compute
Power BI Monitoring for Databricks
Databricks jobs are increasingly the compute layer behind Power BI datasets — they run transformations, write Delta tables, and prepare data for reporting. When a Databricks job fails or runs slower than usual, downstream Power BI datasets refresh against stale or incomplete data without any visible error. MetricSign monitors both layers and surfaces the connection.
What you can monitor
- Detect when a Databricks job that feeds a Power BI dataset fails before the dataset refreshes against stale data
- Alert when a job takes significantly longer than its historical baseline (slow job = late data)
- Visualize the chain from Databricks job → Delta table → Power BI model → reports
- Correlate Power BI refresh failures with concurrent Databricks job failures on the same schedule
How MetricSign helps
01Databricks job run monitoring with slow-run detection (MAD-based baseline)
02Automatic job-to-dataset linkage via workspace and table naming
03Incident creation for job_failed and job_slow events
04Chain view connecting Databricks runs to dependent Power BI reports
MetricSign vs alternatives
Existing tools like Databricks native alerts, Azure Monitor for Databricks, Datadog are built for their own domain — not for connecting Databricks failures to downstream Power BI report health. MetricSign bridges that gap: you get one incident feed that covers both layers without switching between dashboards.
Alternatives
—Databricks native alerts
—Azure Monitor for Databricks
—Datadog
MetricSign
✓Covers DBX and Power BI in one view
✓Chain visualization from source to report
✓One incident feed, not multiple alert tools
✓Free to start, no credit card required