"
+    data_path.mkdir(exist_ok=True)
+
+    print("   🎬 Setting up sample IMDB movie data for RAG demonstration...")
+
+    parquet_file = data_path / "raw_movies.parquet"
+
+    if parquet_file.exists():
+        try:
+            df = pd.read_parquet(parquet_file)
+            print(f"   ✅ Sample dataset ready with {len(df)} movies")
+            print("   💡 For full dataset (48K+ movies), see README.md")
+        except Exception as e:
+            print(f"   ⚠️  Could not read sample dataset: {e}")
+    else:
+        print("   ⚠️  Sample dataset not found, creating minimal example...")
+        sample_data = pd.DataFrame(
+            {
+                "id": ["tt0111161", "tt0068646", "tt0468569", "tt0071562", "tt0050083"],
+                "Name": [
+                    "The Shawshank Redemption",
+                    "The Godfather",
+                    "The Dark Knight",
+                    "The Godfather Part II",
+                    "12 Angry Men",
+                ],
+                "Description": [
+                    "Two imprisoned men bond over a number of years, finding solace and eventual redemption through acts of common decency.",
+                    "The aging patriarch of an organized crime dynasty transfers control of his clandestine empire to his reluctant son.",
+                    "When the menace known as the Joker wreaks havoc and chaos on the people of Gotham, Batman must accept one of the greatest psychological and physical tests.",
+                    "The early life and career of Vito Corleone in 1920s New York City is portrayed, while his son, Michael, expands and tightens his grip on the family crime syndicate.",
+                    "A jury holdout attempts to prevent a miscarriage of justice by forcing his colleagues to reconsider the evidence.",
+                ],
+                "Director": [
+                    "Frank Darabont",
+                    "Francis Ford Coppola",
+                    "Christopher Nolan",
+                    "Francis Ford Coppola",
+                    "Sidney Lumet",
+                ],
+                "Genres": [
+                    "Drama",
+                    "Crime, Drama",
+                    "Action, Crime, Drama",
+                    "Crime, Drama",
+                    "Crime, Drama",
+                ],
+                "RatingValue": [9.3, 9.2, 9.0, 9.0, 9.0],
+                "DatePublished": pd.to_datetime(
+                    [
+                        "1994-09-23",
+                        "1972-03-24",
+                        "2008-07-18",
+                        "1974-12-20",
+                        "1957-04-10",
+                    ],
+                    utc=True,
+                ),
+            }
+        )
+        table = pa.Table.from_pandas(sample_data)
+        pq.write_table(table, parquet_file)
+        print(f"   ✅ Created sample dataset with {len(sample_data)} movies")
+
+    example_py_file = repo_path / "example_repo.py"
+    replace_str_in_file(example_py_file, "%PROJECT_NAME%", str(project_name))
+
+    print("🚀 Ray RAG template initialized successfully!")
+
+    print("\n🎯 To get started:")
+    print(f"  1. cd {project_name}/feature_repo")
+    print("  2. feast apply")
+    print("  3. feast materialize --disable-event-timestamp")
+    print("  4. python test_workflow.py")
+
+
+if __name__ == "__main__":
+    bootstrap()
diff --git a/sdk/python/feast/templates/ray_rag/feature_repo/__init__.py b/sdk/python/feast/templates/ray_rag/feature_repo/__init__.py
new file mode 100644
index 00000000000..7349767eb35
--- /dev/null
+++ b/sdk/python/feast/templates/ray_rag/feature_repo/__init__.py
@@ -0,0 +1 @@
+# Ray RAG Feature Repository
diff --git a/sdk/python/feast/templates/ray_rag/feature_repo/example_repo.py b/sdk/python/feast/templates/ray_rag/feature_repo/example_repo.py
new file mode 100644
index 00000000000..5312996fd92
--- /dev/null
+++ b/sdk/python/feast/templates/ray_rag/feature_repo/example_repo.py
@@ -0,0 +1,139 @@
+"""
+RAG Feature Repository - Movie Embeddings with Ray Native Processing
+
+This template demonstrates distributed embedding generation using:
+- Ray offline store for scalable data I/O
+- Ray compute engine for parallel processing
+- Milvus online store with vector search capabilities
+"""
+
+from datetime import timedelta
+from pathlib import Path
+
+import pandas as pd
+
+from feast import BatchFeatureView, Entity, Field, FileSource, ValueType
+from feast.types import Array, Float32, String
+
+# Configuration
+repo_path = Path(__file__).parent
+data_path = repo_path / "data"
+data_path.mkdir(exist_ok=True)
+
+EMBED_MODEL_ID = "sentence-transformers/all-MiniLM-L6-v2"
+
+# Entity definition
+document = Entity(
+    name="document_id",
+    join_keys=["document_id_pk"],
+    value_type=ValueType.STRING,
+    description="Document identifier for RAG retrieval",
+)
+
+# Data source
+movies_source = FileSource(
+    path=str(data_path / "raw_movies.parquet"),
+    timestamp_field="DatePublished",
+)
+
+
+# Embedding processor for distributed Ray processing
+class EmbeddingProcessor:
+    """
+    Generate embeddings using SentenceTransformer model.
+    Model is loaded once per worker and reused for all batches.
+    """
+
+    def __init__(self):
+        """Initialize model once per worker."""
+        import torch
+        from sentence_transformers import SentenceTransformer
+
+        device = "cuda" if torch.cuda.is_available() else "cpu"
+        self.model = SentenceTransformer(EMBED_MODEL_ID, device=device)
+
+    def __call__(self, batch: pd.DataFrame) -> pd.DataFrame:
+        """Process batch and generate embeddings."""
+        if "id" in batch.columns:
+            batch["document_id"] = "movie_" + batch["id"].astype(str)
+            batch["document_id_pk"] = batch["document_id"]
+
+        # Generate embeddings from descriptions
+        if "Description" in batch.columns:
+            descriptions = batch["Description"].fillna("").tolist()
+            model_batch_size = min(128, max(32, len(descriptions)))
+            embeddings = self.model.encode(
+                descriptions,
+                show_progress_bar=False,
+                batch_size=model_batch_size,
+                normalize_embeddings=True,
+                convert_to_numpy=True,
+            )
+            batch["embedding"] = embeddings.tolist()
+            batch["embedding_model"] = EMBED_MODEL_ID
+
+        # Standardize movie-related metadata
+        if "Name" in batch.columns:
+            batch["movie_name"] = batch["Name"].fillna("")
+        if "Director" in batch.columns:
+            batch["movie_director"] = batch["Director"].fillna("")
+        if "Genres" in batch.columns:
+            batch["movie_genres"] = batch["Genres"].fillna("")
+        if "RatingValue" in batch.columns:
+            batch["movie_rating"] = batch["RatingValue"].fillna(0.0)
+
+        return batch
+
+
+# Ray native UDF - Fully adaptive to cluster resources
+def generate_embeddings_ray_native(ds):
+    """
+    Distributed embedding generation using Ray Data.
+    """
+    # Ray transformation mode providing control to user over the resources
+    # Optimize the resources for the transformation
+    num_blocks = ds.num_blocks()
+    max_workers = 9
+    batch_size = 2500
+    try:
+        sample = ds.take(1)
+        has_data = len(sample) > 0
+    except Exception:
+        has_data = False
+    if has_data and num_blocks < max_workers:
+        ds = ds.repartition(max_workers)
+
+    result = ds.map_batches(
+        EmbeddingProcessor,
+        batch_format="pandas",
+        concurrency=max_workers,
+        batch_size=batch_size,
+    )
+    return result
+
+
+# Batch feature view for embeddings with metadata
+document_embeddings_view = BatchFeatureView(
+    name="document_embeddings",
+    entities=[document],
+    mode="ray",  # Native Ray Dataset mode for distributed processing
+    ttl=timedelta(days=365 * 100),
+    schema=[
+        Field(name="document_id", dtype=String),
+        Field(name="document_id_pk", dtype=String),
+        Field(name="embedding", dtype=Array(Float32), vector_index=True),
+        Field(name="embedding_model", dtype=String),
+        Field(name="movie_name", dtype=String),
+        Field(name="movie_director", dtype=String),
+        Field(name="movie_genres", dtype=String),
+        Field(name="movie_rating", dtype=Float32),
+    ],
+    source=movies_source,
+    udf=generate_embeddings_ray_native,
+    online=True,
+    tags={
+        "team": "ml_platform",
+        "use_case": "rag",
+        "transformation_mode": "ray_native",
+    },
+)
diff --git a/sdk/python/feast/templates/ray_rag/feature_repo/feature_store.yaml b/sdk/python/feast/templates/ray_rag/feature_repo/feature_store.yaml
new file mode 100644
index 00000000000..25aaef1259d
--- /dev/null
+++ b/sdk/python/feast/templates/ray_rag/feature_repo/feature_store.yaml
@@ -0,0 +1,45 @@
+project: my_project
+registry: data/registry.db
+provider: local
+
+# Ray offline store configuration for distributed data processing
+offline_store:
+  type: ray
+  storage_path: data/ray_storage              # Path for storing Ray datasets
+  broadcast_join_threshold_mb: 100
+  max_parallelism_multiplier: 2
+  target_partition_size_mb: 64
+  enable_ray_logging: true
+  # ray_address: "127.0.0.1:10001"
+  
+# Ray compute engine configuration for batch embedding processing
+batch_engine:
+  type: ray.engine
+  max_workers: 12                              # Maximum parallel workers (adjust based on CPU cores)
+  enable_optimization: true
+  broadcast_join_threshold_mb: 100
+  target_partition_size_mb: 64                 # Size of each data partition for processing
+  window_size_for_joins: "1H"
+  enable_ray_logging: true
+  # ray_address: "127.0.0.1:10001"
+
+# Online store for serving features with vector search capabilities
+online_store:
+  type: milvus
+  path: data/online_store.db
+  vector_enabled: true
+  embedding_dim: 384
+  index_type: "FLAT"
+  metric_type: "COSINE"
+
+# For production with remote Milvus, use:
+# online_store:
+#   type: milvus
+#   host: "localhost"
+#   port: 19530
+#   vector_enabled: true
+#   embedding_dim: 384
+#   index_type: "IVF_FLAT"
+#   metric_type: "COSINE"
+
+entity_key_serialization_version: 3
diff --git a/sdk/python/feast/templates/ray_rag/feature_repo/test_workflow.py b/sdk/python/feast/templates/ray_rag/feature_repo/test_workflow.py
new file mode 100644
index 00000000000..ba693d7b8b7
--- /dev/null
+++ b/sdk/python/feast/templates/ray_rag/feature_repo/test_workflow.py
@@ -0,0 +1,89 @@
+"""
+Feast-Ray RAG Pipeline Demo
+
+This script demonstrates:
+1. Ray offline store for distributed data I/O
+2. Ray compute engine for parallel embedding generation
+3. Milvus vector search for semantic similarity
+4. Complete RAG pipeline from data to search results
+
+Usage:
+    1. feast apply
+    2. feast materialize --disable-event-timestamp
+    3. python test_workflow.py
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent))
+
+try:
+    from sentence_transformers import SentenceTransformer
+
+    from feast import FeatureStore
+except ImportError as e:
+    print(f"Missing dependency: {e}")
+    print("💡 Install with: pip install feast[ray] sentence-transformers")
+    sys.exit(1)
+
+
+def main():
+    """Run the RAG pipeline demonstration."""
+
+    store = FeatureStore(repo_path=".")
+    feature_views = store.list_feature_views()
+    print(f"Feature views: {len(feature_views)}")
+
+    print("Vector similarity search with Feast ...")
+    try:
+        model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
+        query = "Crime drama about organized crime families"
+
+        print(f"\n   Query: '{query}'")
+        # Generate query embedding
+        query_embedding = model.encode([query], normalize_embeddings=True)[0].tolist()
+
+        # Use Feast's retrieve_online_documents_v2 API
+        # Request all fields we want to display
+        results = store.retrieve_online_documents_v2(
+            features=[
+                "document_embeddings:embedding",
+                "document_embeddings:movie_name",
+                "document_embeddings:movie_director",
+                "document_embeddings:movie_genres",
+                "document_embeddings:movie_rating",
+            ],
+            query=query_embedding,
+            top_k=3,
+        ).to_dict()
+
+        if results and len(results.get("document_id_pk", [])) > 0:
+            print("   📊 Top 3 results:")
+            num_results = len(results["document_id_pk"])
+            for i in range(num_results):
+                name = results.get("movie_name", ["Unknown"] * num_results)[i]
+                director = results.get("movie_director", ["Unknown"] * num_results)[i]
+                genres = results.get("movie_genres", ["Unknown"] * num_results)[i]
+                print(f"      {i + 1}. {name}")
+                print(f"         Director: {director} | Genres: {genres}")
+        else:
+            print("No results found")
+
+    except Exception as e:
+        print(f"Search failed: {e}")
+        return
+
+    print("\n📚 What was demonstrated:")
+    print("   ✅ Ray-based distributed embedding generation")
+    print("   ✅ Milvus vector storage and retrieval")
+    print("   ✅ Similarity search")
+    print("   ✅ Raw Data to Search workflow")
+
+    print("\n🚀 Next steps:")
+    print("   • Scale to larger datasets")
+    print("   • Connect to distributed Ray cluster")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/sdk/python/feast/templates/ray_rag/gitignore b/sdk/python/feast/templates/ray_rag/gitignore
new file mode 100644
index 00000000000..e4a6beecf3a
--- /dev/null
+++ b/sdk/python/feast/templates/ray_rag/gitignore
@@ -0,0 +1,109 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+
+# Feast specific
+data/
+.feast/
+ray_storage/
diff --git a/sdk/python/feast/transformation/base.py b/sdk/python/feast/transformation/base.py
index 8ff1925d0e0..474f33c962f 100644
--- a/sdk/python/feast/transformation/base.py
+++ b/sdk/python/feast/transformation/base.py
@@ -90,10 +90,14 @@ def __init__(
         self.owner = owner
 
     def to_proto(self) -> Union[UserDefinedFunctionProto, SubstraitTransformationProto]:
+        mode_str = (
+            self.mode.value if isinstance(self.mode, TransformationMode) else self.mode
+        )
         return UserDefinedFunctionProto(
             name=self.udf.__name__,
             body=dill.dumps(self.udf, recurse=True),
             body_text=self.udf_string,
+            mode=mode_str,
         )
 
     def __deepcopy__(self, memo: Optional[Dict[int, Any]] = None) -> "Transformation":
diff --git a/sdk/python/feast/transformation/factory.py b/sdk/python/feast/transformation/factory.py
index 50c3c665764..16d7a7570d5 100644
--- a/sdk/python/feast/transformation/factory.py
+++ b/sdk/python/feast/transformation/factory.py
@@ -7,6 +7,7 @@
     "sql": "feast.transformation.sql_transformation.SQLTransformation",
     "spark_sql": "feast.transformation.spark_transformation.SparkTransformation",
     "spark": "feast.transformation.spark_transformation.SparkTransformation",
+    "ray": "feast.transformation.ray_transformation.RayTransformation",
 }
 
 
diff --git a/sdk/python/feast/transformation/mode.py b/sdk/python/feast/transformation/mode.py
index 2b453477b3a..44d38d8e99c 100644
--- a/sdk/python/feast/transformation/mode.py
+++ b/sdk/python/feast/transformation/mode.py
@@ -6,5 +6,6 @@ class TransformationMode(Enum):
     PANDAS = "pandas"
     SPARK_SQL = "spark_sql"
     SPARK = "spark"
+    RAY = "ray"
     SQL = "sql"
     SUBSTRAIT = "substrait"
diff --git a/sdk/python/feast/transformation/python_transformation.py b/sdk/python/feast/transformation/python_transformation.py
index 2a19b811abe..68e9eee95f6 100644
--- a/sdk/python/feast/transformation/python_transformation.py
+++ b/sdk/python/feast/transformation/python_transformation.py
@@ -155,6 +155,13 @@ def __eq__(self, other):
 
         return True
 
+    def __reduce__(self):
+        """Support for pickle/dill serialization."""
+        return (
+            self.__class__,
+            (self.udf, self.udf_string, self.singleton),
+        )
+
     @classmethod
     def from_proto(cls, user_defined_function_proto: UserDefinedFunctionProto):
         return PythonTransformation(
diff --git a/sdk/python/feast/transformation/ray_transformation.py b/sdk/python/feast/transformation/ray_transformation.py
new file mode 100644
index 00000000000..b592ce8b0d7
--- /dev/null
+++ b/sdk/python/feast/transformation/ray_transformation.py
@@ -0,0 +1,293 @@
+import inspect
+from typing import Any, Callable, Optional, cast, get_type_hints
+
+import dill
+
+from feast.field import Field, from_value_type
+from feast.protos.feast.core.Transformation_pb2 import (
+    UserDefinedFunctionV2 as UserDefinedFunctionProto,
+)
+from feast.transformation.base import Transformation
+from feast.transformation.mode import TransformationMode
+
+
+class RayTransformation(Transformation):
+    """
+    Ray transformation for distributed data processing using Ray Datasets.
+
+    Use this for computationally intensive transformations that benefit from
+    parallel processing, such as:
+    - Embedding generation (e.g., for RAG applications)
+    - Image/video processing
+    - Complex feature engineering
+    - Large-scale data transformations
+
+    Your UDF should accept a Ray Dataset and return a Ray Dataset, enabling
+    native Ray operations and distributed processing across workers.
+
+    Example - Basic transformation:
+        >>> import ray.data
+        >>> def my_ray_udf(ds: ray.data.Dataset) -> ray.data.Dataset:
+        ...     return ds.map_batches(
+        ...         lambda batch: batch,
+        ...         batch_format="pandas"
+        ...     )
+        >>>
+        >>> from feast.transformation.ray_transformation import RayTransformation
+        >>> transform = RayTransformation(
+        ...     udf=my_ray_udf,
+        ...     udf_string="def my_ray_udf(ds): return ds.map_batches(...)"
+        ... )
+
+    Example - Embedding generation with stateful processing:
+        >>> class EmbeddingProcessor:
+        ...     def __init__(self):
+        ...         # Model loaded once per worker (efficient!)
+        ...         from sentence_transformers import SentenceTransformer
+        ...         self.model = SentenceTransformer("all-MiniLM-L6-v2")
+        ...
+        ...     def __call__(self, batch):
+        ...         embeddings = self.model.encode(batch["text"].tolist())
+        ...         batch["embedding"] = embeddings.tolist()
+        ...         return batch
+        >>>
+        >>> def generate_embeddings(ds: ray.data.Dataset) -> ray.data.Dataset:
+        ...     return ds.map_batches(
+        ...         EmbeddingProcessor,
+        ...         batch_format="pandas",
+        ...         concurrency=8  # Use 8 parallel workers
+        ...     )
+
+    Args:
+        udf: Function that takes a Ray Dataset and returns a Ray Dataset
+        udf_string: String representation of the UDF (for serialization)
+        name: Optional name for the transformation
+        tags: Optional metadata tags
+        description: Optional description
+        owner: Optional owner identifier
+
+    Note:
+        For best performance, use stateful classes with `map_batches` to avoid
+        reloading models/resources for each batch. See the embedding example above.
+    """
+
+    def __new__(
+        cls,
+        udf: Optional[Callable[[Any], Any]] = None,
+        udf_string: Optional[str] = None,
+        name: Optional[str] = None,
+        tags: Optional[dict[str, str]] = None,
+        description: str = "",
+        owner: str = "",
+    ) -> "RayTransformation":
+        # Handle Ray deserialization where parameters may not be provided
+        if udf is None and udf_string is None:
+            # Create a bare instance for deserialization
+            instance = object.__new__(cls)
+            return cast("RayTransformation", instance)
+
+        # Ensure required parameters are not None before calling parent constructor
+        if udf is None:
+            raise ValueError("udf parameter cannot be None")
+        if udf_string is None:
+            raise ValueError("udf_string parameter cannot be None")
+
+        return cast(
+            "RayTransformation",
+            super(RayTransformation, cls).__new__(
+                cls,
+                mode=TransformationMode.RAY,
+                udf=udf,
+                name=name,
+                udf_string=udf_string,
+                tags=tags,
+                description=description,
+                owner=owner,
+            ),
+        )
+
+    def __init__(
+        self,
+        udf: Optional[Callable[[Any], Any]] = None,
+        udf_string: Optional[str] = None,
+        name: Optional[str] = None,
+        tags: Optional[dict[str, str]] = None,
+        description: str = "",
+        owner: str = "",
+        *args,
+        **kwargs,
+    ):
+        if udf is None and udf_string is None:
+            return
+        if udf is None:
+            raise ValueError("udf parameter cannot be None")
+        if udf_string is None:
+            raise ValueError("udf_string parameter cannot be None")
+
+        type_hints = get_type_hints(udf)
+        return_annotation = type_hints.get("return", inspect._empty)
+
+        if return_annotation not in (inspect._empty,):
+            return_type_str = str(return_annotation)
+            if "ray.data" not in return_type_str and "Dataset" not in return_type_str:
+                import warnings
+
+                warnings.warn(
+                    f"Return type for RayTransformation should be ray.data.Dataset, got {return_annotation}. "
+                    f"This may cause issues during execution."
+                )
+
+        super().__init__(
+            mode=TransformationMode.RAY,
+            udf=udf,
+            name=name,
+            udf_string=udf_string,
+            tags=tags,
+            description=description,
+            owner=owner,
+        )
+
+    def transform(self, inputs: Any) -> Any:
+        """
+        Apply the transformation to a Ray Dataset.
+
+        This method is called automatically by Feast during materialization.
+        It applies your user-defined function (UDF) to the input data.
+
+        Args:
+            inputs: Ray Dataset containing the input data to transform.
+                   The dataset will have columns matching your source schema.
+
+        Returns:
+            Transformed Ray Dataset with output features. The output schema
+            will be automatically inferred or should match your explicitly
+            defined schema in BatchFeatureView.
+
+        Example:
+            You typically don't call this directly - Feast calls it during:
+            >>> # store.materialize_incremental(end_date)
+
+            But you can test it manually:
+            >>> import ray.data
+            >>> import pandas as pd
+            >>> test_data = ray.data.from_pandas(pd.DataFrame([{"text": "hello"}]))
+            >>> # my_transformation = RayTransformation(udf=my_udf, udf_string="...")
+            >>> # result = my_transformation.transform(test_data)
+            >>> # result.show()
+        """
+        return self.udf(inputs)
+
+    def infer_features(
+        self,
+        random_input: dict[str, list[Any]],
+        *args,
+        **kwargs,
+    ) -> list[Field]:
+        """
+        Infer features from the Ray transformation.
+
+        This method automatically infers the output schema by:
+        1. Creating a Ray Dataset from sample input data
+        2. Applying your transformation UDF
+        3. Extracting the schema from the transformed output
+
+        Args:
+            random_input: Dictionary mapping column names to sample values.
+                         Should contain representative data for your transformation.
+
+        Returns:
+            List of Field objects representing the inferred schema.
+
+        Raises:
+            TypeError: If schema inference fails. In this case, explicitly define
+                      the schema in your BatchFeatureView using the `schema` parameter.
+
+        Example:
+            If your UDF adds an 'embedding' column, this will automatically
+            detect it and infer its type from the output data.
+        """
+        try:
+            import pandas as pd
+            import ray.data
+
+            # Create a Ray Dataset from the sample input
+            df = pd.DataFrame.from_dict(random_input)
+            ds = ray.data.from_pandas([df])
+
+            # Apply the user's transformation
+            output_ds = self.transform(ds)
+
+            # Convert result to pandas to extract schema
+            output_df = output_ds.to_pandas()
+
+            # Infer field types from the output
+            fields = []
+            for feature_name, feature_type in zip(output_df.columns, output_df.dtypes):
+                feature_value = output_df[feature_name].tolist()
+                if len(feature_value) <= 0:
+                    raise TypeError(
+                        f"Cannot infer type for feature '{feature_name}': "
+                        f"UDF returned empty output. Ensure your transformation "
+                        f"returns at least one row of data."
+                    )
+                from feast.type_map import python_type_to_feast_value_type
+
+                fields.append(
+                    Field(
+                        name=feature_name,
+                        dtype=from_value_type(
+                            python_type_to_feast_value_type(
+                                feature_name,
+                                value=feature_value[0],
+                                type_name=str(feature_type),
+                            )
+                        ),
+                    )
+                )
+            return fields
+        except ImportError as e:
+            raise TypeError(
+                f"Failed to import required dependencies for RayTransformation: {e}. "
+                f"Install Ray with: pip install feast[ray]"
+            )
+        except Exception as e:
+            error_msg = (
+                f"Failed to infer features from RayTransformation: {e}\n\n"
+                f"💡 To fix this:\n"
+                f"1. Explicitly define the schema in your BatchFeatureView:\n"
+                f"   BatchFeatureView(\n"
+                f"       schema=[\n"
+                f"           Field(name='your_field', dtype=String),\n"
+                f"           Field(name='embedding', dtype=Array(Float32)),\n"
+                f"       ],\n"
+                f"       ...\n"
+                f"   )\n\n"
+                f"2. Or ensure your UDF returns valid data when called with sample input:\n"
+                f"   - Input sample: {list(random_input.keys())}\n"
+                f"   - Check that your UDF can process this structure\n"
+            )
+            raise TypeError(error_msg)
+
+    def __eq__(self, other):
+        if not isinstance(other, RayTransformation):
+            raise TypeError(
+                "Comparisons should only involve RayTransformation class objects."
+            )
+
+        if (
+            self.udf_string != other.udf_string
+            or self.udf.__code__.co_code != other.udf.__code__.co_code
+        ):
+            return False
+
+        return True
+
+    @classmethod
+    def from_proto(cls, user_defined_function_proto: UserDefinedFunctionProto):
+        return RayTransformation(
+            udf=dill.loads(user_defined_function_proto.body),
+            udf_string=user_defined_function_proto.body_text,
+            name=user_defined_function_proto.name
+            if user_defined_function_proto.name
+            else None,
+        )
diff --git a/sdk/python/feast/type_map.py b/sdk/python/feast/type_map.py
index 9d9921a2bf9..ebf6f0eae19 100644
--- a/sdk/python/feast/type_map.py
+++ b/sdk/python/feast/type_map.py
@@ -172,6 +172,16 @@ def python_type_to_feast_value_type(
     if type_name in type_map:
         return type_map[type_name]
 
+    # Handle pandas "object" dtype by inspecting the actual value
+    if type_name == "object" and value is not None:
+        # Check the actual type of the value
+        actual_type = type(value).__name__.lower()
+        if actual_type == "str":
+            return ValueType.STRING
+        # If it's a different type wrapped in object, try to infer from the value
+        elif actual_type in type_map:
+            return type_map[actual_type]
+
     if isinstance(value, np.ndarray) and str(value.dtype) in type_map:
         item_type = type_map[str(value.dtype)]
         return ValueType[item_type.name + "_LIST"]
diff --git a/sdk/python/feast/ui/package.json b/sdk/python/feast/ui/package.json
index 72029b5c2dd..6b65265755c 100644
--- a/sdk/python/feast/ui/package.json
+++ b/sdk/python/feast/ui/package.json
@@ -6,7 +6,7 @@
     "@elastic/datemath": "^5.0.3",
     "@elastic/eui": "^72.0.0",
     "@emotion/react": "^11.9.0",
-    "@feast-dev/feast-ui": "0.54.0",
+    "@feast-dev/feast-ui": "0.55.0",
     "@testing-library/jest-dom": "^5.16.4",
     "@testing-library/react": "^13.2.0",
     "@testing-library/user-event": "^13.5.0",
diff --git a/sdk/python/feast/ui/yarn.lock b/sdk/python/feast/ui/yarn.lock
index 74db44af9aa..152bf0fb3fd 100644
--- a/sdk/python/feast/ui/yarn.lock
+++ b/sdk/python/feast/ui/yarn.lock
@@ -1575,10 +1575,10 @@
     minimatch "^3.1.2"
     strip-json-comments "^3.1.1"
 
-"@feast-dev/feast-ui@0.54.0":
-  version "0.54.0"
-  resolved "https://registry.yarnpkg.com/@feast-dev/feast-ui/-/feast-ui-0.54.0.tgz#f8d671f0540e84e19dd248803cd24440732f9903"
-  integrity sha512-WFgz75N+Kmt7FNsbPY5hpIZGDfrw0Sdru/7XLoiHtLPASDfUdalfEyCQbknz2f42RwpIVmbM1/eS6VpRcppa3A==
+"@feast-dev/feast-ui@0.55.0":
+  version "0.55.0"
+  resolved "https://registry.yarnpkg.com/@feast-dev/feast-ui/-/feast-ui-0.55.0.tgz#dd90ae8a96fdf3a5da5dd12e1d740c4b78faf0a5"
+  integrity sha512-T+j5ZwPafIsnsUFcSUENh+fR9aKmlfMkJhtKUzKreqg/5bxXRAo0fKIBWkKFSV+KsIAkDCwa8R7V9N5C/eeiKQ==
   dependencies:
     "@elastic/datemath" "^5.0.3"
     "@elastic/eui" "^95.12.0"
diff --git a/sdk/python/feast/ui_server.py b/sdk/python/feast/ui_server.py
index 6883dc1105e..8e201bcf944 100644
--- a/sdk/python/feast/ui_server.py
+++ b/sdk/python/feast/ui_server.py
@@ -4,7 +4,7 @@
 from typing import Callable, Optional
 
 import uvicorn
-from fastapi import FastAPI, Response
+from fastapi import FastAPI, Response, status
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.staticfiles import StaticFiles
 from pydantic import BaseModel
@@ -61,27 +61,66 @@ def shutdown_event():
     with importlib_resources.as_file(ui_dir_ref) as ui_dir:
         # Initialize with the projects-list.json file
         with ui_dir.joinpath("projects-list.json").open(mode="w") as f:
-            projects_dict = {
-                "projects": [
+            # Get all projects from the registry
+            discovered_projects = []
+            registry = store.registry.proto()
+
+            # Use the projects list from the registry
+            if registry and registry.projects and len(registry.projects) > 0:
+                for proj in registry.projects:
+                    if proj.spec and proj.spec.name:
+                        discovered_projects.append(
+                            {
+                                "name": proj.spec.name.replace("_", " ").title(),
+                                "description": proj.spec.description
+                                or f"Project: {proj.spec.name}",
+                                "id": proj.spec.name,
+                                "registryPath": f"{root_path}/registry",
+                            }
+                        )
+            else:
+                # If no projects in registry, use the current project from feature_store.yaml
+                discovered_projects.append(
                     {
                         "name": "Project",
                         "description": "Test project",
                         "id": project_id,
                         "registryPath": f"{root_path}/registry",
                     }
-                ]
-            }
+                )
+
+            # Add "All Projects" option at the beginning if there are multiple projects
+            if len(discovered_projects) > 1:
+                all_projects_entry = {
+                    "name": "All Projects",
+                    "description": "View data across all projects",
+                    "id": "all",
+                    "registryPath": f"{root_path}/registry",
+                }
+                discovered_projects.insert(0, all_projects_entry)
+
+            projects_dict = {"projects": discovered_projects}
             f.write(json.dumps(projects_dict))
 
     @app.get("/registry")
     def read_registry():
         if registry_proto is None:
-            return Response(status_code=503)  # Service Unavailable
+            return Response(
+                status_code=status.HTTP_503_SERVICE_UNAVAILABLE
+            )  # Service Unavailable
         return Response(
             content=registry_proto.SerializeToString(),
             media_type="application/octet-stream",
         )
 
+    @app.get("/health")
+    def health():
+        return (
+            Response(status_code=status.HTTP_200_OK)
+            if registry_proto
+            else Response(status_code=status.HTTP_503_SERVICE_UNAVAILABLE)
+        )
+
     @app.post("/save-document")
     async def save_document_endpoint(request: SaveDocumentRequest):
         try:
diff --git a/sdk/python/feast/utils.py b/sdk/python/feast/utils.py
index 939adbe933f..01ffa774ccd 100644
--- a/sdk/python/feast/utils.py
+++ b/sdk/python/feast/utils.py
@@ -33,6 +33,7 @@
     RequestDataNotFoundInEntityRowsException,
 )
 from feast.field import Field
+from feast.infra.compute_engines.backends.pandas_backend import PandasBackend
 from feast.infra.key_encoding_utils import deserialize_entity_key
 from feast.protos.feast.serving.ServingService_pb2 import (
     FieldStatus,
@@ -561,6 +562,76 @@ def construct_response_feature_vector(
     )
 
 
+def _get_aggregate_operations(agg_specs) -> dict:
+    """
+    Convert Aggregation specs to agg_ops format for PandasBackend.
+
+    Reused from LocalFeatureBuilder logic.
+    TODO: This logic is duplicated from feast.infra.compute_engines.local.feature_builder.LocalFeatureBuilder._get_aggregate_operations().
+    Consider refactoring to a shared utility module in the future.
+    """
+    agg_ops = {}
+    for agg in agg_specs:
+        if agg.time_window is not None:
+            raise ValueError(
+                "Time window aggregation is not supported in online serving."
+            )
+        alias = f"{agg.function}_{agg.column}"
+        agg_ops[alias] = (agg.function, agg.column)
+    return agg_ops
+
+
+def _apply_aggregations_to_response(
+    response_data: Union[pyarrow.Table, Dict[str, List[Any]]],
+    aggregations,
+    group_keys: Optional[List[str]],
+    mode: str,
+) -> Union[pyarrow.Table, Dict[str, List[Any]]]:
+    """
+    Apply aggregations using PandasBackend.
+
+    Args:
+        response_data: Either a pyarrow.Table or dict of lists containing the data
+        aggregations: List of Aggregation objects to apply
+        group_keys: List of column names to group by (optional)
+        mode: Transformation mode ("python", "pandas", or "substrait")
+
+    Returns:
+        Aggregated data in the same format as input
+
+    TODO: Consider refactoring to support backends other than pandas in the future.
+    """
+    if not aggregations:
+        return response_data
+
+    backend = PandasBackend()
+
+    # Convert to pandas DataFrame
+    if isinstance(response_data, dict):
+        df = pd.DataFrame(response_data)
+    else:  # pyarrow.Table
+        df = backend.from_arrow(response_data)
+
+    if df.empty:
+        return response_data
+
+    # Convert aggregations to agg_ops format
+    agg_ops = _get_aggregate_operations(aggregations)
+
+    # Apply aggregations using PandasBackend
+    if group_keys:
+        result_df = backend.groupby_agg(df, group_keys, agg_ops)
+    else:
+        # No grouping - aggregate over entire dataset
+        result_df = backend.groupby_agg(df, [], agg_ops)
+
+    # Convert back to original format
+    if mode == "python":
+        return {col: result_df[col].tolist() for col in result_df.columns}
+    else:  # pandas or substrait
+        return backend.to_arrow(result_df)
+
+
 def _augment_response_with_on_demand_transforms(
     online_features_response: GetOnlineFeaturesResponse,
     feature_refs: List[str],
@@ -605,7 +676,31 @@ def _augment_response_with_on_demand_transforms(
     for odfv_name, _feature_refs in odfv_feature_refs.items():
         odfv = requested_odfv_map[odfv_name]
         if not odfv.write_to_online_store:
-            if odfv.mode == "python":
+            # Apply aggregations if configured.
+            if odfv.aggregations:
+                if odfv.mode == "python":
+                    if initial_response_dict is None:
+                        initial_response_dict = initial_response.to_dict()
+                    initial_response_dict = _apply_aggregations_to_response(
+                        initial_response_dict,
+                        odfv.aggregations,
+                        odfv.entities,
+                        odfv.mode,
+                    )
+                elif odfv.mode in {"pandas", "substrait"}:
+                    if initial_response_arrow is None:
+                        initial_response_arrow = initial_response.to_arrow()
+                    initial_response_arrow = _apply_aggregations_to_response(
+                        initial_response_arrow,
+                        odfv.aggregations,
+                        odfv.entities,
+                        odfv.mode,
+                    )
+
+            # Apply transformation. Note: aggregations and transformation configs are mutually exclusive
+            # TODO: Fix to make it work for having both aggregation and transformation
+            #  ticket: https://github.com/feast-dev/feast/issues/5689
+            elif odfv.mode == "python":
                 if initial_response_dict is None:
                     initial_response_dict = initial_response.to_dict()
                 transformed_features_dict: Dict[str, List[Any]] = odfv.transform_dict(
diff --git a/sdk/python/tests/integration/compute_engines/ray_compute/ray_shared_utils.py b/sdk/python/tests/integration/compute_engines/ray_compute/ray_shared_utils.py
index 9e9aabc4f90..6b28949f401 100644
--- a/sdk/python/tests/integration/compute_engines/ray_compute/ray_shared_utils.py
+++ b/sdk/python/tests/integration/compute_engines/ray_compute/ray_shared_utils.py
@@ -9,10 +9,10 @@
 
 import pandas as pd
 import pytest
-import ray
 
 from feast import Entity, FileSource
 from feast.data_source import DataSource
+from feast.infra.ray_initializer import shutdown_ray
 from feast.utils import _utc_now
 from tests.integration.feature_repos.repo_configuration import (
     construct_test_environment,
@@ -126,8 +126,7 @@ def cleanup_ray_environment(ray_environment):
 
     # Ensure Ray is shut down completely
     try:
-        if ray.is_initialized():
-            ray.shutdown()
+        shutdown_ray()
         time.sleep(0.2)  # Brief pause to ensure clean shutdown
     except Exception as e:
         print(f"Warning: Ray shutdown failed: {e}")
@@ -147,9 +146,8 @@ def create_ray_environment():
 def ray_environment() -> Generator:
     """Pytest fixture to provide a Ray environment for tests with automatic cleanup."""
     try:
-        if ray.is_initialized():
-            ray.shutdown()
-            time.sleep(0.2)
+        shutdown_ray()
+        time.sleep(0.2)
     except Exception:
         pass
 
diff --git a/sdk/python/tests/integration/compute_engines/ray_compute/test_compute.py b/sdk/python/tests/integration/compute_engines/ray_compute/test_compute.py
index e7060b4a756..ef4bfa131da 100644
--- a/sdk/python/tests/integration/compute_engines/ray_compute/test_compute.py
+++ b/sdk/python/tests/integration/compute_engines/ray_compute/test_compute.py
@@ -19,6 +19,7 @@
 from feast.infra.offline_stores.contrib.ray_offline_store.ray import (
     RayOfflineStore,
 )
+from feast.transformation.ray_transformation import RayTransformation
 from feast.types import Float32, Int32, Int64
 from tests.integration.compute_engines.ray_compute.ray_shared_utils import (
     driver,
@@ -162,10 +163,169 @@ def test_ray_compute_engine_config():
         window_size_for_joins="2H",
         max_workers=4,
         enable_optimization=True,
-        execution_timeout_seconds=3600,
     )
 
     assert config.type == "ray.engine"
     assert config.ray_address == "ray://localhost:10001"
     assert config.broadcast_join_threshold_mb == 200
     assert config.window_size_timedelta == timedelta(hours=2)
+
+
+@pytest.mark.integration
+@pytest.mark.xdist_group(name="ray")
+def test_ray_transformation_compute_engine(ray_environment, feature_dataset, entity_df):
+    """Test Ray compute engine with Ray transformation mode."""
+    import ray.data
+
+    fs = ray_environment.feature_store
+    registry = fs.registry
+
+    def ray_transformation_udf(ds: ray.data.Dataset) -> ray.data.Dataset:
+        """Ray native transformation that processes data in parallel."""
+
+        def process_batch(batch: pd.DataFrame) -> pd.DataFrame:
+            # Simulate some computation (e.g., feature engineering)
+            if "conv_rate" in batch.columns:
+                batch["processed_conv_rate"] = batch["conv_rate"] * 2.0
+            if "acc_rate" in batch.columns:
+                batch["processed_acc_rate"] = batch["acc_rate"] * 1.5
+            return batch
+
+        return ds.map_batches(
+            process_batch,
+            batch_format="pandas",
+            concurrency=2,  # Use 2 parallel workers
+        )
+
+    # Create Ray transformation
+    ray_transform = RayTransformation(
+        udf=ray_transformation_udf,
+        udf_string="def ray_transformation_udf(ds): return ds.map_batches(...)",
+    )
+
+    driver_stats_fv = BatchFeatureView(
+        name="driver_hourly_stats_ray",
+        entities=[driver],
+        mode="ray",  # Use Ray transformation mode
+        feature_transformation=ray_transform,
+        ttl=timedelta(days=3),
+        schema=[
+            Field(name="conv_rate", dtype=Float32),
+            Field(name="acc_rate", dtype=Float32),
+            Field(name="processed_conv_rate", dtype=Float32),
+            Field(name="processed_acc_rate", dtype=Float32),
+            Field(name="avg_daily_trips", dtype=Int64),
+            Field(name="driver_id", dtype=Int32),
+        ],
+        online=False,
+        offline=False,
+        source=feature_dataset,
+    )
+
+    fs.apply([driver, driver_stats_fv])
+
+    # Build retrieval task
+    task = HistoricalRetrievalTask(
+        project=ray_environment.project,
+        entity_df=entity_df,
+        feature_view=driver_stats_fv,
+        full_feature_name=False,
+        registry=registry,
+    )
+    engine = RayComputeEngine(
+        repo_config=ray_environment.config,
+        offline_store=RayOfflineStore(),
+        online_store=MagicMock(),
+    )
+
+    ray_dag_retrieval_job = engine.get_historical_features(registry, task)
+    ray_dataset = cast(RayDAGRetrievalJob, ray_dag_retrieval_job).to_ray_dataset()
+    df_out = ray_dataset.to_pandas().sort_values("driver_id")
+
+    # Verify the transformation was applied
+    assert df_out.driver_id.to_list() == [1001, 1002]
+
+    # Check that original columns are present
+    assert "conv_rate" in df_out.columns
+    assert "acc_rate" in df_out.columns
+
+    # Check that transformed columns are present
+    assert "processed_conv_rate" in df_out.columns
+    assert "processed_acc_rate" in df_out.columns
+
+    # Verify the transformation logic was applied
+    for idx, row in df_out.iterrows():
+        assert abs(row["processed_conv_rate"] - row["conv_rate"] * 2.0) < 1e-6
+        assert abs(row["processed_acc_rate"] - row["acc_rate"] * 1.5) < 1e-6
+
+
+@pytest.mark.integration
+@pytest.mark.xdist_group(name="ray")
+def test_ray_transformation_materialization(ray_environment, feature_dataset):
+    """Test Ray transformation during materialization."""
+    import ray.data
+
+    fs = ray_environment.feature_store
+    registry = fs.registry
+
+    def ray_embedding_udf(ds: ray.data.Dataset) -> ray.data.Dataset:
+        """Simulate embedding generation with Ray native processing."""
+
+        def generate_embeddings(batch: pd.DataFrame) -> pd.DataFrame:
+            # Simulate embedding generation
+            if "conv_rate" in batch.columns:
+                # Create a simple embedding based on conv_rate
+                batch["embedding"] = batch["conv_rate"].apply(
+                    lambda x: [x * 0.1, x * 0.2, x * 0.3]
+                )
+            return batch
+
+        return ds.map_batches(generate_embeddings, batch_format="pandas", concurrency=2)
+
+    # Create Ray transformation for embeddings
+    ray_embedding_transform = RayTransformation(
+        udf=ray_embedding_udf,
+        udf_string="def ray_embedding_udf(ds): return ds.map_batches(...)",
+    )
+
+    driver_embeddings_fv = BatchFeatureView(
+        name="driver_embeddings",
+        entities=[driver],
+        mode="ray",
+        feature_transformation=ray_embedding_transform,
+        ttl=timedelta(days=3),
+        schema=[
+            Field(name="conv_rate", dtype=Float32),
+            Field(
+                name="embedding", dtype=Float32
+            ),  # This would be Array(Float32) in real usage
+            Field(name="driver_id", dtype=Int32),
+        ],
+        online=True,
+        offline=False,
+        source=feature_dataset,
+    )
+
+    def tqdm_builder(length):
+        return tqdm(length, ncols=100)
+
+    fs.apply([driver, driver_embeddings_fv])
+
+    task = MaterializationTask(
+        project=ray_environment.project,
+        feature_view=driver_embeddings_fv,
+        start_time=now - timedelta(days=2),
+        end_time=now,
+        tqdm_builder=tqdm_builder,
+    )
+
+    engine = RayComputeEngine(
+        repo_config=ray_environment.config,
+        offline_store=RayOfflineStore(),
+        online_store=MagicMock(),
+    )
+
+    ray_materialize_jobs = engine.materialize(registry, task)
+
+    assert len(ray_materialize_jobs) == 1
+    assert ray_materialize_jobs[0].status() == MaterializationJobStatus.SUCCEEDED
diff --git a/sdk/python/tests/integration/registration/test_universal_registry.py b/sdk/python/tests/integration/registration/test_universal_registry.py
index eb663d8565a..29b31ef1b75 100644
--- a/sdk/python/tests/integration/registration/test_universal_registry.py
+++ b/sdk/python/tests/integration/registration/test_universal_registry.py
@@ -22,8 +22,12 @@
 
 import grpc_testing
 import pandas as pd
+import pyarrow.fs as fs
 import pytest
 from pytest_lazyfixture import lazy_fixture
+from testcontainers.core.container import DockerContainer
+from testcontainers.core.network import Network
+from testcontainers.core.waiting_utils import wait_for_logs
 from testcontainers.mysql import MySqlContainer
 from testcontainers.postgres import PostgresContainer
 
@@ -280,6 +284,60 @@ def sqlite_registry():
     yield SqlRegistry(registry_config, "project", None)
 
 
+@pytest.fixture(scope="function")
+def hdfs_registry():
+    HADOOP_NAMENODE_IMAGE = "bde2020/hadoop-namenode:2.0.0-hadoop3.2.1-java8"
+    HADOOP_DATANODE_IMAGE = "bde2020/hadoop-datanode:2.0.0-hadoop3.2.1-java8"
+    HDFS_CLUSTER_NAME = "feast-hdfs-cluster"
+    HADOOP_NAMENODE_WAIT_LOG = "namenode.NameNode: NameNode RPC up"
+    HADOOP_DATANODE_WAIT_LOG = "datanode.DataNode: .*successfully registered with NN"
+    with Network() as network:
+        namenode = None
+        datanode = None
+
+        try:
+            namenode = (
+                DockerContainer(HADOOP_NAMENODE_IMAGE)
+                .with_network(network)
+                .with_env("CLUSTER_NAME", HDFS_CLUSTER_NAME)
+                .with_exposed_ports(8020)
+                .with_network_aliases("namenode")
+                .with_kwargs(hostname="namenode")
+                .start()
+            )
+            wait_for_logs(namenode, HADOOP_NAMENODE_WAIT_LOG, timeout=120)
+            namenode_ip = namenode.get_container_host_ip()
+            namenode_port = int(namenode.get_exposed_port(8020))
+
+            datanode = (
+                DockerContainer(HADOOP_DATANODE_IMAGE)
+                .with_network(network)
+                .with_exposed_ports(9867)
+                .with_env("CLUSTER_NAME", HDFS_CLUSTER_NAME)
+                .with_env("CORE_CONF_fs_defaultFS", "hdfs://namenode:8020")
+                .with_network_aliases("datanode")
+                .with_kwargs(hostname="datanode")
+                .start()
+            )
+
+            wait_for_logs(datanode, HADOOP_DATANODE_WAIT_LOG, timeout=120)
+
+            hdfs = fs.HadoopFileSystem(host=namenode_ip, port=namenode_port)
+            hdfs.create_dir("/feast")
+            registry_path = f"hdfs://{namenode_ip}:{namenode_port}/feast/registry.db"
+            with hdfs.open_output_stream(registry_path) as f:
+                f.write(b"")
+
+            registry_config = RegistryConfig(path=registry_path, cache_ttl_seconds=600)
+            reg = Registry("project", registry_config, None)
+            yield reg
+        finally:
+            if datanode:
+                datanode.stop()
+            if namenode:
+                namenode.stop()
+
+
 class GrpcMockChannel:
     def __init__(self, service, servicer):
         self.service = service
@@ -350,6 +408,10 @@ def mock_remote_registry():
             lazy_fixture("mock_remote_registry"),
             marks=pytest.mark.rbac_remote_integration_test,
         ),
+        pytest.param(
+            lazy_fixture("hdfs_registry"),
+            marks=pytest.mark.xdist_group(name="hdfs_registry"),
+        ),
     ]
 
 sql_fixtures = [
diff --git a/sdk/python/tests/integration/registration/test_universal_types.py b/sdk/python/tests/integration/registration/test_universal_types.py
index 5ba99b9d7f1..b464cf2f766 100644
--- a/sdk/python/tests/integration/registration/test_universal_types.py
+++ b/sdk/python/tests/integration/registration/test_universal_types.py
@@ -343,7 +343,6 @@ def offline_types_test_fixtures(request, environment):
     if (
         environment.data_source_creator.__class__.__name__
         == "ClickhouseDataSourceCreator"
-        and config.feature_dtype in {"float", "datetime", "bool"}
         and config.feature_is_list
         and not config.has_empty_list
     ):
diff --git a/sdk/python/tests/unit/api/test_api_rest_registry.py b/sdk/python/tests/unit/api/test_api_rest_registry.py
index 8d7a939c583..12e22737f93 100644
--- a/sdk/python/tests/unit/api/test_api_rest_registry.py
+++ b/sdk/python/tests/unit/api/test_api_rest_registry.py
@@ -1528,6 +1528,90 @@ def test_metrics_resource_counts_via_rest(fastapi_test_app):
     assert isinstance(per_project["demo_project"], dict)
 
 
+def test_feature_views_all_types_and_resource_counts_match(fastapi_test_app):
+    """
+    Test that verifies:
+    1. All types of feature views (regular, on-demand, stream) are returned in /feature_views/all
+    2. The count from /metrics/resource_counts matches the count from /feature_views/all
+    """
+    response_all = fastapi_test_app.get("/feature_views/all")
+    assert response_all.status_code == 200
+    data_all = response_all.json()
+    assert "featureViews" in data_all
+
+    feature_views = data_all["featureViews"]
+
+    # Count should include at least:
+    # - 3 regular feature views: user_profile, user_behavior, user_preferences
+    # - 1 on-demand feature view: test_on_demand_feature_view
+    assert len(feature_views) >= 4, (
+        f"Expected at least 4 feature views, got {len(feature_views)}"
+    )
+
+    # Verify we have different types of feature views
+    feature_view_names = {fv["spec"]["name"] for fv in feature_views}
+
+    # Check for regular feature views
+    assert "user_profile" in feature_view_names, (
+        "Regular feature view 'user_profile' not found"
+    )
+    assert "user_behavior" in feature_view_names, (
+        "Regular feature view 'user_behavior' not found"
+    )
+    assert "user_preferences" in feature_view_names, (
+        "Regular feature view 'user_preferences' not found"
+    )
+
+    # Check for on-demand feature view
+    assert "test_on_demand_feature_view" in feature_view_names, (
+        "On-demand feature view 'test_on_demand_feature_view' not found"
+    )
+
+    # Verify all have the correct project
+    for fv in feature_views:
+        assert fv["project"] == "demo_project", (
+            f"Feature view has incorrect project: {fv.get('project')}"
+        )
+
+    # Now get resource counts from /metrics/resource_counts endpoint
+    response_metrics = fastapi_test_app.get(
+        "/metrics/resource_counts?project=demo_project"
+    )
+    assert response_metrics.status_code == 200
+    data_metrics = response_metrics.json()
+    assert "counts" in data_metrics
+
+    counts = data_metrics["counts"]
+    assert "featureViews" in counts
+
+    # Verify that the count from metrics matches the count from feature_views/all
+    feature_views_count_from_all = len(feature_views)
+    feature_views_count_from_metrics = counts["featureViews"]
+
+    assert feature_views_count_from_all == feature_views_count_from_metrics, (
+        f"Feature views count mismatch: /feature_views/all returned {feature_views_count_from_all} "
+        f"but /metrics/resource_counts returned {feature_views_count_from_metrics}"
+    )
+
+    # Test without project parameter (all projects)
+    response_all_projects = fastapi_test_app.get("/feature_views/all")
+    assert response_all_projects.status_code == 200
+    data_all_projects = response_all_projects.json()
+
+    response_metrics_all = fastapi_test_app.get("/metrics/resource_counts")
+    assert response_metrics_all.status_code == 200
+    data_metrics_all = response_metrics_all.json()
+
+    total_fv_count_from_all = len(data_all_projects["featureViews"])
+    total_fv_count_from_metrics = data_metrics_all["total"]["featureViews"]
+
+    assert total_fv_count_from_all == total_fv_count_from_metrics, (
+        f"Total feature views count mismatch across all projects: "
+        f"/feature_views/all returned {total_fv_count_from_all} "
+        f"but /metrics/resource_counts returned {total_fv_count_from_metrics}"
+    )
+
+
 def test_metrics_recently_visited_via_rest(fastapi_test_app):
     """Test the /metrics/recently_visited endpoint."""
     # First, make some requests to generate visit data
diff --git a/sdk/python/tests/unit/infra/compute_engines/local/test_nodes.py b/sdk/python/tests/unit/infra/compute_engines/local/test_nodes.py
index 20e23c35e03..905ea65ae42 100644
--- a/sdk/python/tests/unit/infra/compute_engines/local/test_nodes.py
+++ b/sdk/python/tests/unit/infra/compute_engines/local/test_nodes.py
@@ -4,9 +4,9 @@
 import pandas as pd
 import pyarrow as pa
 
+from feast.infra.compute_engines.backends.pandas_backend import PandasBackend
 from feast.infra.compute_engines.dag.context import ColumnInfo, ExecutionContext
 from feast.infra.compute_engines.local.arrow_table_value import ArrowTableValue
-from feast.infra.compute_engines.local.backends.pandas_backend import PandasBackend
 from feast.infra.compute_engines.local.nodes import (
     LocalAggregationNode,
     LocalDedupNode,
diff --git a/sdk/python/tests/unit/infra/compute_engines/ray_compute/test_nodes.py b/sdk/python/tests/unit/infra/compute_engines/ray_compute/test_nodes.py
index e8c40d43099..0da4fcb956e 100644
--- a/sdk/python/tests/unit/infra/compute_engines/ray_compute/test_nodes.py
+++ b/sdk/python/tests/unit/infra/compute_engines/ray_compute/test_nodes.py
@@ -1,4 +1,6 @@
+import os
 from datetime import datetime, timedelta
+from unittest.mock import patch
 
 import pandas as pd
 import pytest
@@ -18,6 +20,12 @@
     RayReadNode,
     RayTransformationNode,
 )
+from feast.infra.ray_initializer import (
+    RayConfigManager,
+    RayExecutionMode,
+    ensure_ray_initialized,
+    get_ray_wrapper,
+)
 
 
 class DummyInputNode(DAGNode):
@@ -317,3 +325,101 @@ def test_ray_config_validation():
     # Test invalid window size defaults to 1 hour
     config_invalid = RayComputeEngineConfig(window_size_for_joins="invalid")
     assert config_invalid.window_size_timedelta == timedelta(hours=1)
+
+
+def test_ray_initialization_and_kuberay_modes():
+    """
+    Comprehensive test for Ray initialization modes and KubeRay configuration.
+
+    Tests: Mode detection (LOCAL/REMOTE/KUBERAY), config parsing, defaults,
+    environment variables, mode precedence, and Ray wrapper instantiation.
+    """
+    # Test LOCAL mode (default)
+    config_local = RayComputeEngineConfig()
+    assert (
+        RayConfigManager(config_local).determine_execution_mode()
+        == RayExecutionMode.LOCAL
+    )
+
+    # Test REMOTE mode
+    config_remote = RayComputeEngineConfig(ray_address="ray://localhost:10001")
+    manager_remote = RayConfigManager(config_remote)
+    assert manager_remote.determine_execution_mode() == RayExecutionMode.REMOTE
+    # Test execution mode caching
+    assert manager_remote.determine_execution_mode() == RayExecutionMode.REMOTE
+
+    # Test KUBERAY mode with full config
+    config_kuberay = RayComputeEngineConfig(
+        use_kuberay=True,
+        kuberay_conf={
+            "cluster_name": "feast-cluster",
+            "namespace": "feast-system",
+            "auth_token": "test-token",
+            "auth_server": "https://api.example.com",
+            "skip_tls": True,
+        },
+    )
+    manager_kuberay = RayConfigManager(config_kuberay)
+    assert manager_kuberay.determine_execution_mode() == RayExecutionMode.KUBERAY
+    kuberay_config = manager_kuberay.get_kuberay_config()
+    assert kuberay_config["cluster_name"] == "feast-cluster"
+    assert kuberay_config["namespace"] == "feast-system"
+    assert kuberay_config["auth_token"] == "test-token"
+    assert kuberay_config["skip_tls"] is True
+
+    # Test KubeRay defaults
+    config_defaults = RayComputeEngineConfig(
+        use_kuberay=True, kuberay_conf={"cluster_name": "test-cluster"}
+    )
+    defaults_config = RayConfigManager(config_defaults).get_kuberay_config()
+    assert defaults_config["namespace"] == "default"
+    assert defaults_config["skip_tls"] is False
+
+    # Test mode precedence - KUBERAY overrides REMOTE
+    config_precedence = RayComputeEngineConfig(
+        ray_address="ray://localhost:10001",
+        use_kuberay=True,
+        kuberay_conf={"cluster_name": "test-cluster"},
+    )
+    assert (
+        RayConfigManager(config_precedence).determine_execution_mode()
+        == RayExecutionMode.KUBERAY
+    )
+
+    # Test environment variable support
+    with patch.dict(
+        os.environ,
+        {
+            "FEAST_RAY_CLUSTER_NAME": "env-cluster",
+            "FEAST_RAY_NAMESPACE": "env-namespace",
+            "FEAST_RAY_AUTH_TOKEN": "env-token",
+        },
+    ):
+        env_config = RayConfigManager(
+            RayComputeEngineConfig(use_kuberay=True, kuberay_conf={})
+        ).get_kuberay_config()
+        assert env_config["cluster_name"] == "env-cluster"
+        assert env_config["namespace"] == "env-namespace"
+        assert env_config["auth_token"] == "env-token"
+
+    # Test Ray wrapper instantiation
+    from feast.infra.ray_initializer import StandardRayWrapper
+
+    wrapper = get_ray_wrapper()
+    assert isinstance(wrapper, StandardRayWrapper)
+
+    config_custom = RayComputeEngineConfig(
+        enable_ray_logging=True,
+        max_workers=4,
+        broadcast_join_threshold_mb=200,
+        ray_conf={"num_cpus": 4},
+    )
+    assert config_custom.enable_ray_logging is True
+    assert config_custom.max_workers == 4
+    assert config_custom.broadcast_join_threshold_mb == 200
+    assert config_custom.ray_conf["num_cpus"] == 4
+
+    with patch("feast.infra.ray_initializer.ray") as mock_ray:
+        mock_ray.is_initialized.return_value = True
+        ensure_ray_initialized(config_local)
+        mock_ray.init.assert_not_called()
diff --git a/sdk/python/tests/unit/infra/test_inference_unit_tests.py b/sdk/python/tests/unit/infra/test_inference_unit_tests.py
index f1aef20d113..d0df8153c73 100644
--- a/sdk/python/tests/unit/infra/test_inference_unit_tests.py
+++ b/sdk/python/tests/unit/infra/test_inference_unit_tests.py
@@ -96,14 +96,6 @@ def python_native_test_view(input_dict: dict[str, Any]) -> dict[str, Any]:
 
     python_native_test_view.infer_features()
 
-
-def test_on_demand_features_invalid_type_inference():
-    # Create Feature Views
-    date_request = RequestSource(
-        name="date_request",
-        schema=[Field(name="some_date", dtype=UnixTimestamp)],
-    )
-
     @on_demand_feature_view(
         sources=[date_request],
         schema=[
@@ -111,14 +103,20 @@ def test_on_demand_features_invalid_type_inference():
             Field(name="object_output", dtype=String),
         ],
     )
-    def invalid_test_view(features_df: pd.DataFrame) -> pd.DataFrame:
+    def object_string_test_view(features_df: pd.DataFrame) -> pd.DataFrame:
         data = pd.DataFrame()
         data["output"] = features_df["some_date"]
         data["object_output"] = features_df["some_date"].astype(str)
         return data
 
-    with pytest.raises(ValueError, match="Value with native type object"):
-        invalid_test_view.infer_features()
+    object_string_test_view.infer_features()
+
+
+def test_on_demand_features_invalid_type_inference():
+    date_request = RequestSource(
+        name="date_request",
+        schema=[Field(name="some_date", dtype=UnixTimestamp)],
+    )
 
     @on_demand_feature_view(
         schema=[
@@ -184,14 +182,13 @@ def test_view(features_df: pd.DataFrame) -> pd.DataFrame:
             Field(name="object_output", dtype=String),
         ],
     )
-    def invalid_test_view(features_df: pd.DataFrame) -> pd.DataFrame:
+    def object_string_view(features_df: pd.DataFrame) -> pd.DataFrame:
         data = pd.DataFrame()
         data["output"] = features_df["some_date"]
         data["object_output"] = features_df["some_date"].astype(str)
         return data
 
-    with pytest.raises(ValueError, match="Value with native type object"):
-        invalid_test_view.infer_features()
+    object_string_view.infer_features()
 
     @on_demand_feature_view(
         sources=[date_request],
diff --git a/sdk/python/tests/unit/local_feast_tests/test_local_feature_store.py b/sdk/python/tests/unit/local_feast_tests/test_local_feature_store.py
index 397ca72e90d..cbb9d3d334a 100644
--- a/sdk/python/tests/unit/local_feast_tests/test_local_feature_store.py
+++ b/sdk/python/tests/unit/local_feast_tests/test_local_feature_store.py
@@ -1,5 +1,6 @@
 from datetime import datetime, timedelta
 from tempfile import mkstemp
+from unittest.mock import patch
 
 import pytest
 from pytest_lazyfixture import lazy_fixture
@@ -18,7 +19,7 @@
 from feast.permissions.action import AuthzedAction
 from feast.permissions.permission import Permission
 from feast.permissions.policy import RoleBasedPolicy
-from feast.repo_config import RepoConfig
+from feast.repo_config import RegistryConfig, RepoConfig
 from feast.stream_feature_view import stream_feature_view
 from feast.types import Array, Bytes, Float32, Int64, String, ValueType, from_value_type
 from tests.integration.feature_repos.universal.feature_views import TAGS
@@ -797,3 +798,67 @@ def feature_store_with_local_registry():
             entity_key_serialization_version=3,
         )
     )
+
+
+@pytest.mark.parametrize(
+    "test_feature_store",
+    [lazy_fixture("feature_store_with_local_registry")],
+)
+def test_apply_refreshes_registry_cache_sync_mode(test_feature_store):
+    """Test that apply() refreshes registry cache when cache_mode is 'sync' (default)"""
+    # Create a simple entity (no FeatureView to avoid file path issues)
+    entity = Entity(name="test_entity", join_keys=["id"])
+
+    # Mock the refresh_registry method to verify it's called
+    with patch.object(test_feature_store, "refresh_registry") as mock_refresh:
+        # Apply the entity
+        test_feature_store.apply([entity])
+
+        # Verify refresh_registry was called once (due to sync mode)
+        mock_refresh.assert_called_once()
+
+    test_feature_store.teardown()
+
+
+@pytest.mark.parametrize(
+    "test_feature_store",
+    [lazy_fixture("feature_store_with_local_registry")],
+)
+def test_apply_skips_refresh_registry_cache_thread_mode(test_feature_store):
+    """Test that apply() skips registry refresh when cache_mode is 'thread'"""
+    # Create a simple entity
+    entity = Entity(name="test_entity", join_keys=["id"])
+
+    # Temporarily change cache_mode to 'thread'
+    original_cache_mode = test_feature_store.config.registry.cache_mode
+    test_feature_store.config.registry.cache_mode = "thread"
+
+    try:
+        # Mock the refresh_registry method to verify it's NOT called
+        with patch.object(test_feature_store, "refresh_registry") as mock_refresh:
+            # Apply the entity
+            test_feature_store.apply([entity])
+
+            # Verify refresh_registry was NOT called (due to thread mode)
+            mock_refresh.assert_not_called()
+    finally:
+        # Restore original cache_mode
+        test_feature_store.config.registry.cache_mode = original_cache_mode
+
+    test_feature_store.teardown()
+
+
+def test_registry_config_cache_mode_default():
+    """Test that RegistryConfig has cache_mode with default value 'sync'"""
+    config = RegistryConfig()
+    assert hasattr(config, "cache_mode")
+    assert config.cache_mode == "sync"
+
+
+def test_registry_config_cache_mode_can_be_set():
+    """Test that RegistryConfig cache_mode can be set to different values"""
+    config = RegistryConfig(cache_mode="thread")
+    assert config.cache_mode == "thread"
+
+    config = RegistryConfig(cache_mode="sync")
+    assert config.cache_mode == "sync"
diff --git a/sdk/python/tests/unit/test_feature_server_async.py b/sdk/python/tests/unit/test_feature_server_async.py
new file mode 100644
index 00000000000..641a3c53278
--- /dev/null
+++ b/sdk/python/tests/unit/test_feature_server_async.py
@@ -0,0 +1,28 @@
+from unittest.mock import AsyncMock, MagicMock
+
+from fastapi.testclient import TestClient
+
+from feast.feature_server import get_app
+from feast.online_response import OnlineResponse
+from feast.protos.feast.serving.ServingService_pb2 import GetOnlineFeaturesResponse
+
+
+def test_async_get_online_features():
+    """Test that async get_online_features endpoint works correctly"""
+    fs = MagicMock()
+    fs._get_provider.return_value.async_supported.online.read = True
+    fs.get_online_features_async = AsyncMock(
+        return_value=OnlineResponse(GetOnlineFeaturesResponse())
+    )
+    fs.get_feature_service = MagicMock()
+    fs.initialize = AsyncMock()
+    fs.close = AsyncMock()
+
+    client = TestClient(get_app(fs))
+    response = client.post(
+        "/get-online-features",
+        json={"features": ["test:feature"], "entities": {"entity_id": [123]}},
+    )
+
+    assert response.status_code == 200
+    assert fs.get_online_features_async.await_count == 1
diff --git a/sdk/python/tests/unit/test_feature_views.py b/sdk/python/tests/unit/test_feature_views.py
index db058ed68cf..9030e6e0c69 100644
--- a/sdk/python/tests/unit/test_feature_views.py
+++ b/sdk/python/tests/unit/test_feature_views.py
@@ -390,3 +390,143 @@ def transform_udf(df: pd.DataFrame) -> pd.DataFrame:
     assert isinstance(second_deserialized, BatchFeatureView)
     assert second_deserialized.name == original_bfv.name
     assert second_deserialized.feature_transformation is not None
+
+
+def test_transformation_mode_serialization():
+    """
+    Test that transformation mode is properly serialized to proto and deserialized back.
+    This verifies the fix for the mode field in Transformation.proto.
+    """
+    from feast.transformation.mode import TransformationMode
+    from feast.transformation.pandas_transformation import PandasTransformation
+    from feast.transformation.python_transformation import PythonTransformation
+
+    def simple_udf(df: pd.DataFrame) -> pd.DataFrame:
+        df["output"] = df["input"] * 2
+        return df
+
+    file_source = FileSource(
+        name="test-source",
+        path="test_data.parquet",
+        timestamp_field="event_timestamp",
+    )
+
+    entity = Entity(name="test_entity", join_keys=["entity_id"])
+
+    # Test different transformation modes
+    test_cases = [
+        ("python", TransformationMode.PYTHON, PythonTransformation),
+        ("pandas", TransformationMode.PANDAS, PandasTransformation),
+    ]
+
+    for mode_str, mode_enum, transformation_class in test_cases:
+        # Create BatchFeatureView with the transformation
+        bfv = BatchFeatureView(
+            name=f"test_bfv_{mode_str}",
+            entities=[entity],
+            schema=[
+                Field(name="entity_id", dtype=String),
+                Field(name="input", dtype=Int64),
+                Field(name="output", dtype=Int64),
+            ],
+            source=file_source,
+            ttl=timedelta(days=1),
+            mode=mode_str,
+            udf=simple_udf,
+        )
+
+        # Serialize to proto
+        proto = bfv.to_proto()
+
+        # Verify mode is in the proto
+        assert proto.spec.HasField("feature_transformation")
+        assert proto.spec.feature_transformation.HasField("user_defined_function")
+        udf_proto = proto.spec.feature_transformation.user_defined_function
+        assert udf_proto.mode == mode_str, (
+            f"Expected mode '{mode_str}' in proto, got '{udf_proto.mode}'"
+        )
+
+        # Deserialize from proto
+        deserialized = FeatureView.from_proto(proto)
+
+        # Verify mode is preserved
+        assert isinstance(deserialized, BatchFeatureView)
+        # Mode can be either string or enum, so compare values
+        deserialized_mode_str = (
+            deserialized.mode.value
+            if isinstance(deserialized.mode, TransformationMode)
+            else deserialized.mode
+        )
+        assert deserialized_mode_str == mode_str, (
+            f"Expected mode '{mode_str}' after deserialization, got '{deserialized_mode_str}'"
+        )
+        assert deserialized.feature_transformation is not None
+        assert deserialized.feature_transformation.mode == mode_enum, (
+            f"Expected transformation mode {mode_enum} after deserialization, "
+            f"got {deserialized.feature_transformation.mode}"
+        )
+
+
+def test_mode_serialization_without_transformation():
+    """
+    Test that mode is properly serialized in FeatureViewSpec proto.
+    This tests the scenario where mode is set on the FeatureView level,
+    ensuring it's stored in the proto independently of the transformation.
+    """
+    from feast.transformation.mode import TransformationMode
+
+    def simple_udf(df: pd.DataFrame) -> pd.DataFrame:
+        df["output"] = df["feature1"] * 2
+        return df
+
+    file_source = FileSource(
+        name="test-source",
+        path="test_data.parquet",
+        timestamp_field="event_timestamp",
+    )
+
+    entity = Entity(name="test_entity", join_keys=["entity_id"])
+
+    test_modes = ["python", "pandas"]
+
+    for mode_str in test_modes:
+        bfv = BatchFeatureView(
+            name=f"test_bfv_mode_in_spec_{mode_str}",
+            entities=[entity],
+            schema=[
+                Field(name="entity_id", dtype=String),
+                Field(name="feature1", dtype=Int64),
+                Field(name="output", dtype=Int64),
+            ],
+            source=file_source,
+            ttl=timedelta(days=1),
+            mode=mode_str,
+            udf=simple_udf,
+        )
+
+        assert bfv.mode == mode_str
+        proto = bfv.to_proto()
+        assert proto.spec.mode == mode_str, (
+            f"Expected mode '{mode_str}' in FeatureViewSpec proto, got '{proto.spec.mode}'"
+        )
+        deserialized = FeatureView.from_proto(proto)
+        assert isinstance(deserialized, FeatureView)
+
+        # With UDF, should deserialize as BatchFeatureView
+        assert isinstance(deserialized, BatchFeatureView), (
+            f"Expected BatchFeatureView, got {type(deserialized).__name__}"
+        )
+
+        # Verify mode is preserved from FeatureViewSpec proto
+        deserialized_mode_str = (
+            deserialized.mode.value
+            if isinstance(deserialized.mode, TransformationMode)
+            else deserialized.mode
+        )
+        assert deserialized_mode_str == mode_str, (
+            f"Expected mode '{mode_str}' after deserialization, got '{deserialized_mode_str}'"
+        )
+
+        assert deserialized.feature_transformation is not None, (
+            "Expected transformation to be present"
+        )
diff --git a/sdk/python/tests/unit/test_on_demand_feature_view_aggregation.py b/sdk/python/tests/unit/test_on_demand_feature_view_aggregation.py
new file mode 100644
index 00000000000..3d6199be3a0
--- /dev/null
+++ b/sdk/python/tests/unit/test_on_demand_feature_view_aggregation.py
@@ -0,0 +1,89 @@
+# Copyright 2025 The Feast Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Tests for OnDemandFeatureView aggregations in online serving."""
+
+import pyarrow as pa
+
+from feast.aggregation import Aggregation
+from feast.utils import _apply_aggregations_to_response
+
+
+def test_aggregation_python_mode():
+    """Test aggregations in Python mode (dict format)."""
+    data = {
+        "driver_id": [1, 1, 2, 2],
+        "trips": [10, 20, 15, 25],
+    }
+    aggs = [Aggregation(column="trips", function="sum")]
+
+    result = _apply_aggregations_to_response(data, aggs, ["driver_id"], "python")
+
+    assert result == {"driver_id": [1, 2], "sum_trips": [30, 40]}
+
+
+def test_aggregation_pandas_mode():
+    """Test aggregations in Pandas mode (Arrow table format)."""
+    table = pa.table(
+        {
+            "driver_id": [1, 1, 2, 2],
+            "trips": [10, 20, 15, 25],
+        }
+    )
+    aggs = [Aggregation(column="trips", function="sum")]
+
+    result = _apply_aggregations_to_response(table, aggs, ["driver_id"], "pandas")
+
+    assert isinstance(result, pa.Table)
+    result_df = result.to_pandas()
+    assert list(result_df["driver_id"]) == [1, 2]
+    assert list(result_df["sum_trips"]) == [30, 40]
+
+
+def test_multiple_aggregations():
+    """Test multiple aggregation functions."""
+    data = {
+        "driver_id": [1, 1, 2, 2],
+        "trips": [10, 20, 15, 25],
+        "revenue": [100.0, 200.0, 150.0, 250.0],
+    }
+    aggs = [
+        Aggregation(column="trips", function="sum"),
+        Aggregation(column="revenue", function="mean"),
+    ]
+
+    result = _apply_aggregations_to_response(data, aggs, ["driver_id"], "python")
+
+    assert result["driver_id"] == [1, 2]
+    assert result["sum_trips"] == [30, 40]
+    assert result["mean_revenue"] == [150.0, 200.0]
+
+
+def test_no_aggregations_returns_original():
+    """Test that no aggregations returns original data."""
+    data = {"driver_id": [1, 2], "trips": [10, 20]}
+
+    result = _apply_aggregations_to_response(data, [], ["driver_id"], "python")
+
+    assert result == data
+
+
+def test_empty_data_returns_empty():
+    """Test that empty data returns empty result."""
+    data = {"driver_id": [], "trips": []}
+    aggs = [Aggregation(column="trips", function="sum")]
+
+    result = _apply_aggregations_to_response(data, aggs, ["driver_id"], "python")
+
+    assert result == data
diff --git a/sdk/python/tests/unit/test_ui_server.py b/sdk/python/tests/unit/test_ui_server.py
new file mode 100644
index 00000000000..c5a85a85382
--- /dev/null
+++ b/sdk/python/tests/unit/test_ui_server.py
@@ -0,0 +1,297 @@
+import contextlib
+import json
+import os
+import tempfile
+from pathlib import Path
+from unittest.mock import MagicMock, patch
+
+import assertpy
+import pytest
+from fastapi.testclient import TestClient
+
+from feast.ui_server import get_app
+
+# Test constants
+EXPECTED_SUCCESS_STATUS = 200
+EXPECTED_ERROR_STATUS = 503
+TEST_PROJECT_NAME = "test_project"
+REGISTRY_TTL_SECS = 60
+
+
+def _create_mock_ui_files(temp_dir):
+    """Helper function to create required UI files structure"""
+    ui_dir = os.path.join(temp_dir, "ui", "build")
+    os.makedirs(ui_dir, exist_ok=True)
+
+    # Create projects-list.json file
+    projects_file = os.path.join(ui_dir, "projects-list.json")
+    with open(projects_file, "w") as f:
+        json.dump({"projects": []}, f)
+
+    # Create index.html file
+    index_file = os.path.join(ui_dir, "index.html")
+    with open(index_file, "w") as f:
+        f.write("<html><body>Test UI</body></html>")
+
+
+@contextlib.contextmanager
+def _setup_importlib_mocks(temp_dir):
+    """Helper function to setup importlib resource mocks.
+
+    This function mocks the importlib_resources functionality used by the UI server
+    to serve static files. It creates a proper context manager that returns the
+    temporary directory path when used with importlib_resources.as_file().
+    """
+    mock_path = Path(temp_dir)
+
+    # Create a proper context manager mock
+    mock_context_manager = MagicMock()
+    mock_context_manager.__enter__.return_value = mock_path
+    mock_context_manager.__exit__.return_value = None
+
+    # Mock the files() method to return a mock that supports division
+    mock_file_ref = MagicMock()
+    mock_file_ref.__truediv__.return_value = MagicMock()
+
+    with (
+        patch("feast.ui_server.importlib_resources.files") as mock_files,
+        patch("feast.ui_server.importlib_resources.as_file") as mock_as_file,
+    ):
+        mock_files.return_value = mock_file_ref
+        mock_as_file.return_value = mock_context_manager
+
+        yield mock_files, mock_as_file
+
+
+@pytest.fixture
+def mock_feature_store():
+    """Fixture for creating a mock feature store"""
+    mock_store = MagicMock()
+    mock_store.refresh_registry = MagicMock()
+    return mock_store
+
+
+@pytest.fixture
+def ui_app_with_registry(mock_feature_store):
+    """Fixture for UI app with valid registry data.
+
+    Creates a UI app instance with a properly configured feature store
+    that has valid registry data available for testing endpoints that
+    require registry access.
+    """
+    mock_registry = MagicMock()
+    mock_proto = MagicMock()
+    mock_proto.SerializeToString.return_value = b"mock_proto_data"
+    mock_registry.proto.return_value = mock_proto
+    mock_feature_store.registry = mock_registry
+
+    with tempfile.TemporaryDirectory() as temp_dir:
+        _create_mock_ui_files(temp_dir)
+
+        with _setup_importlib_mocks(temp_dir):
+            app = get_app(mock_feature_store, TEST_PROJECT_NAME, REGISTRY_TTL_SECS)
+            yield app
+
+
+@pytest.fixture
+def ui_app_without_registry(mock_feature_store):
+    """Fixture for UI app with None registry data.
+
+    Creates a UI app instance with a feature store that has no registry
+    data available, used for testing error conditions and service
+    unavailable responses.
+    """
+    mock_registry = MagicMock()
+    mock_registry.proto.return_value = None
+    mock_feature_store.registry = mock_registry
+
+    with tempfile.TemporaryDirectory() as temp_dir:
+        _create_mock_ui_files(temp_dir)
+
+        with _setup_importlib_mocks(temp_dir):
+            app = get_app(mock_feature_store, TEST_PROJECT_NAME, REGISTRY_TTL_SECS)
+            yield app
+
+
+def test_ui_server_health_endpoint(ui_app_with_registry):
+    """Test the UI server health endpoint returns 200 when registry is available.
+
+    This test verifies that the /health endpoint correctly returns HTTP 200
+    when the feature store registry is properly initialized and contains data.
+    """
+    client = TestClient(ui_app_with_registry)
+    response = client.get("/health")
+    assertpy.assert_that(response.status_code).is_equal_to(EXPECTED_SUCCESS_STATUS)
+
+
+def test_ui_server_health_endpoint_with_none_registry(ui_app_without_registry):
+    """Test the UI server health endpoint returns 503 when registry is None.
+
+    This test verifies that the /health endpoint correctly returns HTTP 503
+    (Service Unavailable) when the feature store registry is not available
+    or contains no data.
+    """
+    client = TestClient(ui_app_without_registry)
+    response = client.get("/health")
+    assertpy.assert_that(response.status_code).is_equal_to(EXPECTED_ERROR_STATUS)
+
+
+def test_registry_endpoint_with_valid_data(ui_app_with_registry):
+    """Test the registry endpoint returns valid data with correct content type.
+
+    This test verifies that the /registry endpoint correctly returns HTTP 200
+    with the proper content-type header when registry data is available.
+    """
+    client = TestClient(ui_app_with_registry)
+    response = client.get("/registry")
+    assertpy.assert_that(response.status_code).is_equal_to(EXPECTED_SUCCESS_STATUS)
+    assertpy.assert_that(response.headers["content-type"]).is_equal_to(
+        "application/octet-stream"
+    )
+
+
+def test_registry_endpoint_with_none_data(ui_app_without_registry):
+    """Test the registry endpoint returns 503 when registry data is None.
+
+    This test verifies that the /registry endpoint correctly returns HTTP 503
+    (Service Unavailable) when no registry data is available.
+    """
+    client = TestClient(ui_app_without_registry)
+    response = client.get("/registry")
+    assertpy.assert_that(response.status_code).is_equal_to(EXPECTED_ERROR_STATUS)
+
+
+def test_save_document_endpoint_success(ui_app_with_registry):
+    """Test the save document endpoint successfully saves data to a labels file.
+
+    This test verifies that the /save-document endpoint correctly processes
+    a valid request, creates a labels file, and returns success confirmation.
+    """
+    client = TestClient(ui_app_with_registry)
+
+    # Create a temporary file in the current working directory for testing
+    with tempfile.NamedTemporaryFile(
+        mode="w", suffix=".py", delete=False, dir=os.getcwd()
+    ) as f:
+        test_file_path = f.name
+        f.write("# Test file content")
+
+    try:
+        request_data = {
+            "file_path": test_file_path,
+            "data": {"test": "data", "key": "value"},
+        }
+
+        response = client.post("/save-document", json=request_data)
+        assertpy.assert_that(response.status_code).is_equal_to(EXPECTED_SUCCESS_STATUS)
+
+        response_data = response.json()
+        assertpy.assert_that(response_data["success"]).is_true()
+        assertpy.assert_that(response_data).contains_key("saved_to")
+
+        # Verify the file was created
+        labels_file = response_data["saved_to"]
+        assertpy.assert_that(os.path.exists(labels_file)).is_true()
+
+        with open(labels_file, "r") as f:
+            saved_data = json.load(f)
+        assertpy.assert_that(saved_data).is_equal_to(request_data["data"])
+
+    finally:
+        # Cleanup
+        if os.path.exists(test_file_path):
+            os.unlink(test_file_path)
+        labels_file = test_file_path.replace(".py", "-labels.json")
+        if os.path.exists(labels_file):
+            os.unlink(labels_file)
+
+
+def test_save_document_endpoint_invalid_path(ui_app_with_registry):
+    """Test the save document endpoint returns error for invalid file path.
+
+    This test verifies that the /save-document endpoint correctly rejects
+    file paths that are outside the current working directory for security.
+    """
+    client = TestClient(ui_app_with_registry)
+
+    request_data = {
+        "file_path": "/invalid/absolute/path/outside/workspace.py",
+        "data": {"test": "data"},
+    }
+
+    response = client.post("/save-document", json=request_data)
+    assertpy.assert_that(response.status_code).is_equal_to(EXPECTED_SUCCESS_STATUS)
+
+    response_data = response.json()
+    assertpy.assert_that(response_data).contains_key("error")
+    assertpy.assert_that(response_data["error"]).contains("Invalid file path")
+
+
+def test_save_document_endpoint_exception_handling(ui_app_with_registry):
+    """Test the save document endpoint handles exceptions gracefully.
+
+    This test verifies that the /save-document endpoint properly catches
+    and returns error responses when exceptions occur during processing.
+    """
+    client = TestClient(ui_app_with_registry)
+
+    # Test with a file path outside the current working directory (will cause an exception)
+    request_data = {
+        "file_path": "/invalid/absolute/path/outside/workspace.py",
+        "data": {"test": "data"},
+    }
+
+    response = client.post("/save-document", json=request_data)
+    assertpy.assert_that(response.status_code).is_equal_to(EXPECTED_SUCCESS_STATUS)
+
+    response_data = response.json()
+    assertpy.assert_that(response_data).contains_key("error")
+    assertpy.assert_that(response_data["error"]).contains("Invalid file path")
+
+
+@pytest.mark.parametrize(
+    "registry_available,expected_status",
+    [(True, EXPECTED_SUCCESS_STATUS), (False, EXPECTED_ERROR_STATUS)],
+)
+def test_health_endpoint_status(
+    registry_available, expected_status, mock_feature_store
+):
+    """Test the health endpoint returns correct status based on registry availability.
+
+    This parametrized test verifies that the /health endpoint returns the
+    appropriate HTTP status code based on whether registry data is available.
+    """
+    if registry_available:
+        mock_registry = MagicMock()
+        mock_proto = MagicMock()
+        mock_proto.SerializeToString.return_value = b"mock_proto_data"
+        mock_registry.proto.return_value = mock_proto
+        mock_feature_store.registry = mock_registry
+    else:
+        mock_registry = MagicMock()
+        mock_registry.proto.return_value = None
+        mock_feature_store.registry = mock_registry
+
+    with tempfile.TemporaryDirectory() as temp_dir:
+        _create_mock_ui_files(temp_dir)
+
+        with _setup_importlib_mocks(temp_dir):
+            app = get_app(mock_feature_store, TEST_PROJECT_NAME, REGISTRY_TTL_SECS)
+            client = TestClient(app)
+            response = client.get("/health")
+            assertpy.assert_that(response.status_code).is_equal_to(expected_status)
+
+
+def test_catch_all_route(ui_app_with_registry):
+    """Test the catch-all route for React router paths.
+
+    This test reveals a bug in the original UI server code where ui_dir
+    is not in scope for the catch_all function. The ui_dir variable is defined
+    inside the importlib_resources context manager but used outside of it.
+    This causes a NameError when the route is accessed.
+    """
+    client = TestClient(ui_app_with_registry)
+
+    # The route will fail due to the scope issue with ui_dir
+    with pytest.raises(Exception):  # Expecting NameError or FileNotFoundError
+        client.get("/p/some/react/path")
diff --git a/ui/package.json b/ui/package.json
index 17bff99e1aa..f087d6cad14 100644
--- a/ui/package.json
+++ b/ui/package.json
@@ -1,6 +1,6 @@
 {
   "name": "@feast-dev/feast-ui",
-  "version": "0.55.0",
+  "version": "0.56.0",
   "private": false,
   "files": [
     "dist"
diff --git a/ui/src/components/CommandPalette.tsx b/ui/src/components/CommandPalette.tsx
index 9750d73e2d9..8e18898400a 100644
--- a/ui/src/components/CommandPalette.tsx
+++ b/ui/src/components/CommandPalette.tsx
@@ -149,6 +149,7 @@ const CommandPalette: React.FC<CommandPaletteProps> = ({
             ? String(item.spec.description || "")
             : "",
         type: getItemType(item, name),
+        projectId: "projectId" in item ? String(item.projectId) : undefined,
       };
     });
 
@@ -158,15 +159,7 @@ const CommandPalette: React.FC<CommandPaletteProps> = ({
     };
   });
 
-  console.log(
-    "CommandPalette isOpen:",
-    isOpen,
-    "categories:",
-    categories.length,
-  ); // Debug log
-
   if (!isOpen) {
-    console.log("CommandPalette not rendering due to isOpen=false");
     return null;
   }
 
@@ -227,16 +220,11 @@ const CommandPalette: React.FC<CommandPaletteProps> = ({
                                   href={item.link}
                                   onClick={(e) => {
                                     e.preventDefault();
-                                    console.log(
-                                      "Search result clicked:",
-                                      item.name,
-                                    );
 
                                     onClose();
 
                                     setSearchText("");
 
-                                    console.log("Navigating to:", item.link);
                                     navigate(item.link);
                                   }}
                                   style={{
@@ -253,6 +241,17 @@ const CommandPalette: React.FC<CommandPaletteProps> = ({
                                     {item.description}
                                   </div>
                                 )}
+                                {item.projectId && (
+                                  <div
+                                    style={{
+                                      fontSize: "0.85em",
+                                      color: "#69707D",
+                                      marginTop: "4px",
+                                    }}
+                                  >
+                                    Project: {item.projectId}
+                                  </div>
+                                )}
                               </EuiFlexItem>
                               {item.type && (
                                 <EuiFlexItem grow={false}>
diff --git a/ui/src/components/GlobalSearchShortcut.tsx b/ui/src/components/GlobalSearchShortcut.tsx
index 28e55454f30..aa96abe5b97 100644
--- a/ui/src/components/GlobalSearchShortcut.tsx
+++ b/ui/src/components/GlobalSearchShortcut.tsx
@@ -9,23 +9,13 @@ const GlobalSearchShortcut: React.FC<GlobalSearchShortcutProps> = ({
 }) => {
   useEffect(() => {
     const handleKeyDown = (event: KeyboardEvent) => {
-      console.log(
-        "Key pressed:",
-        event.key,
-        "metaKey:",
-        event.metaKey,
-        "ctrlKey:",
-        event.ctrlKey,
-      );
       if ((event.metaKey || event.ctrlKey) && event.key.toLowerCase() === "k") {
-        console.log("Cmd+K detected, preventing default and calling onOpen");
         event.preventDefault();
         event.stopPropagation();
         onOpen();
       }
     };
 
-    console.log("Adding keydown event listener to window");
     window.addEventListener("keydown", handleKeyDown, true);
     return () => {
       window.removeEventListener("keydown", handleKeyDown, true);
diff --git a/ui/src/components/ProjectSelector.tsx b/ui/src/components/ProjectSelector.tsx
index 1bb7ebf85a7..ac9057bfb00 100644
--- a/ui/src/components/ProjectSelector.tsx
+++ b/ui/src/components/ProjectSelector.tsx
@@ -1,11 +1,12 @@
 import { EuiSelect, useGeneratedHtmlId } from "@elastic/eui";
 import React from "react";
-import { useNavigate, useParams } from "react-router-dom";
+import { useNavigate, useParams, useLocation } from "react-router-dom";
 import { useLoadProjectsList } from "../contexts/ProjectListContext";
 
 const ProjectSelector = () => {
   const { projectName } = useParams();
   const navigate = useNavigate();
+  const location = useLocation();
 
   const { isLoading, data } = useLoadProjectsList();
 
@@ -22,7 +23,20 @@ const ProjectSelector = () => {
 
   const basicSelectId = useGeneratedHtmlId({ prefix: "basicSelect" });
   const onChange = (e: React.ChangeEvent<HTMLSelectElement>) => {
-    navigate(`/p/${e.target.value}`);
+    const newProjectId = e.target.value;
+
+    // If we're on a project page, maintain the current path context
+    if (projectName && location.pathname.startsWith(`/p/${projectName}`)) {
+      // Replace the old project name with the new one in the current path
+      const newPath = location.pathname.replace(
+        `/p/${projectName}`,
+        `/p/${newProjectId}`,
+      );
+      navigate(newPath);
+    } else {
+      // Otherwise, just navigate to the project home
+      navigate(`/p/${newProjectId}`);
+    }
   };
 
   return (
diff --git a/ui/src/components/RegistrySearch.tsx b/ui/src/components/RegistrySearch.tsx
index d9d72a20b1a..46d72966713 100644
--- a/ui/src/components/RegistrySearch.tsx
+++ b/ui/src/components/RegistrySearch.tsx
@@ -112,6 +112,7 @@ const RegistrySearch = forwardRef<RegistrySearchRef, RegistrySearchProps>(
               ? String(item.spec.description || "")
               : "",
           type: getItemType(item, name),
+          projectId: "projectId" in item ? String(item.projectId) : undefined,
         };
       });
 
@@ -187,6 +188,17 @@ const RegistrySearch = forwardRef<RegistrySearchRef, RegistrySearchProps>(
                                   {item.description}
                                 </div>
                               )}
+                              {item.projectId && (
+                                <div
+                                  style={{
+                                    fontSize: "0.85em",
+                                    color: "#69707D",
+                                    marginTop: "4px",
+                                  }}
+                                >
+                                  Project: {item.projectId}
+                                </div>
+                              )}
                             </EuiFlexItem>
                             {item.type && (
                               <EuiFlexItem grow={false}>
diff --git a/ui/src/components/RegistryVisualizationTab.tsx b/ui/src/components/RegistryVisualizationTab.tsx
index accf02971c6..ebc77604322 100644
--- a/ui/src/components/RegistryVisualizationTab.tsx
+++ b/ui/src/components/RegistryVisualizationTab.tsx
@@ -1,4 +1,5 @@
 import React, { useContext, useState } from "react";
+import { useParams } from "react-router-dom";
 import {
   EuiEmptyPrompt,
   EuiLoadingSpinner,
@@ -16,7 +17,11 @@ import { filterPermissionsByAction } from "../utils/permissionUtils";
 
 const RegistryVisualizationTab = () => {
   const registryUrl = useContext(RegistryPathContext);
-  const { isLoading, isSuccess, isError, data } = useLoadRegistry(registryUrl);
+  const { projectName } = useParams();
+  const { isLoading, isSuccess, isError, data } = useLoadRegistry(
+    registryUrl,
+    projectName,
+  );
   const [selectedObjectType, setSelectedObjectType] = useState("");
   const [selectedObjectName, setSelectedObjectName] = useState("");
   const [selectedPermissionAction, setSelectedPermissionAction] = useState("");
diff --git a/ui/src/mocks/handlers.ts b/ui/src/mocks/handlers.ts
index 23904787c16..1c32bb2cf87 100644
--- a/ui/src/mocks/handlers.ts
+++ b/ui/src/mocks/handlers.ts
@@ -8,12 +8,12 @@ const registry = readFileSync(
 
 const projectsListWithDefaultProject = http.get("/projects-list.json", () =>
   HttpResponse.json({
-    default: "credit_score_project",
+    default: "credit_scoring_aws",
     projects: [
       {
         name: "Credit Score Project",
         description: "Project for credit scoring team and associated models.",
-        id: "credit_score_project",
+        id: "credit_scoring_aws",
         registryPath: "/registry.db", // Changed to match what the test expects
       },
     ],
diff --git a/ui/src/pages/Layout.tsx b/ui/src/pages/Layout.tsx
index 4a00eb64a37..0e3341b8820 100644
--- a/ui/src/pages/Layout.tsx
+++ b/ui/src/pages/Layout.tsx
@@ -42,8 +42,19 @@ const Layout = () => {
   });
 
   const registryPath = currentProject?.registryPath || "";
-  const { data } = useLoadRegistry(registryPath);
 
+  // For global search, use the first available registry path (typically all projects share the same registry)
+  // If projects have different registries, we use the first one as the "global" registry
+  const globalRegistryPath =
+    projectsData?.projects?.[0]?.registryPath || registryPath;
+
+  // Load filtered data for current project (for sidebar and page-level search)
+  const { data } = useLoadRegistry(registryPath, projectName);
+
+  // Load unfiltered data for global search (across all projects)
+  const { data: globalData } = useLoadRegistry(globalRegistryPath);
+
+  // Categories for page-level search (filtered to current project)
   const categories = data
     ? [
         {
@@ -84,31 +95,92 @@ const Layout = () => {
       ]
     : [];
 
+  // Helper function to extract project ID from an item
+  const getProjectId = (item: any): string => {
+    // Try different possible locations for the project field
+    return item?.spec?.project || item?.project || projectName || "unknown";
+  };
+
+  // Categories for global search (includes all projects)
+  const globalCategories = globalData
+    ? [
+        {
+          name: "Data Sources",
+          data: (globalData.objects.dataSources || []).map((item: any) => ({
+            ...item,
+            projectId: getProjectId(item),
+          })),
+          getLink: (item: any) => {
+            const project = item?.projectId || getProjectId(item);
+            return `/p/${project}/data-source/${item.name}`;
+          },
+        },
+        {
+          name: "Entities",
+          data: (globalData.objects.entities || []).map((item: any) => ({
+            ...item,
+            projectId: getProjectId(item),
+          })),
+          getLink: (item: any) => {
+            const project = item?.projectId || getProjectId(item);
+            return `/p/${project}/entity/${item.name}`;
+          },
+        },
+        {
+          name: "Features",
+          data: (globalData.allFeatures || []).map((item: any) => ({
+            ...item,
+            projectId: getProjectId(item),
+          })),
+          getLink: (item: any) => {
+            const featureView = item?.featureView;
+            const project = item?.projectId || getProjectId(item);
+            return featureView
+              ? `/p/${project}/feature-view/${featureView}/feature/${item.name}`
+              : "#";
+          },
+        },
+        {
+          name: "Feature Views",
+          data: (globalData.mergedFVList || []).map((item: any) => ({
+            ...item,
+            projectId: getProjectId(item),
+          })),
+          getLink: (item: any) => {
+            const project = item?.projectId || getProjectId(item);
+            return `/p/${project}/feature-view/${item.name}`;
+          },
+        },
+        {
+          name: "Feature Services",
+          data: (globalData.objects.featureServices || []).map((item: any) => ({
+            ...item,
+            projectId: getProjectId(item),
+          })),
+          getLink: (item: any) => {
+            const serviceName = item?.name || item?.spec?.name;
+            const project = item?.projectId || getProjectId(item);
+            return serviceName
+              ? `/p/${project}/feature-service/${serviceName}`
+              : "#";
+          },
+        },
+      ]
+    : [];
+
   const handleSearchOpen = () => {
-    console.log("Opening command palette - before state update"); // Debug log
     setIsCommandPaletteOpen(true);
-    console.log("Command palette state should be updated to true");
   };
 
   useEffect(() => {
     const handleKeyDown = (event: KeyboardEvent) => {
-      console.log(
-        "Layout key pressed:",
-        event.key,
-        "metaKey:",
-        event.metaKey,
-        "ctrlKey:",
-        event.ctrlKey,
-      );
       if ((event.metaKey || event.ctrlKey) && event.key.toLowerCase() === "k") {
-        console.log("Layout detected Cmd+K, preventing default");
         event.preventDefault();
         event.stopPropagation();
         handleSearchOpen();
       }
     };
 
-    console.log("Layout adding keydown event listener");
     window.addEventListener("keydown", handleKeyDown, true);
     return () => {
       window.removeEventListener("keydown", handleKeyDown, true);
@@ -121,7 +193,7 @@ const Layout = () => {
       <CommandPalette
         isOpen={isCommandPaletteOpen}
         onClose={() => setIsCommandPaletteOpen(false)}
-        categories={categories}
+        categories={globalCategories}
       />
       <EuiPage paddingSize="none" style={{ background: "transparent" }}>
         <EuiPageSidebar
@@ -179,7 +251,10 @@ const Layout = () => {
                       grow={false}
                       style={{ width: "600px", maxWidth: "90%" }}
                     >
-                      <RegistrySearch ref={searchRef} categories={categories} />
+                      <RegistrySearch
+                        ref={searchRef}
+                        categories={globalCategories}
+                      />
                     </EuiFlexItem>
                   </EuiFlexGroup>
                 </div>
diff --git a/ui/src/pages/ProjectOverviewPage.tsx b/ui/src/pages/ProjectOverviewPage.tsx
index aa8d7cd4745..839fbcc5d89 100644
--- a/ui/src/pages/ProjectOverviewPage.tsx
+++ b/ui/src/pages/ProjectOverviewPage.tsx
@@ -9,6 +9,9 @@ import {
   EuiSkeletonText,
   EuiEmptyPrompt,
   EuiFieldSearch,
+  EuiPanel,
+  EuiStat,
+  EuiCard,
 } from "@elastic/eui";
 
 import { useDocumentTitle } from "../hooks/useDocumentTitle";
@@ -18,14 +21,191 @@ import useLoadRegistry from "../queries/useLoadRegistry";
 import RegistryPathContext from "../contexts/RegistryPathContext";
 import RegistryVisualizationTab from "../components/RegistryVisualizationTab";
 import RegistrySearch from "../components/RegistrySearch";
-import { useParams } from "react-router-dom";
+import { useParams, useNavigate } from "react-router-dom";
+import { useLoadProjectsList } from "../contexts/ProjectListContext";
+
+// Component for "All Projects" view
+const AllProjectsDashboard = () => {
+  const registryUrl = useContext(RegistryPathContext);
+  const navigate = useNavigate();
+  const { data: projectsData } = useLoadProjectsList();
+  const { data: registryData } = useLoadRegistry(registryUrl);
+
+  if (!registryData) {
+    return <EuiSkeletonText lines={10} />;
+  }
+
+  // Calculate total counts across all projects
+  const totalCounts = {
+    featureViews: registryData.objects.featureViews?.length || 0,
+    entities: registryData.objects.entities?.length || 0,
+    dataSources: registryData.objects.dataSources?.length || 0,
+    featureServices: registryData.objects.featureServices?.length || 0,
+    features: registryData.allFeatures?.length || 0,
+  };
+
+  // Get projects from registry and count their objects
+  const projects = projectsData?.projects.filter((p) => p.id !== "all") || [];
+  const projectStats = projects.map((project) => {
+    const projectFVs =
+      registryData.objects.featureViews?.filter(
+        (fv: any) => fv?.spec?.project === project.id,
+      ) || [];
+    const projectEntities =
+      registryData.objects.entities?.filter(
+        (e: any) => e?.spec?.project === project.id,
+      ) || [];
+    const projectFeatures =
+      registryData.allFeatures?.filter((f: any) => f?.project === project.id) ||
+      [];
+
+    return {
+      ...project,
+      counts: {
+        featureViews: projectFVs.length,
+        entities: projectEntities.length,
+        features: projectFeatures.length,
+      },
+    };
+  });
+
+  return (
+    <EuiPageTemplate panelled>
+      <EuiPageTemplate.Section>
+        <EuiTitle size="l">
+          <h1>All Projects Overview</h1>
+        </EuiTitle>
+        <EuiSpacer />
+
+        <EuiText>
+          <p>
+            View aggregated statistics and explore data across all your Feast
+            projects.
+          </p>
+        </EuiText>
+        <EuiSpacer size="l" />
+
+        {/* Total Stats */}
+        <EuiPanel hasBorder>
+          <EuiTitle size="s">
+            <h3>Total Across All Projects</h3>
+          </EuiTitle>
+          <EuiSpacer size="m" />
+          <EuiFlexGroup>
+            <EuiFlexItem>
+              <EuiStat
+                title={totalCounts.featureViews.toString()}
+                description="Feature Views"
+                titleSize="m"
+                textAlign="center"
+              />
+            </EuiFlexItem>
+            <EuiFlexItem>
+              <EuiStat
+                title={totalCounts.entities.toString()}
+                description="Entities"
+                titleSize="m"
+                textAlign="center"
+              />
+            </EuiFlexItem>
+            <EuiFlexItem>
+              <EuiStat
+                title={totalCounts.features.toString()}
+                description="Features"
+                titleSize="m"
+                textAlign="center"
+              />
+            </EuiFlexItem>
+            <EuiFlexItem>
+              <EuiStat
+                title={totalCounts.featureServices.toString()}
+                description="Feature Services"
+                titleSize="m"
+                textAlign="center"
+              />
+            </EuiFlexItem>
+            <EuiFlexItem>
+              <EuiStat
+                title={totalCounts.dataSources.toString()}
+                description="Data Sources"
+                titleSize="m"
+                textAlign="center"
+              />
+            </EuiFlexItem>
+          </EuiFlexGroup>
+        </EuiPanel>
+
+        <EuiSpacer size="l" />
+
+        {/* Individual Projects */}
+        <EuiTitle size="s">
+          <h3>Projects ({projects.length})</h3>
+        </EuiTitle>
+        <EuiSpacer size="m" />
+        <EuiFlexGroup gutterSize="l" wrap>
+          {projectStats.map((project) => (
+            <EuiFlexItem
+              key={project.id}
+              style={{ minWidth: "300px", maxWidth: "400px" }}
+            >
+              <EuiCard
+                title={project.name}
+                description={project.description}
+                onClick={() => navigate(`/p/${project.id}`)}
+                style={{ cursor: "pointer" }}
+              >
+                <EuiSpacer size="s" />
+                <EuiFlexGroup justifyContent="spaceAround" gutterSize="s">
+                  <EuiFlexItem grow={false}>
+                    <EuiText size="s" textAlign="center">
+                      <strong>{project.counts.featureViews}</strong>
+                      <br />
+                      <span style={{ fontSize: "0.85em", color: "#69707D" }}>
+                        Feature Views
+                      </span>
+                    </EuiText>
+                  </EuiFlexItem>
+                  <EuiFlexItem grow={false}>
+                    <EuiText size="s" textAlign="center">
+                      <strong>{project.counts.entities}</strong>
+                      <br />
+                      <span style={{ fontSize: "0.85em", color: "#69707D" }}>
+                        Entities
+                      </span>
+                    </EuiText>
+                  </EuiFlexItem>
+                  <EuiFlexItem grow={false}>
+                    <EuiText size="s" textAlign="center">
+                      <strong>{project.counts.features}</strong>
+                      <br />
+                      <span style={{ fontSize: "0.85em", color: "#69707D" }}>
+                        Features
+                      </span>
+                    </EuiText>
+                  </EuiFlexItem>
+                </EuiFlexGroup>
+              </EuiCard>
+            </EuiFlexItem>
+          ))}
+        </EuiFlexGroup>
+      </EuiPageTemplate.Section>
+    </EuiPageTemplate>
+  );
+};
 
 const ProjectOverviewPage = () => {
   useDocumentTitle("Feast Home");
   const registryUrl = useContext(RegistryPathContext);
-  const { isLoading, isSuccess, isError, data } = useLoadRegistry(registryUrl);
-
   const { projectName } = useParams<{ projectName: string }>();
+  const { isLoading, isSuccess, isError, data } = useLoadRegistry(
+    registryUrl,
+    projectName,
+  );
+
+  // Show aggregated dashboard for "All Projects" view
+  if (projectName === "all") {
+    return <AllProjectsDashboard />;
+  }
 
   const categories = [
     {
diff --git a/ui/src/pages/Sidebar.tsx b/ui/src/pages/Sidebar.tsx
index d7a5a54cda0..55c8ec805c9 100644
--- a/ui/src/pages/Sidebar.tsx
+++ b/ui/src/pages/Sidebar.tsx
@@ -17,8 +17,8 @@ import { PermissionsIcon } from "../graphics/PermissionsIcon";
 
 const SideNav = () => {
   const registryUrl = useContext(RegistryPathContext);
-  const { isSuccess, data } = useLoadRegistry(registryUrl);
   const { projectName } = useParams();
+  const { isSuccess, data } = useLoadRegistry(registryUrl, projectName);
 
   const [isSideNavOpenOnMobile, setisSideNavOpenOnMobile] = useState(false);
 
diff --git a/ui/src/pages/data-sources/DataSourceOverviewTab.tsx b/ui/src/pages/data-sources/DataSourceOverviewTab.tsx
index e4931aa7c50..d702034a558 100644
--- a/ui/src/pages/data-sources/DataSourceOverviewTab.tsx
+++ b/ui/src/pages/data-sources/DataSourceOverviewTab.tsx
@@ -27,9 +27,9 @@ import RequestDataSourceSchemaTable from "./RequestDataSourceSchemaTable";
 import useLoadDataSource from "./useLoadDataSource";
 
 const DataSourceOverviewTab = () => {
-  let { dataSourceName } = useParams();
+  let { dataSourceName, projectName } = useParams();
   const registryUrl = useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const dsName = dataSourceName === undefined ? "" : dataSourceName;
   const { isLoading, isSuccess, isError, data, consumingFeatureViews } =
diff --git a/ui/src/pages/data-sources/DataSourcesListingTable.tsx b/ui/src/pages/data-sources/DataSourcesListingTable.tsx
index fd1ff73deb7..c314a4dfb94 100644
--- a/ui/src/pages/data-sources/DataSourcesListingTable.tsx
+++ b/ui/src/pages/data-sources/DataSourcesListingTable.tsx
@@ -18,9 +18,11 @@ const DatasourcesListingTable = ({
       name: "Name",
       field: "name",
       sortable: true,
-      render: (name: string) => {
+      render: (name: string, item: feast.core.IDataSource) => {
+        // For "All Projects" view, link to the specific project
+        const itemProject = item?.project || projectName;
         return (
-          <EuiCustomLink to={`/p/${projectName}/data-source/${name}`}>
+          <EuiCustomLink to={`/p/${itemProject}/data-source/${name}`}>
             {name}
           </EuiCustomLink>
         );
@@ -36,6 +38,18 @@ const DatasourcesListingTable = ({
     },
   ];
 
+  // Add Project column when viewing all projects
+  if (projectName === "all") {
+    columns.splice(1, 0, {
+      name: "Project",
+      field: "project",
+      sortable: true,
+      render: (project: string) => {
+        return <span>{project || "Unknown"}</span>;
+      },
+    });
+  }
+
   const getRowProps = (item: feast.core.IDataSource) => {
     return {
       "data-test-subj": `row-${item.name}`,
diff --git a/ui/src/pages/data-sources/Index.tsx b/ui/src/pages/data-sources/Index.tsx
index 59bdcecd1df..96aef712aec 100644
--- a/ui/src/pages/data-sources/Index.tsx
+++ b/ui/src/pages/data-sources/Index.tsx
@@ -1,4 +1,5 @@
 import React, { useContext } from "react";
+import { useParams } from "react-router-dom";
 
 import {
   EuiPageTemplate,
@@ -22,7 +23,8 @@ import ExportButton from "../../components/ExportButton";
 
 const useLoadDatasources = () => {
   const registryUrl = useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const { projectName } = useParams();
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const data =
     registryQuery.data === undefined
diff --git a/ui/src/pages/data-sources/useLoadDataSource.ts b/ui/src/pages/data-sources/useLoadDataSource.ts
index aa9f4e731bf..43f697fca03 100644
--- a/ui/src/pages/data-sources/useLoadDataSource.ts
+++ b/ui/src/pages/data-sources/useLoadDataSource.ts
@@ -1,11 +1,13 @@
 import { useContext } from "react";
+import { useParams } from "react-router-dom";
 import RegistryPathContext from "../../contexts/RegistryPathContext";
 import { FEAST_FCO_TYPES } from "../../parsers/types";
 import useLoadRegistry from "../../queries/useLoadRegistry";
 
 const useLoadDataSource = (dataSourceName: string) => {
   const registryUrl = useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const { projectName } = useParams();
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const data =
     registryQuery.data === undefined
diff --git a/ui/src/pages/entities/EntitiesListingTable.tsx b/ui/src/pages/entities/EntitiesListingTable.tsx
index 06190409b04..51ffb7c8609 100644
--- a/ui/src/pages/entities/EntitiesListingTable.tsx
+++ b/ui/src/pages/entities/EntitiesListingTable.tsx
@@ -18,9 +18,11 @@ const EntitiesListingTable = ({ entities }: EntitiesListingTableProps) => {
       name: "Name",
       field: "spec.name",
       sortable: true,
-      render: (name: string) => {
+      render: (name: string, item: feast.core.IEntity) => {
+        // For "All Projects" view, link to the specific project
+        const itemProject = item?.spec?.project || projectName;
         return (
-          <EuiCustomLink to={`/p/${projectName}/entity/${name}`}>
+          <EuiCustomLink to={`/p/${itemProject}/entity/${name}`}>
             {name}
           </EuiCustomLink>
         );
@@ -46,6 +48,18 @@ const EntitiesListingTable = ({ entities }: EntitiesListingTableProps) => {
     },
   ];
 
+  // Add Project column when viewing all projects
+  if (projectName === "all") {
+    columns.splice(1, 0, {
+      name: "Project",
+      field: "spec.project",
+      sortable: true,
+      render: (project: string) => {
+        return <span>{project || "Unknown"}</span>;
+      },
+    });
+  }
+
   const getRowProps = (item: feast.core.IEntity) => {
     return {
       "data-test-subj": `row-${item?.spec?.name}`,
diff --git a/ui/src/pages/entities/EntityOverviewTab.tsx b/ui/src/pages/entities/EntityOverviewTab.tsx
index 09d9aaa3446..8a20688d140 100644
--- a/ui/src/pages/entities/EntityOverviewTab.tsx
+++ b/ui/src/pages/entities/EntityOverviewTab.tsx
@@ -28,9 +28,9 @@ import useFeatureViewEdgesByEntity from "./useFeatureViewEdgesByEntity";
 import useLoadEntity from "./useLoadEntity";
 
 const EntityOverviewTab = () => {
-  let { entityName } = useParams();
+  let { entityName, projectName } = useParams();
   const registryUrl = useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const eName = entityName === undefined ? "" : entityName;
   const { isLoading, isSuccess, isError, data } = useLoadEntity(eName);
diff --git a/ui/src/pages/entities/Index.tsx b/ui/src/pages/entities/Index.tsx
index bed1bfb762c..070c53d38fa 100644
--- a/ui/src/pages/entities/Index.tsx
+++ b/ui/src/pages/entities/Index.tsx
@@ -1,4 +1,5 @@
 import React, { useContext } from "react";
+import { useParams } from "react-router-dom";
 
 import { EuiPageTemplate, EuiLoadingSpinner } from "@elastic/eui";
 
@@ -13,7 +14,8 @@ import ExportButton from "../../components/ExportButton";
 
 const useLoadEntities = () => {
   const registryUrl = useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const { projectName } = useParams();
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const data =
     registryQuery.data === undefined
diff --git a/ui/src/pages/entities/useLoadEntity.ts b/ui/src/pages/entities/useLoadEntity.ts
index e3e2ede8c2c..fdb4a7968f1 100644
--- a/ui/src/pages/entities/useLoadEntity.ts
+++ b/ui/src/pages/entities/useLoadEntity.ts
@@ -1,10 +1,12 @@
 import { useContext } from "react";
+import { useParams } from "react-router-dom";
 import RegistryPathContext from "../../contexts/RegistryPathContext";
 import useLoadRegistry from "../../queries/useLoadRegistry";
 
 const useLoadEntity = (entityName: string) => {
   const registryUrl = useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const { projectName } = useParams();
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const data =
     registryQuery.data === undefined
diff --git a/ui/src/pages/feature-services/FeatureServiceListingTable.tsx b/ui/src/pages/feature-services/FeatureServiceListingTable.tsx
index 69d4d1f969d..acc68b6e619 100644
--- a/ui/src/pages/feature-services/FeatureServiceListingTable.tsx
+++ b/ui/src/pages/feature-services/FeatureServiceListingTable.tsx
@@ -28,9 +28,11 @@ const FeatureServiceListingTable = ({
     {
       name: "Name",
       field: "spec.name",
-      render: (name: string) => {
+      render: (name: string, item: feast.core.IFeatureService) => {
+        // For "All Projects" view, link to the specific project
+        const itemProject = item?.spec?.project || projectName;
         return (
-          <EuiCustomLink to={`/p/${projectName}/feature-service/${name}`}>
+          <EuiCustomLink to={`/p/${itemProject}/feature-service/${name}`}>
             {name}
           </EuiCustomLink>
         );
@@ -56,6 +58,18 @@ const FeatureServiceListingTable = ({
     },
   ];
 
+  // Add Project column when viewing all projects
+  if (projectName === "all") {
+    columns.splice(1, 0, {
+      name: "Project",
+      field: "spec.project",
+      sortable: true,
+      render: (project: string) => {
+        return project || "Unknown";
+      },
+    });
+  }
+
   tagKeysSet.forEach((key) => {
     columns.push({
       name: key,
diff --git a/ui/src/pages/feature-services/Index.tsx b/ui/src/pages/feature-services/Index.tsx
index 0da8986e610..260a9b821dc 100644
--- a/ui/src/pages/feature-services/Index.tsx
+++ b/ui/src/pages/feature-services/Index.tsx
@@ -1,4 +1,5 @@
 import React, { useContext } from "react";
+import { useParams } from "react-router-dom";
 
 import {
   EuiPageTemplate,
@@ -30,7 +31,8 @@ import { feast } from "../../protos";
 
 const useLoadFeatureServices = () => {
   const registryUrl = useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const { projectName } = useParams();
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const data =
     registryQuery.data === undefined
diff --git a/ui/src/pages/feature-services/useLoadFeatureService.ts b/ui/src/pages/feature-services/useLoadFeatureService.ts
index fe21fe2d36b..004ab35b927 100644
--- a/ui/src/pages/feature-services/useLoadFeatureService.ts
+++ b/ui/src/pages/feature-services/useLoadFeatureService.ts
@@ -1,5 +1,6 @@
 import { FEAST_FCO_TYPES } from "../../parsers/types";
 import { useContext } from "react";
+import { useParams } from "react-router-dom";
 import RegistryPathContext from "../../contexts/RegistryPathContext";
 
 import useLoadRegistry from "../../queries/useLoadRegistry";
@@ -7,7 +8,8 @@ import { EntityReference } from "../../parsers/parseEntityRelationships";
 
 const useLoadFeatureService = (featureServiceName: string) => {
   const registryUrl = useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const { projectName } = useParams();
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const data =
     registryQuery.data === undefined
diff --git a/ui/src/pages/feature-views/FeatureViewInstance.tsx b/ui/src/pages/feature-views/FeatureViewInstance.tsx
index 4a0cc6a9129..93d0245b9fa 100644
--- a/ui/src/pages/feature-views/FeatureViewInstance.tsx
+++ b/ui/src/pages/feature-views/FeatureViewInstance.tsx
@@ -14,9 +14,9 @@ import useLoadRegistry from "../../queries/useLoadRegistry";
 import RegistryPathContext from "../../contexts/RegistryPathContext";
 
 const FeatureViewInstance = () => {
-  const { featureViewName } = useParams();
+  const { featureViewName, projectName } = useParams();
   const registryUrl = React.useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const fvName = featureViewName === undefined ? "" : featureViewName;
 
diff --git a/ui/src/pages/feature-views/FeatureViewLineageTab.tsx b/ui/src/pages/feature-views/FeatureViewLineageTab.tsx
index 39c31e17dbd..8759935e8ea 100644
--- a/ui/src/pages/feature-views/FeatureViewLineageTab.tsx
+++ b/ui/src/pages/feature-views/FeatureViewLineageTab.tsx
@@ -22,13 +22,13 @@ interface FeatureViewLineageTabProps {
 
 const FeatureViewLineageTab = ({ data }: FeatureViewLineageTabProps) => {
   const registryUrl = useContext(RegistryPathContext);
+  const { featureViewName, projectName } = useParams();
   const {
     isLoading,
     isSuccess,
     isError,
     data: registryData,
-  } = useLoadRegistry(registryUrl);
-  const { featureViewName } = useParams();
+  } = useLoadRegistry(registryUrl, projectName);
   const [selectedPermissionAction, setSelectedPermissionAction] = useState("");
 
   const filterNode = {
diff --git a/ui/src/pages/feature-views/FeatureViewListingTable.tsx b/ui/src/pages/feature-views/FeatureViewListingTable.tsx
index cf0fc305f84..e865abe6e74 100644
--- a/ui/src/pages/feature-views/FeatureViewListingTable.tsx
+++ b/ui/src/pages/feature-views/FeatureViewListingTable.tsx
@@ -30,8 +30,10 @@ const FeatureViewListingTable = ({
       field: "name",
       sortable: true,
       render: (name: string, item: genericFVType) => {
+        // For "All Projects" view, link to the specific project
+        const itemProject = item.object?.spec?.project || projectName;
         return (
-          <EuiCustomLink to={`/p/${projectName}/feature-view/${name}`}>
+          <EuiCustomLink to={`/p/${itemProject}/feature-view/${name}`}>
             {name}{" "}
             {(item.type === "ondemand" && <EuiBadge>ondemand</EuiBadge>) ||
               (item.type === "stream" && <EuiBadge>stream</EuiBadge>)}
@@ -49,6 +51,16 @@ const FeatureViewListingTable = ({
     },
   ];
 
+  // Add Project column when viewing all projects
+  if (projectName === "all") {
+    columns.splice(1, 0, {
+      name: "Project",
+      render: (item: genericFVType) => {
+        return <span>{item.object?.spec?.project || "Unknown"}</span>;
+      },
+    });
+  }
+
   // Add columns if they come up in search
   tagKeysSet.forEach((key) => {
     columns.push({
diff --git a/ui/src/pages/feature-views/Index.tsx b/ui/src/pages/feature-views/Index.tsx
index 57ac597168b..b1c28895370 100644
--- a/ui/src/pages/feature-views/Index.tsx
+++ b/ui/src/pages/feature-views/Index.tsx
@@ -1,4 +1,5 @@
 import React, { useContext } from "react";
+import { useParams } from "react-router-dom";
 
 import {
   EuiPageTemplate,
@@ -29,7 +30,8 @@ import ExportButton from "../../components/ExportButton";
 
 const useLoadFeatureViews = () => {
   const registryUrl = useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const { projectName } = useParams();
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const data =
     registryQuery.data === undefined
diff --git a/ui/src/pages/features/FeatureListPage.tsx b/ui/src/pages/features/FeatureListPage.tsx
index 72428dde494..36087f98bc0 100644
--- a/ui/src/pages/features/FeatureListPage.tsx
+++ b/ui/src/pages/features/FeatureListPage.tsx
@@ -33,6 +33,7 @@ interface Feature {
   name: string;
   featureView: string;
   type: string;
+  project?: string;
   permissions?: any[];
 }
 
@@ -43,7 +44,10 @@ type FeatureColumn =
 const FeatureListPage = () => {
   const { projectName } = useParams();
   const registryUrl = useContext(RegistryPathContext);
-  const { data, isLoading, isError } = useLoadRegistry(registryUrl);
+  const { data, isLoading, isError } = useLoadRegistry(
+    registryUrl,
+    projectName,
+  );
   const [searchText, setSearchText] = useState("");
   const [selectedPermissionAction, setSelectedPermissionAction] = useState("");
 
@@ -95,23 +99,31 @@ const FeatureListPage = () => {
       name: "Feature Name",
       field: "name",
       sortable: true,
-      render: (name: string, feature: Feature) => (
-        <EuiCustomLink
-          to={`/p/${projectName}/feature-view/${feature.featureView}/feature/${name}`}
-        >
-          {name}
-        </EuiCustomLink>
-      ),
+      render: (name: string, feature: Feature) => {
+        // For "All Projects" view, link to the specific project
+        const itemProject = feature.project || projectName;
+        return (
+          <EuiCustomLink
+            to={`/p/${itemProject}/feature-view/${feature.featureView}/feature/${name}`}
+          >
+            {name}
+          </EuiCustomLink>
+        );
+      },
     },
     {
       name: "Feature View",
       field: "featureView",
       sortable: true,
-      render: (featureView: string) => (
-        <EuiCustomLink to={`/p/${projectName}/feature-view/${featureView}`}>
-          {featureView}
-        </EuiCustomLink>
-      ),
+      render: (featureView: string, feature: Feature) => {
+        // For "All Projects" view, link to the specific project
+        const itemProject = feature.project || projectName;
+        return (
+          <EuiCustomLink to={`/p/${itemProject}/feature-view/${featureView}`}>
+            {featureView}
+          </EuiCustomLink>
+        );
+      },
     },
     { name: "Type", field: "type", sortable: true },
     {
@@ -144,6 +156,18 @@ const FeatureListPage = () => {
     },
   ];
 
+  // Add Project column when viewing all projects
+  if (projectName === "all") {
+    columns.splice(1, 0, {
+      name: "Project",
+      field: "project",
+      sortable: true,
+      render: (project: string) => {
+        return <span>{project || "Unknown"}</span>;
+      },
+    });
+  }
+
   const onTableChange = ({ page, sort }: CriteriaWithPagination<Feature>) => {
     if (sort) {
       setSortField(sort.field as keyof Feature);
diff --git a/ui/src/pages/lineage/Index.tsx b/ui/src/pages/lineage/Index.tsx
index 24112ea8571..a3a9ca19296 100644
--- a/ui/src/pages/lineage/Index.tsx
+++ b/ui/src/pages/lineage/Index.tsx
@@ -16,8 +16,44 @@ import { useParams } from "react-router-dom";
 const LineagePage = () => {
   useDocumentTitle("Feast Lineage");
   const registryUrl = useContext(RegistryPathContext);
-  const { isLoading, isSuccess, isError, data } = useLoadRegistry(registryUrl);
   const { projectName } = useParams<{ projectName: string }>();
+  const { isLoading, isSuccess, isError, data } = useLoadRegistry(
+    registryUrl,
+    projectName,
+  );
+
+  // Show message for "All Projects" view
+  if (projectName === "all") {
+    return (
+      <EuiPageTemplate panelled>
+        <EuiPageTemplate.Section>
+          <EuiTitle size="l">
+            <h1>Lineage Visualization</h1>
+          </EuiTitle>
+          <EuiSpacer />
+          <EuiEmptyPrompt
+            iconType="branch"
+            title={<h2>Project Selection Required</h2>}
+            body={
+              <>
+                <p>
+                  Lineage visualization requires a specific project context to
+                  show the relationships between Feature Views, Entities, and
+                  Data Sources.
+                </p>
+                <p>
+                  <strong>
+                    Please select a specific project from the dropdown above
+                  </strong>{" "}
+                  to view its lineage graph.
+                </p>
+              </>
+            }
+          />
+        </EuiPageTemplate.Section>
+      </EuiPageTemplate>
+    );
+  }
 
   return (
     <EuiPageTemplate panelled>
diff --git a/ui/src/pages/permissions/Index.tsx b/ui/src/pages/permissions/Index.tsx
index 683d3dcdba0..76dde026e90 100644
--- a/ui/src/pages/permissions/Index.tsx
+++ b/ui/src/pages/permissions/Index.tsx
@@ -13,6 +13,7 @@ import {
   EuiFormRow,
 } from "@elastic/eui";
 import { useContext, useState } from "react";
+import { useParams } from "react-router-dom";
 import RegistryPathContext from "../../contexts/RegistryPathContext";
 import useLoadRegistry from "../../queries/useLoadRegistry";
 import PermissionsDisplay from "../../components/PermissionsDisplay";
@@ -20,7 +21,11 @@ import { filterPermissionsByAction } from "../../utils/permissionUtils";
 
 const PermissionsIndex = () => {
   const registryUrl = useContext(RegistryPathContext);
-  const { isLoading, isSuccess, isError, data } = useLoadRegistry(registryUrl);
+  const { projectName } = useParams();
+  const { isLoading, isSuccess, isError, data } = useLoadRegistry(
+    registryUrl,
+    projectName,
+  );
   const [selectedPermissionAction, setSelectedPermissionAction] = useState("");
 
   return (
diff --git a/ui/src/queries/useLoadRegistry.ts b/ui/src/queries/useLoadRegistry.ts
index 4354ec0e98e..e3f5ac87a1d 100644
--- a/ui/src/queries/useLoadRegistry.ts
+++ b/ui/src/queries/useLoadRegistry.ts
@@ -22,11 +22,12 @@ interface Feature {
   name: string;
   featureView: string;
   type: string;
+  project?: string;
 }
 
-const useLoadRegistry = (url: string) => {
+const useLoadRegistry = (url: string, projectName?: string) => {
   return useQuery(
-    `registry:${url}`,
+    `registry:${url}:${projectName || "all"}`,
     () => {
       return fetch(url, {
         headers: {
@@ -55,6 +56,78 @@ const useLoadRegistry = (url: string) => {
             objects.featureViews = [];
           }
 
+          // Filter objects by project if projectName is provided
+          // Skip filtering if projectName is "all" (All Projects view)
+          // Only filter if we detect that the registry contains multiple projects
+          if (projectName && projectName !== "all") {
+            // Check if the registry actually has multiple projects
+            const projectsInRegistry = new Set();
+            objects.featureViews?.forEach((fv: any) => {
+              if (fv?.spec?.project) projectsInRegistry.add(fv.spec.project);
+            });
+            objects.entities?.forEach((entity: any) => {
+              if (entity?.spec?.project)
+                projectsInRegistry.add(entity.spec.project);
+            });
+
+            // Only apply filtering if there are actually multiple projects in the registry
+            // OR if the projectName matches one of the projects in the registry
+            const shouldFilter =
+              projectsInRegistry.size > 1 ||
+              projectsInRegistry.has(projectName);
+
+            if (shouldFilter && projectsInRegistry.has(projectName)) {
+              if (objects.featureViews) {
+                objects.featureViews = objects.featureViews.filter(
+                  (fv: any) => fv?.spec?.project === projectName,
+                );
+              }
+              if (objects.entities) {
+                objects.entities = objects.entities.filter(
+                  (entity: any) => entity?.spec?.project === projectName,
+                );
+              }
+              if (objects.dataSources) {
+                objects.dataSources = objects.dataSources.filter(
+                  (ds: any) => ds?.project === projectName,
+                );
+              }
+              if (objects.featureServices) {
+                objects.featureServices = objects.featureServices.filter(
+                  (fs: any) => fs?.spec?.project === projectName,
+                );
+              }
+              if (objects.onDemandFeatureViews) {
+                objects.onDemandFeatureViews =
+                  objects.onDemandFeatureViews.filter(
+                    (odfv: any) => odfv?.spec?.project === projectName,
+                  );
+              }
+              if (objects.streamFeatureViews) {
+                objects.streamFeatureViews = objects.streamFeatureViews.filter(
+                  (sfv: any) => sfv?.spec?.project === projectName,
+                );
+              }
+              if (objects.savedDatasets) {
+                objects.savedDatasets = objects.savedDatasets.filter(
+                  (sd: any) => sd?.spec?.project === projectName,
+                );
+              }
+              if (objects.validationReferences) {
+                objects.validationReferences =
+                  objects.validationReferences.filter(
+                    (vr: any) => vr?.project === projectName,
+                  );
+              }
+              if (objects.permissions) {
+                objects.permissions = objects.permissions.filter(
+                  (perm: any) =>
+                    perm?.spec?.project === projectName || !perm?.spec?.project,
+                );
+              }
+            }
+          }
+
           if (
             process.env.NODE_ENV === "test" &&
             objects.featureViews.length === 0
@@ -107,32 +180,42 @@ const useLoadRegistry = (url: string) => {
                     feature.valueType != null
                       ? feast.types.ValueType.Enum[feature.valueType]
                       : "Unknown Type",
+                  project: fv?.spec?.project, // Include project from parent feature view
                 })) || [],
             ) || [];
 
-          let projectName =
-            process.env.NODE_ENV === "test"
-              ? "credit_scoring_aws"
-              : objects.projects &&
-                  objects.projects.length > 0 &&
-                  objects.projects[0].spec &&
-                  objects.projects[0].spec.name
-                ? objects.projects[0].spec.name
-                : objects.project
-                  ? objects.project
-                  : "credit_scoring_aws";
+          // Use the provided projectName parameter if available, otherwise try to determine from registry
+          let resolvedProjectName: string =
+            projectName === "all"
+              ? "All Projects"
+              : projectName ||
+                (process.env.NODE_ENV === "test"
+                  ? "credit_scoring_aws"
+                  : objects.projects &&
+                      objects.projects.length > 0 &&
+                      objects.projects[0].spec &&
+                      objects.projects[0].spec.name
+                    ? objects.projects[0].spec.name
+                    : objects.project
+                      ? objects.project
+                      : "credit_scoring_aws");
 
           let projectDescription = undefined;
-          if (
-            objects.projects &&
-            objects.projects.length > 0 &&
-            objects.projects[0].spec
-          ) {
-            projectDescription = objects.projects[0].spec.description;
+
+          // Find project description from the projects array
+          if (projectName === "all") {
+            projectDescription = "View data across all projects";
+          } else if (objects.projects && objects.projects.length > 0) {
+            const currentProject = objects.projects.find(
+              (p: any) => p?.spec?.name === resolvedProjectName,
+            );
+            if (currentProject?.spec) {
+              projectDescription = currentProject.spec.description;
+            }
           }
 
           return {
-            project: projectName,
+            project: resolvedProjectName,
             description: projectDescription,
             objects,
             mergedFVMap,
diff --git a/ui/src/queries/useLoadRelationshipsData.ts b/ui/src/queries/useLoadRelationshipsData.ts
index 6f65af7e764..c0b7f1c1a28 100644
--- a/ui/src/queries/useLoadRelationshipsData.ts
+++ b/ui/src/queries/useLoadRelationshipsData.ts
@@ -1,10 +1,12 @@
 import { useContext } from "react";
+import { useParams } from "react-router-dom";
 import RegistryPathContext from "../contexts/RegistryPathContext";
 import useLoadRegistry from "./useLoadRegistry";
 
 const useLoadRelationshipData = () => {
   const registryUrl = useContext(RegistryPathContext);
-  const registryQuery = useLoadRegistry(registryUrl);
+  const { projectName } = useParams();
+  const registryQuery = useLoadRegistry(registryUrl, projectName);
 
   const data =
     registryQuery.data === undefined