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This section describes monitoring and observability features for Lakeflow Declarative Pipelines.
| Topic | Description |
|---|---|
| Monitor using the UI | Observe the progress and status of pipeline updates, and alert on the success or failure. View metrics for streaming sources, like Apache Kafka and Auto Loader. |
| Event log | Extract detailed information on pipeline updates such as data lineage, data quality metrics, and resource usage using the Lakeflow Declarative Pipelines event log. Additionally, see the schema for the event log. |
| Query history | Inspect and diagnose query performance by looking at the query history. |
| Custom monitoring | Define custom actions to take when specific events occur using event hooks. |
Additionally, there are troubleshooting topics for specific scenarios.
| Topic | Description |
|---|---|
| Recover a Lakeflow Declarative Pipelines from streaming checkpoint failure | Recover a pipeline that has an invalid or corrupted streaming checkpoint. |
| Fixing high initialization times in Lakeflow Declarative Pipelines | Fix high initialization times for a pipeline by splitting and load balancing flows across pipelines. |