databricks-jobs

You can automate Databricks Jobs lifecycle management by describing the desired task, such as creating or running a job, which the skill then guides across CLI, Python SDK, or Asset Bundles. This provides a unified, discoverable interface to replace repetitive manual configuration.

Yes, you can configure cron schedules and triggers for Databricks Jobs. The automation skill allows you to define schedules and set up notifications to automate monitoring and alerting for your orchestrated data workflows.

The best way to manage Databricks Jobs as code is by integrating with Databricks Asset Bundles. This approach manages jobs as shareable resources, applying consistent practices and governance across your data orchestration workflows.

Yes, this approach works with both the Databricks CLI and Python SDK. It provides a single discoverable skill to create, list, run, update, and delete jobs, ensuring consistent practices whether you use the CLI, SDK, or Asset Bundles.

You set up notifications and monitoring for Databricks Jobs by configuring them during the job creation or update process. The automation skill helps define alerting rules and monitoring configurations to track your orchestrated data workflows effectively.