Spark on Kubernetes is growing in popularity due to improved isolation, better resource sharing, and the ability to leverage homogeneous and cloud-native infrastructure for the entire stack. However, running Spark on Kubernetes in a stable, performant, cost-efficient, and secure manner still presents complex challenges. In this webinar, Alex Pierce discusses the key performance metrics to focus on when monitoring and optimizing Spark performance on Kubernetes. Topics include: - Automation and observability for lowering costs and improving performance - Deploying, managing, monitoring, and simplifying Spark on Kubernetes: big data application monitoring, platform monitoring, and dynamic optimization - Configuring for performance and efficiency - Spark app-level dynamic allocation and cluster level autoscaling - The fastest way to improve Spark on Kubernetes performance