Databricks Best Practices for Cloud Data Engineering
Comprehensive guide to designing, securing, and optimizing Databricks environments for scalable, high-performance data engineering and analytics.
Architecture Design
Adopt Lakehouse architecture, use Delta Lake, and leverage Unity Catalog for governance.
Security
Enable SSO, enforce cluster policies, and encrypt data at rest and in transit.
Performance Optimization
Use autoscaling clusters, Photon runtime, and caching for optimal performance.
Cost Management
Use job clusters, auto-termination, and spot instances to reduce costs.
Deployment Strategies
Automate deployments with Terraform, implement CI/CD, and version control notebooks.
Integration Patterns
Integrate with cloud storage, use Delta Live Tables, and leverage MLflow for ML workflows.
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