~/lightning

Lightning Talk: How Jenga & Tetris Can Help Run More Containers with Lesser Costs & Downtime

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Describes a concrete implementation on Kubernetes that generates pod move and place recommendations using node and pod affinities, simulates migrations in-memory, and applies two strategies (singular recursive moves or multiple-container swaps) to defragment resources so a queued container fits. It measures imbalance with an entropy CPU/memory ratio, runs periodic swaps, and shows results on a real test cluster: roughly $5,000/month (≈30%) lower autoscaling cost while avoiding added nodes and reducing risk of CPU throttling and OOM restarts.

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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