~/lightning

How Jenga & Tetris Can Help Run More Containers with Lesser Costs...

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Proposes a Kubernetes-focused rescheduler that simulates placement in memory and emits move-and-place recommendations using node/pod affinity APIs, with singular and multi-pod migration strategies that minimize total evicted capacity. Uses an entropy CPU/memory ratio to identify and swap imbalance-causing pods, accepts a scheduling time budget (example: 5 seconds) for pruning search, and reports a real test saving about $5,000/month (~30%) on clusters with >$2/hr nodes.

AI-written summary · about

  1. 0:00Container scheduling challenges
  2. 1:25Tetris for resource fragmentation
  3. 3:31Impact of fragmented resources
  4. 4:57Rescheduling strategies
  5. 6:22Jenga for resource imbalance
  6. 8:55Cost savings from balance
  7. 10:18Runtime scheduling constraints
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