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Authors: Chao Chen, Geeta Gharpure
2023-04-19

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Operational issues and their mitigations in running etcd
  • Database size exceeding
  • Revision divergence
  • Out of memory panic
  • Timeouts due to defrag
  • Oversized requests
Authors: Rick Spencer, Wojciech Kocjan
2022-05-18

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The presentation discusses the incident response and recovery process of a company's Kubernetes cluster. The company used Valero to recover the cluster after a Git revert caused data loss. The presentation also covers the company's decision to commit generated files in their CD process and the importance of prioritizing data protection.
  • Valero was used to recover the Kubernetes cluster after a Git revert caused data loss
  • Committing generated files in the CD process is a safer way to do things and allows for easier tracking of changes
  • Prioritizing data protection is crucial and should always be a top priority
  • The decision to use Valero or redeploy depends on the type of data and how often it changes
Authors: Marcin Wielgus, Joseph Burnett
2021-10-14

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An overview of autoscaling features in Kubernetes, covering horizontal, vertical, and cluster autoscalers, and upcoming features like the new HPA v2 stable API and support for alternative recommenders in VPA.
  • SIG Auto Scaling is responsible for horizontal and vertical polynomial scaling, cluster proportional system component auto scaling, and cluster autoscaler.
  • Horizontal Pod Autoscaler (HPA) scales in and out based on pre-defined metrics, while Vertical Pod Autoscaler (VPA) adjusts resources for workloads that don't necessarily scale horizontally.
  • Cluster autoscaler adjusts the number of nodes in any of the node pools that are configured.
  • The new HPA v2 stable API and support for alternative recommenders in VPA are upcoming features.
  • The autoscaling community can be accessed through Slack channels and weekly meetings.