1.5. Automatically adjust pod resource levels with the vertical pod autoscaler
The OpenShift Container Platform Vertical Pod Autoscaler Operator (VPA) automatically reviews the historic and current CPU and memory resources for containers in pods and can update the resource limits and requests based on the usage values it learns. The VPA uses individual custom resources (CR) to update all of the pods associated with a workload object, such as a Deployment, DeploymentConfig, StatefulSet, Job, DaemonSet, ReplicaSet, or ReplicationController, in a project.
The VPA helps you to understand the optimal CPU and memory usage for your pods and can automatically maintain pod resources through the pod lifecycle.
vertical pod autoscaler is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see https://access.redhat.com/support/offerings/techpreview/.
1.5.1. About the Vertical Pod Autoscaler Operator
The Vertical Pod Autoscaler Operator (VPA) is implemented as an API resource and a custom resource (CR). The CR determines the actions the Vertical Pod Autoscaler Operator should take with the pods associated with a specific workload object, such as a daemon set, replication controller, and so forth, in a project.
The VPA automatically computes historic and current CPU and memory usage for the containers in those pods and uses this data to determine optimized resource limits and requests to ensure that these pods are operating efficiently at all times. For example, the VPA reduces resources for pods that are requesting more resources than they are using and increases resources for pods that are not requesting enough.
The VPA automatically deletes any pods that are out of alignment with its recommendations one at a time, so that your applications can continue to serve requests with no downtime. The workload objects then re-deploy the pods with the original resource limits and requests. The VPA uses a mutating admission webhook to update the pods with optimized resource limits and requests before the pods are admitted to a node. If you do not want the VPA to delete pods, you can view the VPA resource limits and requests and manually update the pods as needed.
For example, if you have a pod that uses 50% of the CPU but only requests 10%, the VPA determines that the pod is consuming more CPU than requested and deletes the pod. The workload object, such as replica set, restarts the pods and the VPA updates the new pod with its recommended resources.
For developers, you can use the VPA to help ensure your pods stay up during periods of high demand by scheduling pods onto nodes that have appropriate resources for each pod.
Administrators can use the VPA to better utilize cluster resources, such as preventing pods from reserving more CPU resources than needed. The VPA monitors the resources that workloads are actually using and adjusts the resource requirements so capacity is available to other workloads. The VPA also maintains the ratios between limits and requests that are specified in initial container configuration.
If you stop running the VPA or delete a specific VPA CR in your cluster, the resource requests for the pods already modified by the VPA do not change. Any new pods get the resources defined in the workload object, not the previous recommendations made by the VPA.
1.5.2. Installing the Vertical Pod Autoscaler Operator
You can use the OpenShift Container Platform web console to install the Vertical Pod Autoscaler Operator (VPA).
Procedure
-
In the OpenShift Container Platform web console, click Operators
OperatorHub. - Choose VerticalPodAutoscaler from the list of available Operators, and click Install.
-
On the Install Operator page, ensure that the Operator recommended namespace option is selected. This installs the Operator in the mandatory
openshift-vertical-pod-autoscalernamespace, which is automatically created if it does not exist. - Click Install.
Verify the installation by listing the VPA Operator components:
-
Navigate to Workloads
Pods. -
Select the
openshift-vertical-pod-autoscalerproject from the drop-down menu and verify that there are four pods running. -
Navigate to Workloads
Deployments to verify that there are four deployments running.
-
Navigate to Workloads
Optional. Verify the installation in the OpenShift Container Platform CLI using the following command:
$ oc get all -n openshift-vertical-pod-autoscaler
The output shows four pods and four deplyoments:
Example output
NAME READY STATUS RESTARTS AGE pod/vertical-pod-autoscaler-operator-85b4569c47-2gmhc 1/1 Running 0 3m13s pod/vpa-admission-plugin-default-67644fc87f-xq7k9 1/1 Running 0 2m56s pod/vpa-recommender-default-7c54764b59-8gckt 1/1 Running 0 2m56s pod/vpa-updater-default-7f6cc87858-47vw9 1/1 Running 0 2m56s NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE service/vpa-webhook ClusterIP 172.30.53.206 <none> 443/TCP 2m56s NAME READY UP-TO-DATE AVAILABLE AGE deployment.apps/vertical-pod-autoscaler-operator 1/1 1 1 3m13s deployment.apps/vpa-admission-plugin-default 1/1 1 1 2m56s deployment.apps/vpa-recommender-default 1/1 1 1 2m56s deployment.apps/vpa-updater-default 1/1 1 1 2m56s NAME DESIRED CURRENT READY AGE replicaset.apps/vertical-pod-autoscaler-operator-85b4569c47 1 1 1 3m13s replicaset.apps/vpa-admission-plugin-default-67644fc87f 1 1 1 2m56s replicaset.apps/vpa-recommender-default-7c54764b59 1 1 1 2m56s replicaset.apps/vpa-updater-default-7f6cc87858 1 1 1 2m56s
1.5.3. About Using the Vertical Pod Autoscaler Operator
To use the Vertical Pod Autoscaler Operator (VPA), you create a VPA custom resource (CR) for a workload object in your cluster. The VPA learns and applies the optimal CPU and memory resources for the pods associated with that workload object. You can use a VPA with a deployment, stateful set, job, daemon set, replica set, or replication controller workload object. The VPA CR must be in the same project as the pods you want to monitor.
You use the VPA CR to associate a workload object and specify which mode the VPA operates in:
-
The
AutoandRecreatemodes automatically apply the VPA CPU and memory recommendations throughout the pod lifetime. The VPA deletes any pods in the project that are out of alignment with its recommendations. When redeployed by the workload object, the VPA updates the new pods with its recommendations. -
The
Initialmode automatically applies VPA recommendations only at pod creation. -
The
Offmode only provides recommended resource limits and requests, allowing you to manually apply the recommendations. Theoffmode does not update pods.
You can also use the CR to opt-out certain containers from VPA evaluation and updates.
For example, a pod has the following limits and requests:
resources:
limits:
cpu: 1
memory: 500Mi
requests:
cpu: 500m
memory: 100Mi
After creating a VPA that is set to auto, the VPA learns the resource usage and deletes the pod. When redeployed, the pod uses the new resource limits and requests:
resources:
limits:
cpu: 50m
memory: 1250Mi
requests:
cpu: 25m
memory: 262144kYou can view the VPA recommendations using the following command:
$ oc get vpa <vpa-name> --output yaml
After a few minutes, the output shows the recommendations for CPU and memory requests, similar to the following:
Example output
...
status:
...
recommendation:
containerRecommendations:
- containerName: frontend
lowerBound:
cpu: 25m
memory: 262144k
target:
cpu: 25m
memory: 262144k
uncappedTarget:
cpu: 25m
memory: 262144k
upperBound:
cpu: 262m
memory: "274357142"
- containerName: backend
lowerBound:
cpu: 12m
memory: 131072k
target:
cpu: 12m
memory: 131072k
uncappedTarget:
cpu: 12m
memory: 131072k
upperBound:
cpu: 476m
memory: "498558823"
...
The output shows the recommended resources, target, the minimum recommended resources, lowerBound, the highest recommended resources, upperBound, and the most recent resource recommendations, uncappedTarget.
The VPA uses the lowerBound and upperBound values to determine if a pod needs to be updated. If a pod has resource requests below the lowerBound values or above the upperBound values, the VPA terminates and recreates the pod with the target values.
1.5.3.1. Automatically applying VPA recommendations
To use the VPA to automatically update pods, create a VPA CR for a specific workload object with updateMode set to Auto or Recreate.
When the pods are created for the workload object, the VPA constantly monitors the containers to analyze their CPU and memory needs. The VPA deletes any pods that do not meet the VPA recommendations for CPU and memory. When redeployed, the pods use the new resource limits and requests based on the VPA recommendations, honoring any pod disruption budget set for your applications. The recommendations are added to the status field of the VPA CR for reference.
The workload object must specify a minimum of two replicas in order for the VPA to monitor and update the pods. If the workload object specifies one replica, the VPA does not delete the pod to prevent application downtime. You can manually delete the pod to use the recommended resources.
Example VPA CR for the Auto mode
apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
name: vpa-recommender
spec:
targetRef:
apiVersion: "apps/v1"
kind: Deployment 1
name: frontend 2
updatePolicy:
updateMode: "Auto" 3
- 1 1
- The type of workload object you want this VPA CR to manage.
- 2
- The name of the workload object you want this VPA CR to manage.
- 3
- Set the mode to
AutoorRecreate:-
Auto. The VPA assigns resource requests on pod creation and updates the existing pods by terminating them when the requested resources differ significantly from the new recommendation. -
Recreate. The VPA assigns resource requests on pod creation and updates the existing pods by terminating them when the requested resources differ significantly from the new recommendation. This mode should be used rarely, only if you need to ensure that the pods are restarted whenever the resource request changes.
-
There must be operating pods in the project before the VPA can determine recommended resources and apply the recommendations to new pods.
1.5.3.2. Automatically applying VPA recommendations on pod creation
To use the VPA to apply the recommended resources only when a pod is first deployed, create a VPA CR for a specific workload object with updateMode set to Initial.
Then, manually delete any pods associated with the workload object that you want to use the VPA recommendations. In the Initial mode, the VPA does not delete pods and does not update the pods as it learns new resource recommendations.
Example VPA CR for the Initial mode
apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
name: vpa-recommender
spec:
targetRef:
apiVersion: "apps/v1"
kind: Deployment 1
name: frontend 2
updatePolicy:
updateMode: "Initial" 3
There must be operating pods in the project before a VPA can determine recommended resources and apply the recommendations to new pods.
1.5.3.3. Manually applying VPA recommendations
To use the VPA to only determine the recommended CPU and memory values, create a VPA CR for a specific workload object with updateMode set to off.
When the pods are created for that workload object, the VPA analyzes the CPU and memory needs of the containers and records those recommendations in the status field of the VPA CR. The VPA does not update the pods as it determines new resource recommendations.
Example VPA CR for the Off mode
apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
name: vpa-recommender
spec:
targetRef:
apiVersion: "apps/v1"
kind: Deployment 1
name: frontend 2
updatePolicy:
updateMode: "Off" 3
You can view the recommendations using the following command.
$ oc get vpa <vpa-name> --output yaml
With the recommendations, you can edit the workload object to add CPU and memory requests, then delete and redeploy the pods using the recommended resources.
There must be operating pods in the project before a VPA can determine recommended resources.
1.5.3.4. Exempting containers from applying VPA recommendations
If your workload object has multiple containers and you do not want the VPA to evaluate and act on all of the containers, create a VPA CR for a specific workload object and add a resourcePolicy to opt-out specific containers.
When the VPA updates the pods with recommended resources, any containers with a resourcePolicy are not updated and the VPA does not present recommendations for those containers in the pod.
apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
name: vpa-recommender
spec:
targetRef:
apiVersion: "apps/v1"
kind: Deployment 1
name: frontend 2
updatePolicy:
updateMode: "Auto" 3
resourcePolicy: 4
containerPolicies:
- containerName: my-opt-sidecar
mode: "Off"- 1
- The type of workload object you want this VPA CR to manage.
- 2
- The name of the workload object you want this VPA CR to manage.
- 3
- Set the mode to
Auto,Recreate, orOff. TheRecreatemode should be used rarely, only if you need to ensure that the pods are restarted whenever the resource request changes. - 4
- Specify the containers you want to opt-out and set
modetoOff.
For example, a pod has two containers, the same resource requests and limits:
...
spec:
containers:
name: frontend
resources:
limits:
cpu: 1
memory: 500Mi
requests:
cpu: 500m
memory: 100Mi
...
name: backend
resources:
limits:
cpu: "1"
memory: 500Mi
requests:
cpu: 500m
memory: 100Mi
...
After launching a VPA CR with the backend container set to opt-out, the VPA terminates and recreates the pod with the recommended resources applied only to the frontend container:
...
spec:
containers:
name: frontend
resources:
limits:
cpu: 50m
memory: 1250Mi
requests:
cpu: 25m
memory: 262144k
...
name: backend
resources:
limits:
cpu: "1"
memory: 500Mi
requests:
cpu: 500m
memory: 100Mi
...1.5.4. Using the Vertical Pod Autoscaler Operator
You can use the Vertical Pod Autoscaler Operator (VPA) by creating a VPA custom resource (CR). The CR indicates which pods it should analyze and determines the actions the VPA should take with those pods.
Procedure
To create a VPA CR for a specific workload object:
Change to the project where the workload object you want to scale is located.
Create a VPA CR YAML file:
apiVersion: autoscaling.k8s.io/v1 kind: VerticalPodAutoscaler metadata: name: vpa-recommender spec: targetRef: apiVersion: "apps/v1" kind: Deployment 1 name: frontend 2 updatePolicy: updateMode: "Auto" 3 resourcePolicy: 4 containerPolicies: - containerName: my-opt-sidecar mode: "Off"- 1
- Specify the type of workload object you want this VPA to manage:
Deployment,StatefulSet,Job,DaemonSet,ReplicaSet, orReplicationController. - 2
- Specify the name of an existing workload object you want this VPA to manage.
- 3
- Specify the VPA mode:
-
autoto automatically apply the recommended resources on pods associated with the controller. The VPA terminates existing pods and creates new pods with the recommended resource limits and requests. -
recreateto automatically apply the recommended resources on pods associated with the workload object. The VPA terminates existing pods and creates new pods with the recommended resource limits and requests. Therecreatemode should be used rarely, only if you need to ensure that the pods are restarted whenever the resource request changes. -
initialto automatically apply the recommended resources when pods associated with the workload object are created. The VPA does not update the pods as it learns new resource recommendations. -
offto only generate resource recommendations for the pods associated with the workload object. The VPA does not update the pods as it learns new resource recommendations and does not apply the recommendations to new pods.
-
- 4
- Optional. Specify the containers you want to opt-out and set the mode to
Off.
Create the VPA CR:
$ oc create -f <file-name>.yaml
After a few moments, the VPA learns the resource usage of the containers in the pods associated with the workload object.
You can view the VPA recommendations using the following command:
$ oc get vpa <vpa-name> --output yaml
The output shows the recommendations for CPU and memory requests, similar to the following:
Example output
... status: ... recommendation: containerRecommendations: - containerName: frontend lowerBound: 1 cpu: 25m memory: 262144k target: 2 cpu: 25m memory: 262144k uncappedTarget: 3 cpu: 25m memory: 262144k upperBound: 4 cpu: 262m memory: "274357142" - containerName: backend lowerBound: cpu: 12m memory: 131072k target: cpu: 12m memory: 131072k uncappedTarget: cpu: 12m memory: 131072k upperBound: cpu: 476m memory: "498558823" ...
1.5.5. Uninstalling the Vertical Pod Autoscaler Operator
You can remove the Vertical Pod Autoscaler Operator (VPA) from your OpenShift Container Platform cluster. After uninstalling, the resource requests for the pods already modified by an existing VPA CR do not change. Any new pods get the resources defined in the workload object, not the previous recommendations made by the Vertical Pod Autoscaler Operator.
You can remove a specific VPA using the oc delete vpa <vpa-name> command. The same actions apply for resource requests as uninstalling the vertical pod autoscaler.
Prerequisites
- The Vertical Pod Autoscaler Operator must be installed.
Procedure
-
In the OpenShift Container Platform web console, click Operators
Installed Operators. - Switch to the openshift-vertical-pod-autoscaler project.
- Find the VerticalPodAutoscaler Operator and click the Options menu. Select Uninstall Operator.
- In the dialog box, click Uninstall.
