Manually scaling a compute machine set

You can add or remove an instance of a machine in a compute machine set.

If you need to modify aspects of a compute machine set outside of scaling, see Modifying a compute machine set.

Prerequisites

You can use the advanced machine management and scaling capabilities only in clusters where the Machine API is operational. Clusters with user-provisioned infrastructure require additional validation and configuration to use the Machine API.

Clusters with the infrastructure platform type none cannot use the Machine API. This limitation applies even if the compute machines that are attached to the cluster are installed on a platform that supports the feature. This parameter cannot be changed after installation.

To view the platform type for your cluster, run the following command:

  1. $ oc get infrastructure cluster -o jsonpath=’{.status.platform}’

Scaling a compute machine set manually

To add or remove an instance of a machine in a compute machine set, you can manually scale the compute machine set.

This guidance is relevant to fully automated, installer-provisioned infrastructure installations. Customized, user-provisioned infrastructure installations do not have compute machine sets.

Prerequisites

  • Install an OKD cluster and the oc command line.

  • Log in to oc as a user with cluster-admin permission.

Procedure

  1. View the compute machine sets that are in the cluster by running the following command:

    1. $ oc get machinesets -n openshift-machine-api

    The compute machine sets are listed in the form of <clusterid>-worker-<aws-region-az>.

  2. View the compute machines that are in the cluster by running the following command:

    1. $ oc get machine -n openshift-machine-api

  3. Set the annotation on the compute machine that you want to delete by running the following command:

    1. $ oc annotate machine/<machine_name> -n openshift-machine-api machine.openshift.io/delete-machine="true"

  4. Scale the compute machine set by running one of the following commands:

    1. $ oc scale --replicas=2 machineset <machineset> -n openshift-machine-api

    Or:

    1. $ oc edit machineset <machineset> -n openshift-machine-api

    You can alternatively apply the following YAML to scale the compute machine set:

    1. apiVersion: machine.openshift.io/v1beta1
    2. kind: MachineSet
    3. metadata:
    4.   name: <machineset>
    5.   namespace: openshift-machine-api
    6. spec:
    7.   replicas: 2

    You can scale the compute machine set up or down. It takes several minutes for the new machines to be available.

    By default, the machine controller tries to drain the node that is backed by the machine until it succeeds. In some situations, such as with a misconfigured pod disruption budget, the drain operation might not be able to succeed. If the drain operation fails, the machine controller cannot proceed removing the machine.

    You can skip draining the node by annotating machine.openshift.io/exclude-node-draining in a specific machine.

Verification

  • Verify the deletion of the intended machine by running the following command:

    1. $ oc get machines

The compute machine set deletion policy

Random, Newest, and Oldest are the three supported deletion options. The default is Random, meaning that random machines are chosen and deleted when scaling compute machine sets down. The deletion policy can be set according to the use case by modifying the particular compute machine set:

  1. spec:
  2.   deletePolicy: <delete_policy>
  3.   replicas: <desired_replica_count>

Specific machines can also be prioritized for deletion by adding the annotation machine.openshift.io/delete-machine=true to the machine of interest, regardless of the deletion policy.

By default, the OKD router pods are deployed on workers. Because the router is required to access some cluster resources, including the web console, do not scale the worker compute machine set to 0 unless you first relocate the router pods.

Custom compute machine sets can be used for use cases requiring that services run on specific nodes and that those services are ignored by the controller when the worker compute machine sets are scaling down. This prevents service disruption.

Additional resources