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Authors: Maciek Pytel
2023-04-20

tldr - powered by Generative AI

The presentation discusses the reliability of running Cluster Autoscaler in production and provides insights on monitoring and debugging tools.
  • Cluster Autoscaler's primary job is to ensure that all pods can schedule
  • Metrics such as pending pod metrics are useful for monitoring Cluster Autoscaler's performance
  • Cluster Autoscaler should be run on dedicated nodes or on the control plane VMs to prevent issues with scaling down
  • Testing configurations before using them in production is recommended
  • Ignoring certain flags can have significant side effects
  • Auto scaling can vary significantly at scale and should be tested