From version 1.8 onwards, Kubernetes provides resource usage metrics, such as the container CPU and memory usage, through the Metrics API. These metrics can be directly accessed by users (for example, by using the kubectl top command) or used by controllers (for example, Horizontal Pod Autoscaler) in a cluster for decision-making. The specific component is metrics-server, which is used to substitute for heapster for providing the similar functions. heapster has been gradually abandoned since v1.11.
metrics-server is an aggregator for monitoring data of core cluster resources. You can quickly install this add-on on the CCE console.
After installing this add-on, you can create HPA policies. For details, see HPA Policies.
The official community project and documentation are available at https://github.com/kubernetes-sigs/metrics-server.
Parameter |
Description |
---|---|
Add-on Specifications |
Select Single, Custom, or HA for Add-on Specifications. |
Pods |
Number of pods that will be created to match the selected add-on specifications. If you select Custom, you can adjust the number of pods as required. |
Containers |
CPU and memory quotas of the container allowed for the selected add-on specifications. If you select Custom, you can adjust the container specifications as required. |
Parameter |
Description |
---|---|
Multi AZ |
|
Node Affinity |
|
Toleration |
Using both taints and tolerations allows (not forcibly) the add-on Deployment to be scheduled to a node with the matching taints, and controls the Deployment eviction policies after the node where the Deployment is located is tainted. The add-on adds the default tolerance policy for the node.kubernetes.io/not-ready and node.kubernetes.io/unreachable taints, respectively. The tolerance time window is 60s. For details, see Taints and Tolerations. |
Component |
Description |
Resource Type |
---|---|---|
metrics-server |
Aggregator for the monitored data of cluster core resources, which is used to collect and aggregate resource usage metrics obtained through the Metrics API in the cluster |
Deployment |