The Data Flow metrics architecture is designed around the Micrometer library - vendor-neutral application metrics facade.
The Spring Cloud Data Flow server leverages the Prometheus RSocket Proxy,
for monitoring of tasks, which are short lived, as well as long lived stream applications.
The RSocket based monitoring architecture is reusable across the Local, Kubernetes and Cloud Foundry platforms.
The prebuilt stream and task applications support the Prometheus Proxy RSocket monitoring architecture.
The stream-apps samples shows how to enable monitoring for custom built source, processor and sink apps.
The task-apps sample shows how to enable monitoring for custom built task apps.
The following image shows the general architecture of how the Stream applications are monitored:
and the same architecture is used for monitoring the tasks as well.
Prometheus is configured to scrape each rsocket-proxy instance. Proxies in turn use the RSocket connection to pull metrics from each application. The scraped metrics are then viewable through Grafana dashboards.
Following animated diagram shows the metrics collection flow:
