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FAQ

Table of Contents

What metrics are exposed by the metrics server?

Metrics server collects resource usage metrics needed for autoscaling: CPU & Memory. Metric values use standard kubernetes units (m, Ki), same as those used to define pod requests and limits (Read more Meaning of CPU, Meaning of memory) Metrics server itself is not responsible for calculating metric values, this is done by Kubelet.

Why do the CPU values reported by Metrics Server differ from Prometheus/docker stats/top etc.?

Metrics Server reports CPU value optimized for horizontal scaling of pods. CPU is reported as the 15 seconds average usage.

Why do the memory values reported by Metrics Server differ from Prometheus/docker stats/top etc.?

Metrics Server reports memory value optimized for vertical autoscaling of pods. Memory is reported as the working set at the instant the metric was collected. In an ideal world, the "working set" is the amount of memory in-use that cannot be freed under memory pressure. However, calculation of the working set varies by host OS, and generally makes heavy use of heuristics to produce an estimate. It includes all anonymous (non-file-backed) memory since Kubernetes does not support swap. The metric typically also includes some cached (file-backed) memory, because the host OS cannot always reclaim such pages.

How does the metrics server calculate metrics?

Metrics Server itself doesn't calculate any metrics, it aggragetes values exposed by Kubelets so they are available in API that can by used for autoscaling. For any problem with metric values please contact SIG-Node.

How often is metrics server released?

There is no hard release schedule. A release is done after an important feature is implemented or upon request.

Can I run two instances of metrics-server?

Yes, but it will not provide any benefits. Both instances will scrape all nodes to collect metrics, but only one instance will be actively serving metrics API.

How to run metrics-server securely?

Suggested configuration:

  • Cluster with RBAC enabled
  • Kubelet read-only port port disabled
  • Validate kubelet certificate by mounting CA file and providing --kubelet-certificate-authority flag to metrics server
  • Avoid passing insecure flags to metrics server (--deprecated-kubelet-completely-insecure, --kubelet-insecure-tls)
  • Consider using your own certificates (--tls-cert-file, --tls-private-key-file)

How to run metric-server on different architecture?

Starting from v0.3.7 docker image k8s.gcr.io/metrics-server/metrics-server should support multiple architectures via Manifests List. List of supported architectures: amd64, arm, arm64, ppc64le, s390x.

What Kubernetes versions are supported?

Metrics server is tested against the last 3 Kubernetes versions.

How is resource utilization calculated?

Metrics server doesn't provide resource utilization metrics (e.g. percent of CPU used). Kubectl top and HPA calculate those values by themselves based on pod resource requests or node capacity.

How to autoscale Metrics Server?

Metrics server scales linearly vertically according to the number of nodes and pods in a cluster. This can be automated using addon-resizer.

Can I get other metrics beside CPU/Memory using Metrics Server?

No, metrics server was designed to provide metrics used for autoscaling.

What requests and limits should I set for metrics server?

Metrics server scales linearly according to the number of nodes and pods in cluster. For pod density of 30 pods per node:

  • CPU: 40mCore base + 0.5 mCore per node
  • Memory: 40MiB base + 4 MiB per node

For higher pod density you should be able to scale resources proportionally. We are not recommending setting CPU limits as metrics server needs more compute to generate certificates at bootstrap.

How large can clusters be?

Metrics Server was tested to run within clusters up to 5000 nodes with an average pod density of 30 pods per node.

How often metrics are scraped?

Default 60 seconds, can be changed using metrics-resolution flag. We are not recommending setting values below 15s, as this is the resolution of metrics calculated within Kubelet.