Apache Spark on Kubernetes - Lessons Learned from Launching Millions of Spark Executors

Apache Spark on Kubernetes - Lessons Learned from Launching Millions of Spark Executors

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Varying Workload Pattern

8 of 18

8 of 18

Varying Workload Pattern

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Apache Spark on Kubernetes - Lessons Learned from Launching Millions of Spark Executors

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  1. 1 Intro
  2. 2 Data Platform
  3. 3 Elastic Self Service Spark
  4. 4 Code to Deployment
  5. 5 Security
  6. 6 Monitoring
  7. 7 Orchestration Architecture
  8. 8 Varying Workload Pattern
  9. 9 One Interface over Multi-Cloud
  10. 10 Optimize Kubernetes for Spark Workload
  11. 11 Granular Concurrency Check at Orchestration
  12. 12 Avoid Partially Running Applications
  13. 13 Timeout Partially Running Applications
  14. 14 Mitigate Cluster Storage Stress
  15. 15 Utilization-based Allocation Recommendation
  16. 16 Dynamic Allocation
  17. 17 Push-button Cloud Management
  18. 18 Scale up Spark on Kubernetes

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