Running Spark on Kubernetes in a stable, performant, cost-efficient, and secure manner presents complex challenges. Spark performance tuning on Kubernetes ensures you get the best performance by optimizing system resources and tuning configurations.
Join Pepperdata Field Engineer Alex Pierce as he discusses how to reduce the complexity of monitoring and managing Spark on Kubernetes with autonomous optimization and full-stack observability.
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
• What Spark on Kubernetes performance success looks like