A horizontal pod autoscaler, defined by a
specifies how the system should automatically increase or decrease the scale of
a replication controller or deployment configuration, based on metrics collected
from the pods that belong to that replication controller or deployment
In order to use horizontal pod autoscalers, your cluster administrator must have properly configured cluster metrics.
The following metrics are supported by horizontal pod autoscalers:
Percentage of the requested CPU
You can create a horizontal pod autoscaler with the
oc autoscale command and
specify the minimum and maximum number of pods you want to run, as well as the
CPU utilization your pods should target.
After a horizontal pod autoscaler is created, it begins attempting to query Heapster for metrics on the pods. It may take one to two minutes before Heapster obtains the initial metrics.
After metrics are available in Heapster, the horizontal pod autoscaler computes the ratio of the current metric utilization with the desired metric utilization, and scales up or down accordingly. The scaling will occur at a regular interval, but it may take one to two minutes before metrics make their way into Heapster.
For replication controllers, this scaling corresponds directly to the replicas
of the replication controller. For deployment configurations, scaling corresponds
directly to the replica count of the deployment configuration. Note that autoscaling
applies only to the latest deployment in the
OKD automatically accounts for resources and prevents unnecessary autoscaling
during resource spikes, such as during start up. Pods in the
0 CPU usage when scaling up and the autoscaler ignores the pods when scaling down.
Pods without known metrics have
0% CPU usage when scaling up and
100% CPU when scaling down.
This allows for more stability during the HPA decision. To use this feature, you must configure
checks to determine if a new pod is ready for use.
oc autoscale command and specify at least the maximum number of pods
you want to run at any given time. You can optionally specify the minimum number
of pods and the average CPU utilization your pods should target, otherwise those
are given default values from the OKD server.
$ oc autoscale dc/frontend --min 1 --max 10 --cpu-percent=80 deploymentconfig "frontend" autoscaled
The above example creates a horizontal pod autoscaler with the following definition:
apiVersion: extensions/v1beta1 kind: HorizontalPodAutoscaler metadata: name: frontend (1) spec: scaleRef: kind: DeploymentConfig (2) name: frontend (3) apiVersion: v1 (4) subresource: scale minReplicas: 1 (5) maxReplicas: 10 (6) cpuUtilization: targetPercentage: 80 (7)
|1||The name of this horizontal pod autoscaler object|
|2||The kind of object to scale|
|3||The name of the object to scale|
|4||The API version of the object to scale|
|5||The minimum number of replicas to which to scale down|
|6||The maximum number of replicas to which to scale up|
|7||The percentage of the requested CPU that each pod should ideally be using|
To view the status of a horizontal pod autoscaler:
$ oc get hpa/frontend NAME REFERENCE TARGET CURRENT MINPODS MAXPODS AGE frontend DeploymentConfig/default/frontend/scale 80% 79% 1 10 8d $ oc describe hpa/frontend Name: frontend Namespace: default Labels: <none> CreationTimestamp: Mon, 26 Oct 2015 21:13:47 -0400 Reference: DeploymentConfig/default/frontend/scale Target CPU utilization: 80% Current CPU utilization: 79% Min pods: 1 Max pods: 10