A CLI utility built using Typer, Locust, and the Looker Python SDK to execute load tests, collect embed observability metrics, and manage/cleanup Looker SSO embed users.

• Debug Diagnostics: Quickly test and verify your Looker API connection and SDK settings.
• Load Testing: Simulates concurrent users accessing dashboards, running queries, rendering PDFs/images, or loading cookieless embed environments.
• Observability Server: Hosts a local dashboard iframe server, launches automated users, tracks Looker iframe JS event timings (loaded, run:start, run:complete), and reports performance metrics.
• Embed User Cleanup: Batch deletes expired/old SSO embed users using concurrent thread pools to keep Looker instance user lists clean.

• Python 3.13 or higher
• uv (recommended Python package installer)
• Docker (optional, for containerization)
• Google Cloud SDK (gcloud) (optional, if pushing to GCP Artifact Registry)

Clone/copy the repository, navigate to the folder, and run:

# Install runtime dependencies
make install

# Install dev dependencies (pytest, pre-commit, etc.)
make dev-install

The CLI relies on standard Looker SDK environment variables. Create a .env file in the root of the project:

LOOKERSDK_BASE_URL="https://your-looker-instance.com:19999"
LOOKERSDK_CLIENT_ID="your_api_client_id"
LOOKERSDK_CLIENT_SECRET="your_api_client_secret"

Verify your configuration by running the debug check:

make run-debug

The main entry point is lkr.

# Debug credentials & check connectivity
uv run lkr load-test debug looker

# Run a dashboard load test for 5 minutes with 25 users
uv run lkr load-test dashboard --dashboard <dashboard_id> --model <model_name> --users 25 --run-time 5

uv run lkr load-test cookieless-embed-dashboard --dashboard <dashboard_id> --model <model_name> --users 25

uv run lkr load-test query --query <query_id> --model <model_name> --users 25

uv run lkr load-test render --dashboard <dashboard_id> --model <model_name> --result-format pdf

Starts a local web server to capture Looker javascript frontend metrics during simulated dashboard sessions:

uv run lkr load-test embed-observability --dashboard <dashboard_id> --port 4000

SSO embed logins create new users in Looker. Clean them up using concurrent batch deletion:

# Dry run to see how many users match the prefix (defaults to first name "Embed")
uv run lkr load-test delete-embed-users --first-name "Embed" --dry-run

# Execute deletion with a limit
uv run lkr load-test delete-embed-users --first-name "Embed" --no-dry-run --limit 500

To build the Docker image using the provided Dockerfile:

make build

Pass your .env configuration file to run CLI commands in the isolated environment:

docker run --rm -it --env-file .env lkr:latest load-test debug looker

Use the included Makefile for common development tasks:

• make test - Run pytest suites.
• make format - Format code and run pre-commit checks.
• make clean - Remove virtualenv, caches, and build artifacts.