Explore best practices and potential pitfalls of running Apache Spark on Kubernetes in this 25-minute conference talk from Databricks. Dive into core concepts, setup procedures, and configuration tips for optimizing performance and resource sharing. Learn about Spark-app level dynamic allocation, cluster level autoscaling, and Kubernetes-specific considerations for data I/O performance. Discover monitoring and security best practices, as well as current limitations and planned future developments. Gain valuable insights from lessons learned while building a serverless Spark platform powered by Kubernetes, covering topics such as efficient resource usage, spot instance management, and security measures. Conclude with a high-level checklist to ensure successful implementation of Spark on Kubernetes in your data analytics infrastructure.