databricks-pack

Configure Databricks CI/CD integration with GitHub Actions and Asset Bundles. Use when setting up automated testing, configuring CI pipelines, or integrating Databricks deployments into your build process. Trigger with phrases like "databricks CI", "databricks GitHub Actions", "databricks automated tests", "CI databricks", "databricks pipeline".

Diagnose and fix Databricks common errors and exceptions. Use when encountering Databricks errors, debugging failed jobs, or troubleshooting cluster and notebook issues. Trigger with phrases like "databricks error", "fix databricks", "databricks not working", "debug databricks", "spark error".

Execute Databricks primary workflow: Delta Lake ETL pipelines. Use when building data ingestion pipelines, implementing medallion architecture, or creating Delta Lake transformations. Trigger with phrases like "databricks ETL", "delta lake pipeline", "medallion architecture", "databricks data pipeline", "bronze silver gold".

Execute Databricks secondary workflow: MLflow model training and deployment. Use when building ML pipelines, training models, or deploying to production. Trigger with phrases like "databricks ML", "mlflow training", "databricks model", "feature store", "model registry".

Optimize Databricks costs with cluster policies, spot instances, and monitoring. Use when reducing cloud spend, implementing cost controls, or analyzing Databricks usage costs. Trigger with phrases like "databricks cost", "reduce databricks spend", "databricks billing", "databricks cost optimization", "cluster cost".

Implement Delta Lake data management patterns including GDPR, PII handling, and data lifecycle. Use when implementing data retention, handling GDPR requests, or managing data lifecycle in Delta Lake. Trigger with phrases like "databricks GDPR", "databricks PII", "databricks data retention", "databricks data lifecycle", "delete user data".

Collect Databricks debug evidence for support tickets and troubleshooting. Use when encountering persistent issues, preparing support tickets, or collecting diagnostic information for Databricks problems. Trigger with phrases like "databricks debug", "databricks support bundle", "collect databricks logs", "databricks diagnostic".

Deploy Databricks jobs and pipelines with Asset Bundles. Use when deploying jobs to different environments, managing deployments, or setting up deployment automation. Trigger with phrases like "databricks deploy", "asset bundles", "databricks deployment", "deploy to production", "bundle deploy".

Configure Databricks enterprise SSO, Unity Catalog RBAC, and organization management. Use when implementing SSO integration, configuring role-based permissions, or setting up organization-level controls with Unity Catalog. Trigger with phrases like "databricks SSO", "databricks RBAC", "databricks enterprise", "unity catalog permissions", "databricks SCIM".

Create a minimal working Databricks example with cluster and notebook. Use when starting a new Databricks project, testing your setup, or learning basic Databricks patterns. Trigger with phrases like "databricks hello world", "databricks example", "databricks quick start", "first databricks notebook", "create cluster".

Execute Databricks incident response procedures with triage, mitigation, and postmortem. Use when responding to Databricks-related outages, investigating job failures, or running post-incident reviews for pipeline failures. Trigger with phrases like "databricks incident", "databricks outage", "databricks down", "databricks on-call", "databricks emergency", "job failed".

Install and configure Databricks CLI and SDK authentication. Use when setting up a new Databricks integration, configuring tokens, or initializing Databricks in your project. Trigger with phrases like "install databricks", "setup databricks", "databricks auth", "configure databricks token", "databricks CLI".

Configure Databricks local development with dbx, Databricks Connect, and IDE. Use when setting up a local dev environment, configuring test workflows, or establishing a fast iteration cycle with Databricks. Trigger with phrases like "databricks dev setup", "databricks local", "databricks IDE", "develop with databricks", "databricks connect".

Execute comprehensive platform migrations to Databricks from legacy systems. Use when migrating from on-premises Hadoop, other cloud platforms, or legacy data warehouses to Databricks. Trigger with phrases like "migrate to databricks", "hadoop migration", "snowflake to databricks", "legacy migration", "data warehouse migration".

Configure Databricks across development, staging, and production environments. Use when setting up multi-environment deployments, configuring per-environment secrets, or implementing environment-specific Databricks configurations. Trigger with phrases like "databricks environments", "databricks staging", "databricks dev prod", "databricks environment setup", "databricks config by env".

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".

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".

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".

Apply production-ready Databricks SDK patterns for Python and REST API. Use when implementing Databricks integrations, refactoring SDK usage, or establishing team coding standards for Databricks. Trigger with phrases like "databricks SDK patterns", "databricks best practices", "databricks code patterns", "idiomatic databricks".

Apply Databricks security best practices for secrets and access control. Use when securing API tokens, implementing least privilege access, or auditing Databricks security configuration. Trigger with phrases like "databricks security", "databricks secrets", "secure databricks", "databricks token security", "databricks scopes".

Upgrade Databricks runtime versions and migrate between features. Use when upgrading DBR versions, migrating to Unity Catalog, or updating deprecated APIs and features. Trigger with phrases like "databricks upgrade", "DBR upgrade", "databricks migration", "unity catalog migration", "hive to unity".

Configure Databricks job notifications, webhooks, and event handling. Use when setting up Slack/Teams notifications, configuring alerts, or integrating Databricks events with external systems. Trigger with phrases like "databricks webhook", "databricks notifications", "databricks alerts", "job failure notification", "databricks slack".