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Qiming Teng
2020-08-07 16:46:52 +08:00
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content/en/docs/tasks/debug-application-cluster/resource-usage-monitoring.md
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@@ -10,29 +10,32 @@ title: Tools for Monitoring Resources
To scale an application and provide a reliable service, you need to
understand how the application behaves when it is deployed. You can examine
application performance in a Kubernetes cluster by examining the containers,
[pods](/docs/user-guide/pods), [services](/docs/user-guide/services), and
[pods](/docs/concepts/workloads/pods/),
[services](/docs/concepts/services-networking/service/), and
the characteristics of the overall cluster. Kubernetes provides detailed
information about an application's resource usage at each of these levels.
This information allows you to evaluate your application's performance and
where bottlenecks can be removed to improve overall performance.
<!-- body -->
In Kubernetes, application monitoring does not depend on a single monitoring solution. On new clusters, you can use [resource metrics](#resource-metrics-pipeline) or [full metrics](#full-metrics-pipeline) pipelines to collect monitoring statistics.
In Kubernetes, application monitoring does not depend on a single monitoring solution.
On new clusters, you can use [resource metrics](#resource-metrics-pipeline) or
[full metrics](#full-metrics-pipeline) pipelines to collect monitoring statistics.
## Resource metrics pipeline
The resource metrics pipeline provides a limited set of metrics related to
cluster components such as the [Horizontal Pod Autoscaler](/docs/tasks/run-application/horizontal-pod-autoscale) controller, as well as the `kubectl top` utility.
cluster components such as the
[Horizontal Pod Autoscaler](/docs/tasks/run-application/horizontal-pod-autoscale/)
controller, as well as the `kubectl top` utility.
These metrics are collected by the lightweight, short-term, in-memory
[metrics-server](https://github.com/kubernetes-incubator/metrics-server) and
are exposed via the `metrics.k8s.io` API.
metrics-server discovers all nodes on the cluster and
queries each node's
[kubelet](/docs/reference/command-line-tools-reference/kubelet) for CPU and
[kubelet](/docs/reference/command-line-tools-reference/kubelet/) for CPU and
memory usage. The kubelet acts as a bridge between the Kubernetes master and
the nodes, managing the pods and containers running on a machine. The kubelet
translates each pod into its constituent containers and fetches individual