Introducing advanced Kubernetes control plane configuration in Amazon EKS

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Customers running large Amazon Elastic Kubernetes Service (Amazon EKS) clusters want to optimize pod placement strategies for higher resource utilization and lower compute costs. Teams running high-churn batch, continuous integration and continuous delivery (CI/CD), and artificial intelligence and machine learning (AI/ML) workloads want to customize resource lifecycle management settings such as event retention duration to reduce etcd storage pressure. And customers migrating from self-managed Kubernetes want to preserve scheduler settings they have tuned over the years. Previously, many of these needs meant building and maintaining your own solution, adding operational overhead and maintenance burden. Today, Amazon EKS introduces advanced Kubernetes control plane configuration. You can now set parameters on the API server, scheduler, and controller manager directly in Amazon EKS. You continue to receive the same Amazon EKS availability and performance characteristics. In this post, we walk through the feature, review the supported parameters, and then get hands-on with two walkthroughs: first, we configure pod placement strategies using the MostAllocated scoring strategy to prefer resource utilization over the default spreading behavior. Then, we configure event retention duration to balance debugging capabilities with storage efficiency. What you can configure With the scheduler customization, you can configure pod placement strategies to control how nodes are scored for pod scheduling. By default, the Kubernetes scheduler uses the LeastAllocated scoring strategy, …

Vollständiger Originalartikel ↗

• Betroffenheit im eigenen Stack prüfen: Versionen/Komponenten abgleichen.
• Originalquelle / Hersteller-Advisory lesen: https://aws.amazon.com/blogs/containers/introducing-advanced-kubernetes-control-plane-configuration-in-amazon-eks/
• Verfügbaren Patch oder Workaround einspielen und dokumentieren.