Post by Rajagopal Senthil Kumar

Most Databricks users know how to create a cluster. But have you ever wondered what actually happens after clicking the “Start Cluster” button? Where are the machines created? Who installs Docker? How are Spark Driver and Executors started? Does Databricks use Kubernetes? Who manages scaling, health checks, and container orchestration behind the scenes? Many engineers work with All Purpose Clusters, Job Clusters, and SQL Warehouses every day, but very few understand the underlying compute architecture that powers them. To prepare for the Databricks Professional certification and deepen my understanding of the platform internals, I researched how Databricks orchestrates cloud infrastructure, Docker containers, Spark runtime components, and Kubernetes-based services behind the scenes. In this infographic, I explain: • How Databricks requests compute from AWS, Azure, and GCP • How VMs are provisioned and configured • How Docker containers host Spark Driver and Executors • The role of Databricks Runtime • How Kubernetes is used internally for orchestration • What happens when a cluster is created, scaled, and terminated • The complete lifecycle of an All Purpose Cluster One of the most important takeaways: Databricks does not own the compute infrastructure. Cloud providers create and manage the underlying virtual machines, while Databricks orchestrates, configures, monitors, and optimizes the entire data platform experience. Understanding these internals helps data engineers make better decisions around performance, cost optimization, scalability, troubleshooting, and platform architecture. References: Databricks Compute Documentation https://lnkd.in/gfsyhpCz Databricks Clusters https://lnkd.in/grrTUdQR Databricks Container Services https://lnkd.in/gEDcMXGt Apache Spark Architecture https://lnkd.in/gqVs4n8C Kubernetes Documentation https://lnkd.in/ggs3C6Gc #Databricks #ApacheSpark #DataEngineering #CloudArchitecture #AWS #Azure #GCP #Docker #Kubernetes #Lakehouse #BigData #DataPlatform #DataArchitect #AnalyticsEngineering #CloudComputing