Monitor Databricks workspace clusters, job runs, SQL warehouses, and user details.
npx skills add https://github.com/rbutinar/ade-ops --skill databricks-status
Please help me install this Agent Skill. Skill: databricks-status Source: https://github.com/rbutinar/ade-ops/tree/main/.agents/skills/databricks-status Command: npx skills add https://github.com/rbutinar/ade-ops --skill databricks-status
This Skill simplifies the monitoring of a Databricks workspace, providing insights into clusters, recent job runs, SQL warehouses, and the current user.
Execute /databricks-status to retrieve a comprehensive status overview.
High-intent search queries and answers about installing and using this skill.
To check the operational status of your Databricks workspace, you can retrieve a comprehensive overview of clusters, recent job runs, SQL warehouses, and current user details. This provides immediate visibility into resource performance for routine health checks and troubleshooting.
Yes, you can retrieve customized views to monitor specific Databricks clusters and SQL warehouses. The Skill allows you to retrieve targeted information about individual clusters, job runs, warehouses, or user details instead of fetching the full workspace overview.
Accessing Databricks workspace health monitoring requires access to the Databricks Management Plane (MCP) and relevant Databricks workspace permissions. These prerequisites ensure you can securely retrieve operational data for clusters, job runs, and SQL warehouses.
Yes, this tool provides recent job runs status for Databricks troubleshooting. It monitors and reports on recent job runs alongside cluster states and SQL warehouses, making it suitable for promptly identifying resource performance issues and troubleshooting operational failures.
The best way to get a quick Databricks environment overview is to run a single command that reports on clusters, job runs, SQL warehouses, and user details. This approach provides immediate visibility into your workspace resources to ensure they are performing as expected.
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