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Volcano

v1.13.2Orchestration & Management
2026年3月30日

Volcano v1.13.2 is a focused patch release fixing five bugs: a panic in NUMA resource handling, GPU resource errors, scheduler snapshot corruption, and incorrect terminating pod behavior in jobs.

  • breakingScheduler snapshot mutation bug can corrupt scheduling decisions — upgrade now

    The shared mutable objects bug in scheduler snapshot clones (PR #5093) is the most serious fix here. If multiple scheduling cycles inadvertently share state, you get non-deterministic scheduling behavior that's extremely hard to diagnose. Any cluster running GPU or multi-task batch jobs under load should treat this as urgent. Upgrade from v1.13.1 to v1.13.2 immediately.

  • securityPanic in NUMA snapshot could crash the scheduler — patch before scaling NUMA workloads

    A nil pointer / concurrent-write panic in NUMA resource info updating during snapshots can bring down the volcano-scheduler process. On NUMA-aware clusters, this means scheduling halts entirely until the pod restarts. If you're running topology-aware workloads, don't wait — patch to v1.13.2 before expanding those workloads.

  • enhancementGPU resource fix prevents ghost allocations on GPU nodes

    The GPU resource error fix addresses incorrect resource accounting that could lead to nodes appearing over-allocated or under-utilized. If you've noticed GPU pods stuck in Pending despite apparent capacity, or unexpected scheduling failures on GPU nodes, this patch likely resolves it. After upgrading, force a reconciliation by restarting the scheduler pod to clear any stale resource state.

主な変更 (5)

  • Terminating pods now correctly stay within their job scope instead of being dropped prematurely
  • Fixed a potential panic when updating NUMA resource info during scheduler snapshot operations
  • GPU resource accounting errors corrected — miscounts could cause over- or under-scheduling of GPU workloads
  • Prometheus metrics client updated to fix reporting issues
  • Scheduler snapshot clones no longer share mutable objects, preventing subtle state corruption across scheduling cycles