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Resource metrics pipeline
Resource usage metrics, such as container CPU and memory usage,
are available in Kubernetes through the Metrics API. These metrics can be accessed either directly
by the user with the
kubectl top command, or by a controller in the cluster, for example
Horizontal Pod Autoscaler, to make decisions.
The Metrics API
Through the Metrics API, you can get the amount of resource currently used by a given node or a given pod. This API doesn't store the metric values, so it's not possible, for example, to get the amount of resources used by a given node 10 minutes ago.
The API is no different from any other API:
- it is discoverable through the same endpoint as the other Kubernetes APIs under the path:
- it offers the same security, scalability, and reliability guarantees
The API is defined in k8s.io/metrics repository. You can find more information about the API there.
Measuring Resource Usage
CPU is reported as the average usage, in CPU cores, over a period of time. This value is derived by taking a rate over a cumulative CPU counter provided by the kernel (in both Linux and Windows kernels). The kubelet chooses the window for the rate calculation.
Memory is reported as the working set, in bytes, 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.
Metrics Server is a cluster-wide aggregator of resource usage data.
By default, it is deployed in clusters created by
as a Deployment object. If you use a different Kubernetes setup mechanism, you can deploy it using the provided
deployment components.yaml file.
Learn more about the metrics server in the design doc.