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張 旭

The problem with Docker and Alpine's package pinning | by Stefan Schindler | Medium - 0 views

stschindler.medium.com/s-package-pinning-18346593e891

docker image alpine

shared by 張 旭 on 13 Jul 22 - No Cached
  • What’s one of the biggest benefits of Docker? Clearly reproducibility: It doesn’t matter where you run your images, or when you run them: The result will always be the same.
  • For example, in Alpine 3.5, the package Node.js might be 2.0, and in Alpine 3.4 it’s 1.9. By pinning down the repository to Alpine 3.4, you will alwaysget Node.js 1.9, because Alpine 3.4 is an old version and not updated anymore.
  • Unfortunately Alpine Linux does not keep old packages.
  • 張 旭 on 13 Jul 22
     
    "What's one of the biggest benefits of Docker? Clearly reproducibility: It doesn't matter where you run your images, or when you run them: The result will always be the same."
張 旭

Considerations for large clusters | Kubernetes - 0 views

kubernetes.io/...cluster-large

kubernetes

shared by 張 旭 on 24 Mar 22 - No Cached
  • A cluster is a set of nodes (physical or virtual machines) running Kubernetes agents, managed by the control plane.
  • Kubernetes v1.23 supports clusters with up to 5000 nodes.
  • criteria: No more than 110 pods per node No more than 5000 nodes No more than 150000 total pods No more than 300000 total containers
  • ...14 more annotations...
  • In-use IP addresses
  • run one or two control plane instances per failure zone, scaling those instances vertically first and then scaling horizontally after reaching the point of falling returns to (vertical) scale.
  • Kubernetes nodes do not automatically steer traffic towards control-plane endpoints that are in the same failure zone
  • store Event objects in a separate dedicated etcd instance.
  • start and configure additional etcd instance
  • Kubernetes resource limits help to minimize the impact of memory leaks and other ways that pods and containers can impact on other components.
  • Addons' default limits are typically based on data collected from experience running each addon on small or medium Kubernetes clusters.
  • When running on large clusters, addons often consume more of some resources than their default limits.
  • Many addons scale horizontally - you add capacity by running more pods
  • The VerticalPodAutoscaler can run in recommender mode to provide suggested figures for requests and limits.
  • Some addons run as one copy per node, controlled by a DaemonSet: for example, a node-level log aggregator.
  • VerticalPodAutoscaler is a custom resource that you can deploy into your cluster to help you manage resource requests and limits for pods.
  • The cluster autoscaler integrates with a number of cloud providers to help you run the right number of nodes for the level of resource demand in your cluster.
  • The addon resizer helps you in resizing the addons automatically as your cluster's scale changes.
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