Data Stack Monitoring Integrations

Monitor your ADF pipeline runs alongside Power BI refreshes to see exactly how orchestration failures ripple into report staleness.

Monitor Airflow DAG runs across self-hosted, MWAA, Astronomer, and Cloud Composer — detect failed, slow, and missing DAG runs before they cascade into stale downstream reports.

Databricks monitoring for Power BI teams — track job run failures, slow runs, and downstream BI impact when Databricks stops writing fresh data to your lakehouse.

Monitor Fabric pipelines, dataflows, and the fabric capacity metrics app in a unified view — track CU consumption alongside pipeline outcomes and downstream BI impact.

Connect dbt Cloud job runs to your Power BI datasets and instantly see when a failed dbt model causes stale or broken reports.

Monitor self-hosted dbt Core pipelines via CI/CD webhook and manifest lineage — without needing dbt Cloud.

See when Snowflake query performance or availability issues are causing slow or failed Power BI refreshes, before users notice stale reports.

Monitor Power BI datasets that source from Azure SQL Database or Azure SQL Managed Instance — catch credential, timeout, and connection failures before they surface as stale reports.

Track Power BI refreshes that connect to on-premises or Azure-hosted SQL Server through the data gateway and diagnose exactly why they fail.

Monitor Power BI datasets connected to PostgreSQL — whether on-premises, AWS RDS, Azure Database for PostgreSQL, or Google Cloud SQL.

Monitor Power BI datasets that read from SharePoint Online lists or Excel files stored on SharePoint — and catch authentication and permission changes before they break reports.

Monitor Power BI datasets that read from Azure Blob Storage or Azure Data Lake Storage Gen2 — including Direct Lake datasets on Fabric lakehouses.

Monitor your on-premises data gateway health, job queue depth, and refresh failures — the gateway is the critical bridge between Power BI Service and all your on-prem data sources.