New
Feature
Introducing Resource Quotas & Limits for Spark Jobs! 🚀
We’ve added Kubernetes Resource Quotas, CPU Limit Range, and Memory Limit Range to Ilum, giving you granular control over resource allocation within your cluster or namespace. Now, you can isolate workloads, prevent resource overuse, and ensure fair distribution across teams.
With this update, you can set per-job CPU and memory limits, so no more worrying about a single user consuming 1TB of RAM and starving other workloads. Instead, each team can have its own dedicated and controlled resource space, improving stability, efficiency, and cost management.
Key Improvements:
- Namespace-Level Resource Quotas – Define team-specific resource limits to ensure fair usage across the cluster.
- CPU & Memory Limit Ranges – Set per-job CPU and memory caps to prevent a single workload from overwhelming the system.
- Isolated Workspaces – Assign dedicated resource pools per team, avoiding conflicts and ensuring predictable performance.
- Better Cost Control & Stability – Keep Spark workloads optimized and prevent unexpected cluster slowdowns.
