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