> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mage.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Monitoring

> You can monitor many metrics for each of your pipelines and blocks.

Use the Overview page to monitor aggregate pipeline run health across your
project. The monitoring panels show recent run status, failing runs, active
runs, and trigger activity for the selected time range.

<img alt="Monitoring" src="https://mage-ai.github.io/assets/monitoring.jpg" />

## Metrics

Here are the following metrics that are monitored for each pipeline and block:

* Pipeline runs completed successfully
* Pipeline runs failed
* Block runs completed successfully
* Block runs failed
* How long each block ran for
* CPU usage for Kubernetes block and pipeline runs in Mage Pro
* Memory usage for Kubernetes block and pipeline runs in Mage Pro
* *Data validation success for each block (coming soon)*
* *Data validation failure for each block (coming soon)*

For pipelines that run with the Kubernetes executor in Mage Pro, the pipeline
monitoring dashboard can show historical peak CPU and memory usage, sample
counts, and copied resource request and limit recommendations based on stored
run metrics. See [Monitoring with Prometheus](/observability/external/prometheus#kubernetes-resource-usage-in-mage-pro)
to set up Prometheus as the preferred resource usage source.

## Overview monitoring actions

The Overview page includes actions for the monitoring panels:

* **Fix runs** opens AI Sidekick with a prompt to investigate failing runs for
  the selected time range.
* **Analyze runs** opens AI Sidekick with a prompt to inspect active runs for
  the selected time range.
* **View triggers** opens the trigger list, preserving the selected compute
  cluster filter when one is active.