databricks-pack

Set up comprehensive observability for Databricks with metrics, traces, and alerts. Use when implementing monitoring for Databricks jobs, setting up dashboards, or configuring alerting for pipeline health. Trigger with phrases like "databricks monitoring", "databricks metrics", "databricks observability", "monitor databricks", "databricks alerts", "databricks logging".

Implement Databricks API rate limiting, backoff, and idempotency patterns. Use when handling rate limit errors, implementing retry logic, or optimizing API request throughput for Databricks. Trigger with phrases like "databricks rate limit", "databricks throttling", "databricks 429", "databricks retry", "databricks backoff".

Implement Databricks reference architecture with best-practice project layout. Use when designing new Databricks projects, reviewing architecture, or establishing standards for Databricks applications. Trigger with phrases like "databricks architecture", "databricks best practices", "databricks project structure", "how to organize databricks", "databricks layout".

Optimize Databricks cluster and query performance. Use when jobs are running slowly, optimizing Spark configurations, or improving Delta Lake query performance. Trigger with phrases like "databricks performance", "spark tuning", "databricks slow", "optimize databricks", "cluster performance".

Execute Databricks production deployment checklist and rollback procedures. Use when deploying Databricks jobs to production, preparing for launch, or implementing go-live procedures. Trigger with phrases like "databricks production", "deploy databricks", "databricks go-live", "databricks launch checklist".