I built a free 11-tab Cost Observability Dashboard as a Databricks App — open source

[vijayakunuri1]

I built Databricks Cost Observability — a full-stack observability dashboard
that runs natively as a Databricks App and reads directly from system tables.
No data leaves your workspace, no external BI tools needed.

What it covers across 11 tabs:
• Executive spend KPIs + AI_FORECAST() contract-year projection
• ML-powered anomaly detection (Isolation Forest) with cost impact
• Compute right-sizing — clusters, warehouses, DBR version sprawl
• Per-user query attribution with 30/60/90-day cost breakdown
• AI Gateway token usage by model (GPT-4, Claude, Mixtral, LLaMA, DBRX)
• Unity Catalog permission graph (interactive — users, groups, SPs, catalogs)
• Job SLA tracking — success rates, failure trends, DLT pipeline health
• Data lineage (bronze→silver→gold), MLflow, model registry

Works on free-tier workspaces via MOCK_MODE — no system table access needed.
Deploys in one git push via GitHub Actions + Databricks Asset Bundle.

GitHub: https://github.com/vijayakunuri1/databricks-cost-observability

Would love feedback — especially from AWS/GCP/Azure users. Happy to take feature
requests via GitHub Issues.

[cyborg-de]

That is really good, would be better to get platform cost in it as well, like Azure costing for subscription triggered using cost api and saved to databricks tables. 

[vijayakunuri1 · Accepted solution]

Got a new feature added to include cloud cost (multi-cloud)

[vijayakunuri1]

The main tradeoff: Azure Cost Management API has a 1-2 day lag, so the data is never truly real-time, but that's fine for a cost observability use case. We can have a ingestion notebook would run daily to get those cost ingested. 
Azure Cost Management → Databricks tables → Dashboard tab