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Recommended cluster node configurations

Last updated:2021-05-11 10:41:31

Cluster planning

Some customers prefer to configure small-capacity nodes when they create a Kubernetes cluster. Small-capacity nodes have the following disadvantages:

  • Network resources of the small-capacity nodes are limited.
  • If a small-capacity node is occupied by a container, the available resources of the node cannot be used to, for example, create another container or recover a failed container. When the number of small-capacity worker nodes increases, resources are wasted.

Large-capacity nodes have the following advantages:

  • Large-capacity nodes are assigned high network bandwidth. If your applications require high network bandwidth, the resource utilization is increased.
  • Container communication inside a node increases, resulting in decreased network transmission.
  • Image pull efficiency increases. Images can be used by multiple containers after they are pulled. On small-capacity nodes, images must be pulled frequently, affecting the speed of starting containers.

Recommended master node configurations

The capacity of a master node is subject to the cluster scale. A large cluster requires large-capacity master nodes. The following table describes the recommended master node configurations in different cluster scales.

Cluster scale (number of nodes) Capacity of a master node
0 to 100 4 CPU cores, 8 GB memory, and 50 GB SSD data disk or higher
100 to 300 8 CPU cores, 16 GB memory, and 50 GB SSD data disk or higher
300 to 500 16 CPU cores, 32 GB memory, and 100 GB SSD data disk or higher
500 to 1,000 32 CPU cores, 64 GB memory, and 100 GB SSD data disk or higher
> 1,000 Contact Kingsoft Cloud.

Worker node selection

  • To ensure stability of nodes, KCE reserves some resources on the nodes based on the node specifications for Kubernetes components, such as kubelet, kube-proxy, and docker. For more information, see Reserve resources in a cluster. We recommend that you select node configurations based on the reserved resources and your business requirements.

  • Determine the CPU-memory ratio based on your business type. If you need to run applications that require much memory, for example, Java applications, we recommend that you select KEC instances with a CPU-memory ratio of 1:8. If your applications are CPU intensive, you can select KEC instances with a CPU-memory ratio of 1:2. If you deploy different business applications together, we recommend that you attach labels to nodes of different instance types or configurations and schedule pods based on nodeAffinity.
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