1. Documentation
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Postinstallation cluster tasks

After installing OKD, you can further expand and customize your cluster to your requirements.

Available cluster customizations

You complete most of the cluster configuration and customization after you deploy your OKD cluster. A number of configuration resources are available.

If you install your cluster on IBM Z®, not all features and functions are available.

You modify the configuration resources to configure the major features of the cluster, such as the image registry, networking configuration, image build behavior, and the identity provider.

For current documentation of the settings that you control by using these resources, use the oc explain command, for example oc explain builds --api-version=config.openshift.io/v1

Cluster configuration resources

All cluster configuration resources are globally scoped (not namespaced) and named cluster.

Resource name Description

apiserver.config.openshift.io

Provides API server configuration such as certificates and certificate authorities.

authentication.config.openshift.io

Controls the identity provider and authentication configuration for the cluster.

build.config.openshift.io

Controls default and enforced configuration for all builds on the cluster.

console.config.openshift.io

Configures the behavior of the web console interface, including the logout behavior.

featuregate.config.openshift.io

Enables FeatureGates so that you can use Tech Preview features.

image.config.openshift.io

Configures how specific image registries should be treated (allowed, disallowed, insecure, CA details).

ingress.config.openshift.io

Configuration details related to routing such as the default domain for routes.

oauth.config.openshift.io

Configures identity providers and other behavior related to internal OAuth server flows.

project.config.openshift.io

Configures how projects are created including the project template.

proxy.config.openshift.io

Defines proxies to be used by components needing external network access. Note: not all components currently consume this value.

scheduler.config.openshift.io

Configures scheduler behavior such as profiles and default node selectors.

Operator configuration resources

These configuration resources are cluster-scoped instances, named cluster, which control the behavior of a specific component as owned by a particular Operator.

Resource name Description

consoles.operator.openshift.io

Controls console appearance such as branding customizations

config.imageregistry.operator.openshift.io

Configures OpenShift image registry settings such as public routing, log levels, proxy settings, resource constraints, replica counts, and storage type.

config.samples.operator.openshift.io

Configures the Samples Operator to control which example image streams and templates are installed on the cluster.

Additional configuration resources

These configuration resources represent a single instance of a particular component. In some cases, you can request multiple instances by creating multiple instances of the resource. In other cases, the Operator can use only a specific resource instance name in a specific namespace. Reference the component-specific documentation for details on how and when you can create additional resource instances.

Resource name Instance name Namespace Description

alertmanager.monitoring.coreos.com

main

openshift-monitoring

Controls the Alertmanager deployment parameters.

ingresscontroller.operator.openshift.io

default

openshift-ingress-operator

Configures Ingress Operator behavior such as domain, number of replicas, certificates, and controller placement.

Informational Resources

You use these resources to retrieve information about the cluster. Some configurations might require you to edit these resources directly.

Resource name Instance name Description

clusterversion.config.openshift.io

version

In OKD 4.16, you must not customize the ClusterVersion resource for production clusters. Instead, follow the process to update a cluster.

dns.config.openshift.io

cluster

You cannot modify the DNS settings for your cluster. You can check the DNS Operator status.

infrastructure.config.openshift.io

cluster

Configuration details allowing the cluster to interact with its cloud provider.

network.config.openshift.io

cluster

You cannot modify your cluster networking after installation. To customize your network, follow the process to customize networking during installation.

Adding worker nodes

After you deploy your OKD cluster, you can add worker nodes to scale cluster resources. There are different ways you can add worker nodes depending on the installation method and the environment of your cluster.

Adding worker nodes to installer-provisioned infrastructure clusters

For installer-provisioned infrastructure clusters, you can manually or automatically scale the MachineSet object to match the number of available bare-metal hosts.

To add a bare-metal host, you must configure all network prerequisites, configure an associated baremetalhost object, then provision the worker node to the cluster. You can add a bare-metal host manually or by using the web console.

Adding worker nodes to user-provisioned infrastructure clusters

For user-provisioned infrastructure clusters, you can add worker nodes by using a Fedora or FCOS ISO image and connecting it to your cluster using cluster Ignition config files. For RHEL worker nodes, the following example uses Ansible playbooks to add worker nodes to the cluster. For RHCOS worker nodes, the following example uses an ISO image and network booting to add worker nodes to the cluster.

Adding worker nodes to clusters managed by the Assisted Installer

For clusters managed by the Assisted Installer, you can add worker nodes by using the Red Hat OpenShift Cluster Manager console, the Assisted Installer REST API or you can manually add worker nodes using an ISO image and cluster Ignition config files.

Adding worker nodes to clusters managed by the multicluster engine for Kubernetes

For clusters managed by the multicluster engine for Kubernetes, you can add worker nodes by using the dedicated multicluster engine console.

Adjust worker nodes

If you incorrectly sized the worker nodes during deployment, adjust them by creating one or more new compute machine sets, scale them up, then scale the original compute machine set down before removing them.

Understanding the difference between compute machine sets and the machine config pool

MachineSet objects describe OKD nodes with respect to the cloud or machine provider.

The MachineConfigPool object allows MachineConfigController components to define and provide the status of machines in the context of upgrades.

The MachineConfigPool object allows users to configure how upgrades are rolled out to the OKD nodes in the machine config pool.

The NodeSelector object can be replaced with a reference to the MachineSet object.

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:

    $ oc get machinesets.machine.openshift.io -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:

    $ oc get machines.machine.openshift.io -n openshift-machine-api

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

    $ oc annotate machines.machine.openshift.io/<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:

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

    Or:

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

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

    apiVersion: machine.openshift.io/v1beta1
kind: MachineSet
metadata:
  name: <machineset>
  namespace: openshift-machine-api
spec:
  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:

    $ oc get machines.machine.openshift.io

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:

spec:
  deletePolicy: <delete_policy>
  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.

Creating default cluster-wide node selectors

You can use default cluster-wide node selectors on pods together with labels on nodes to constrain all pods created in a cluster to specific nodes.

With cluster-wide node selectors, when you create a pod in that cluster, OKD adds the default node selectors to the pod and schedules the pod on nodes with matching labels.

You configure cluster-wide node selectors by editing the Scheduler Operator custom resource (CR). You add labels to a node, a compute machine set, or a machine config. Adding the label to the compute machine set ensures that if the node or machine goes down, new nodes have the label. Labels added to a node or machine config do not persist if the node or machine goes down.

You can add additional key/value pairs to a pod. But you cannot add a different value for a default key.
Procedure

To add a default cluster-wide node selector:

  1. Edit the Scheduler Operator CR to add the default cluster-wide node selectors:

    $ oc edit scheduler cluster
    Example Scheduler Operator CR with a node selector
    apiVersion: config.openshift.io/v1
kind: Scheduler
metadata:
  name: cluster
...
spec:
  defaultNodeSelector: type=user-node,region=east (1)
  mastersSchedulable: false
    1 Add a node selector with the appropriate <key>:<value> pairs.

    After making this change, wait for the pods in the openshift-kube-apiserver project to redeploy. This can take several minutes. The default cluster-wide node selector does not take effect until the pods redeploy.

  2. Add labels to a node by using a compute machine set or editing the node directly:

    • Use a compute machine set to add labels to nodes managed by the compute machine set when a node is created:

      1. Run the following command to add labels to a MachineSet object:

        $ oc patch MachineSet <name> --type='json' -p='[{"op":"add","path":"/spec/template/spec/metadata/labels", "value":{"<key>"="<value>","<key>"="<value>"}}]'  -n openshift-machine-api (1)
        1 Add a <key>/<value> pair for each label.

        For example:

        $ oc patch MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c --type='json' -p='[{"op":"add","path":"/spec/template/spec/metadata/labels", "value":{"type":"user-node","region":"east"}}]'  -n openshift-machine-api

        You can alternatively apply the following YAML to add labels to a compute machine set:

        apiVersion: machine.openshift.io/v1beta1
kind: MachineSet
metadata:
  name: <machineset>
  namespace: openshift-machine-api
spec:
  template:
    spec:
      metadata:
        labels:
          region: "east"
          type: "user-node"

      2. Verify that the labels are added to the MachineSet object by using the oc edit command:

        For example:

        $ oc edit MachineSet abc612-msrtw-worker-us-east-1c -n openshift-machine-api
        Example MachineSet object
        apiVersion: machine.openshift.io/v1beta1
kind: MachineSet
  ...
spec:
  ...
  template:
    metadata:
  ...
    spec:
      metadata:
        labels:
          region: east
          type: user-node
  ...

      3. Redeploy the nodes associated with that compute machine set by scaling down to 0 and scaling up the nodes:

        For example:

        $ oc scale --replicas=0 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api
        $ oc scale --replicas=1 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api

      4. When the nodes are ready and available, verify that the label is added to the nodes by using the oc get command:

        $ oc get nodes -l <key>=<value>

        For example:

        $ oc get nodes -l type=user-node
        Example output
        NAME                                       STATUS   ROLES    AGE   VERSION
ci-ln-l8nry52-f76d1-hl7m7-worker-c-vmqzp   Ready    worker   61s   v1.29.4

    • Add labels directly to a node:

      1. Edit the Node object for the node:

        $ oc label nodes <name> <key>=<value>

        For example, to label a node:

        $ oc label nodes ci-ln-l8nry52-f76d1-hl7m7-worker-b-tgq49 type=user-node region=east

        You can alternatively apply the following YAML to add labels to a node:

        kind: Node
apiVersion: v1
metadata:
  name: <node_name>
  labels:
    type: "user-node"
    region: "east"

      2. Verify that the labels are added to the node using the oc get command:

        $ oc get nodes -l <key>=<value>,<key>=<value>

        For example:

        $ oc get nodes -l type=user-node,region=east
        Example output
        NAME                                       STATUS   ROLES    AGE   VERSION
ci-ln-l8nry52-f76d1-hl7m7-worker-b-tgq49   Ready    worker   17m   v1.29.4

Improving cluster stability in high latency environments using worker latency profiles

If the cluster administrator has performed latency tests for platform verification, they can discover the need to adjust the operation of the cluster to ensure stability in cases of high latency. The cluster administrator needs to change only one parameter, recorded in a file, which controls four parameters affecting how supervisory processes read status and interpret the health of the cluster. Changing only the one parameter provides cluster tuning in an easy, supportable manner.

The Kubelet process provides the starting point for monitoring cluster health. The Kubelet sets status values for all nodes in the OKD cluster. The Kubernetes Controller Manager (kube controller) reads the status values every 10 seconds, by default. If the kube controller cannot read a node status value, it loses contact with that node after a configured period. The default behavior is:

  1. The node controller on the control plane updates the node health to Unhealthy and marks the node Ready condition`Unknown`.

  2. In response, the scheduler stops scheduling pods to that node.

  3. The Node Lifecycle Controller adds a node.kubernetes.io/unreachable taint with a NoExecute effect to the node and schedules any pods on the node for eviction after five minutes, by default.

This behavior can cause problems if your network is prone to latency issues, especially if you have nodes at the network edge. In some cases, the Kubernetes Controller Manager might not receive an update from a healthy node due to network latency. The Kubelet evicts pods from the node even though the node is healthy.

To avoid this problem, you can use worker latency profiles to adjust the frequency that the Kubelet and the Kubernetes Controller Manager wait for status updates before taking action. These adjustments help to ensure that your cluster runs properly if network latency between the control plane and the worker nodes is not optimal.

These worker latency profiles contain three sets of parameters that are predefined with carefully tuned values to control the reaction of the cluster to increased latency. There is no need to experimentally find the best values manually.

You can configure worker latency profiles when installing a cluster or at any time you notice increased latency in your cluster network.

Understanding worker latency profiles

Worker latency profiles are four different categories of carefully-tuned parameters. The four parameters which implement these values are node-status-update-frequency, node-monitor-grace-period, default-not-ready-toleration-seconds and default-unreachable-toleration-seconds. These parameters can use values which allow you to control the reaction of the cluster to latency issues without needing to determine the best values by using manual methods.

Setting these parameters manually is not supported. Incorrect parameter settings adversely affect cluster stability.

All worker latency profiles configure the following parameters:

node-status-update-frequency

Specifies how often the kubelet posts node status to the API server.

node-monitor-grace-period

Specifies the amount of time in seconds that the Kubernetes Controller Manager waits for an update from a kubelet before marking the node unhealthy and adding the node.kubernetes.io/not-ready or node.kubernetes.io/unreachable taint to the node.

default-not-ready-toleration-seconds

Specifies the amount of time in seconds after marking a node unhealthy that the Kube API Server Operator waits before evicting pods from that node.

default-unreachable-toleration-seconds

Specifies the amount of time in seconds after marking a node unreachable that the Kube API Server Operator waits before evicting pods from that node.

The following Operators monitor the changes to the worker latency profiles and respond accordingly:

  • The Machine Config Operator (MCO) updates the node-status-update-frequency parameter on the worker nodes.

  • The Kubernetes Controller Manager updates the node-monitor-grace-period parameter on the control plane nodes.

  • The Kubernetes API Server Operator updates the default-not-ready-toleration-seconds and default-unreachable-toleration-seconds parameters on the control plane nodes.

Although the default configuration works in most cases, OKD offers two other worker latency profiles for situations where the network is experiencing higher latency than usual. The three worker latency profiles are described in the following sections:

Default worker latency profile

With the Default profile, each Kubelet updates its status every 10 seconds (node-status-update-frequency). The Kube Controller Manager checks the statuses of Kubelet every 5 seconds.

The Kubernetes Controller Manager waits 40 seconds (node-monitor-grace-period) for a status update from Kubelet before considering the Kubelet unhealthy. If no status is made available to the Kubernetes Controller Manager, it then marks the node with the node.kubernetes.io/not-ready or node.kubernetes.io/unreachable taint and evicts the pods on that node.

If a pod is on a node that has the NoExecute taint, the pod runs according to tolerationSeconds. If the node has no taint, it will be evicted in 300 seconds (default-not-ready-toleration-seconds and default-unreachable-toleration-seconds settings of the Kube API Server).

Profile Component Parameter Value

Default

kubelet

node-status-update-frequency

10s

Kubelet Controller Manager

node-monitor-grace-period

40s

Kubernetes API Server Operator

default-not-ready-toleration-seconds

300s

Kubernetes API Server Operator

default-unreachable-toleration-seconds

300s
Medium worker latency profile

Use the MediumUpdateAverageReaction profile if the network latency is slightly higher than usual.

The MediumUpdateAverageReaction profile reduces the frequency of kubelet updates to 20 seconds and changes the period that the Kubernetes Controller Manager waits for those updates to 2 minutes. The pod eviction period for a pod on that node is reduced to 60 seconds. If the pod has the tolerationSeconds parameter, the eviction waits for the period specified by that parameter.

The Kubernetes Controller Manager waits for 2 minutes to consider a node unhealthy. In another minute, the eviction process starts.

Profile Component Parameter Value

MediumUpdateAverageReaction

kubelet

node-status-update-frequency

20s

Kubelet Controller Manager

node-monitor-grace-period

2m

Kubernetes API Server Operator

default-not-ready-toleration-seconds

60s

Kubernetes API Server Operator

default-unreachable-toleration-seconds

60s
Low worker latency profile

Use the LowUpdateSlowReaction profile if the network latency is extremely high.

The LowUpdateSlowReaction profile reduces the frequency of kubelet updates to 1 minute and changes the period that the Kubernetes Controller Manager waits for those updates to 5 minutes. The pod eviction period for a pod on that node is reduced to 60 seconds. If the pod has the tolerationSeconds parameter, the eviction waits for the period specified by that parameter.

The Kubernetes Controller Manager waits for 5 minutes to consider a node unhealthy. In another minute, the eviction process starts.

Profile Component Parameter Value

LowUpdateSlowReaction

kubelet

node-status-update-frequency

1m

Kubelet Controller Manager

node-monitor-grace-period

5m

Kubernetes API Server Operator

default-not-ready-toleration-seconds

60s

Kubernetes API Server Operator

default-unreachable-toleration-seconds

60s

Using and changing worker latency profiles

To change a worker latency profile to deal with network latency, edit the node.config object to add the name of the profile. You can change the profile at any time as latency increases or decreases.

You must move one worker latency profile at a time. For example, you cannot move directly from the Default profile to the LowUpdateSlowReaction worker latency profile. You must move from the Default worker latency profile to the MediumUpdateAverageReaction profile first, then to LowUpdateSlowReaction. Similarly, when returning to the Default profile, you must move from the low profile to the medium profile first, then to Default.

You can also configure worker latency profiles upon installing an OKD cluster.
Procedure

To move from the default worker latency profile:

  1. Move to the medium worker latency profile:

    1. Edit the node.config object:

      $ oc edit nodes.config/cluster

    2. Add spec.workerLatencyProfile: MediumUpdateAverageReaction:

      Example node.config object
      apiVersion: config.openshift.io/v1
kind: Node
metadata:
  annotations:
    include.release.openshift.io/ibm-cloud-managed: "true"
    include.release.openshift.io/self-managed-high-availability: "true"
    include.release.openshift.io/single-node-developer: "true"
    release.openshift.io/create-only: "true"
  creationTimestamp: "2022-07-08T16:02:51Z"
  generation: 1
  name: cluster
  ownerReferences:
  - apiVersion: config.openshift.io/v1
    kind: ClusterVersion
    name: version
    uid: 36282574-bf9f-409e-a6cd-3032939293eb
  resourceVersion: "1865"
  uid: 0c0f7a4c-4307-4187-b591-6155695ac85b
spec:
  workerLatencyProfile: MediumUpdateAverageReaction (1)

# ...
      1 Specifies the medium worker latency policy.

      Scheduling on each worker node is disabled as the change is being applied.

  2. Optional: Move to the low worker latency profile:

    1. Edit the node.config object:

      $ oc edit nodes.config/cluster

    2. Change the spec.workerLatencyProfile value to LowUpdateSlowReaction:

      Example node.config object
      apiVersion: config.openshift.io/v1
kind: Node
metadata:
  annotations:
    include.release.openshift.io/ibm-cloud-managed: "true"
    include.release.openshift.io/self-managed-high-availability: "true"
    include.release.openshift.io/single-node-developer: "true"
    release.openshift.io/create-only: "true"
  creationTimestamp: "2022-07-08T16:02:51Z"
  generation: 1
  name: cluster
  ownerReferences:
  - apiVersion: config.openshift.io/v1
    kind: ClusterVersion
    name: version
    uid: 36282574-bf9f-409e-a6cd-3032939293eb
  resourceVersion: "1865"
  uid: 0c0f7a4c-4307-4187-b591-6155695ac85b
spec:
  workerLatencyProfile: LowUpdateSlowReaction (1)

# ...
      1 Specifies use of the low worker latency policy.

Scheduling on each worker node is disabled as the change is being applied.

Verification

  • When all nodes return to the Ready condition, you can use the following command to look in the Kubernetes Controller Manager to ensure it was applied:

    $ oc get KubeControllerManager -o yaml | grep -i workerlatency -A 5 -B 5
    Example output
    # ...
    - lastTransitionTime: "2022-07-11T19:47:10Z"
      reason: ProfileUpdated
      status: "False"
      type: WorkerLatencyProfileProgressing
    - lastTransitionTime: "2022-07-11T19:47:10Z" (1)
      message: all static pod revision(s) have updated latency profile
      reason: ProfileUpdated
      status: "True"
      type: WorkerLatencyProfileComplete
    - lastTransitionTime: "2022-07-11T19:20:11Z"
      reason: AsExpected
      status: "False"
      type: WorkerLatencyProfileDegraded
    - lastTransitionTime: "2022-07-11T19:20:36Z"
      status: "False"
# ...
    1 Specifies that the profile is applied and active.

To change the medium profile to default or change the default to medium, edit the node.config object and set the spec.workerLatencyProfile parameter to the appropriate value.

Managing control plane machines

Control plane machine sets provide management capabilities for control plane machines that are similar to what compute machine sets provide for compute machines. The availability and initial status of control plane machine sets on your cluster depend on your cloud provider and the version of OKD that you installed. For more information, see Getting started with control plane machine sets.

Creating infrastructure machine sets for production environments

You can create a compute machine set to create machines that host only infrastructure components, such as the default router, the integrated container image registry, and components for cluster metrics and monitoring. These infrastructure machines are not counted toward the total number of subscriptions that are required to run the environment.

In a production deployment, it is recommended that you deploy at least three compute machine sets to hold infrastructure components. Both OpenShift Logging and Red Hat OpenShift Service Mesh deploy Elasticsearch, which requires three instances to be installed on different nodes. Each of these nodes can be deployed to different availability zones for high availability. A configuration like this requires three different compute machine sets, one for each availability zone. In global Azure regions that do not have multiple availability zones, you can use availability sets to ensure high availability.

For information on infrastructure nodes and which components can run on infrastructure nodes, see Creating infrastructure machine sets.

To create an infrastructure node, you can use a machine set, assign a label to the nodes, or use a machine config pool.

For sample machine sets that you can use with these procedures, see Creating machine sets for different clouds.

Applying a specific node selector to all infrastructure components causes OKD to schedule those workloads on nodes with that label.

Creating a compute machine set

In addition to the compute machine sets created by the installation program, you can create your own to dynamically manage the machine compute resources for specific workloads of your choice.

Prerequisites

  • Deploy an OKD cluster.

  • Install the OpenShift CLI (oc).

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

Procedure

  1. Create a new YAML file that contains the compute machine set custom resource (CR) sample and is named <file_name>.yaml.

    Ensure that you set the <clusterID> and <role> parameter values.

  2. Optional: If you are not sure which value to set for a specific field, you can check an existing compute machine set from your cluster.

    1. To list the compute machine sets in your cluster, run the following command:

      $ oc get machinesets -n openshift-machine-api
      Example output
      NAME                                DESIRED   CURRENT   READY   AVAILABLE   AGE
agl030519-vplxk-worker-us-east-1a   1         1         1       1           55m
agl030519-vplxk-worker-us-east-1b   1         1         1       1           55m
agl030519-vplxk-worker-us-east-1c   1         1         1       1           55m
agl030519-vplxk-worker-us-east-1d   0         0                             55m
agl030519-vplxk-worker-us-east-1e   0         0                             55m
agl030519-vplxk-worker-us-east-1f   0         0                             55m

    2. To view values of a specific compute machine set custom resource (CR), run the following command:

      $ oc get machineset <machineset_name> \
  -n openshift-machine-api -o yaml
      Example output
      apiVersion: machine.openshift.io/v1beta1
kind: MachineSet
metadata:
  labels:
    machine.openshift.io/cluster-api-cluster: <infrastructure_id> (1)
  name: <infrastructure_id>-<role> (2)
  namespace: openshift-machine-api
spec:
  replicas: 1
  selector:
    matchLabels:
      machine.openshift.io/cluster-api-cluster: <infrastructure_id>
      machine.openshift.io/cluster-api-machineset: <infrastructure_id>-<role>
  template:
    metadata:
      labels:
        machine.openshift.io/cluster-api-cluster: <infrastructure_id>
        machine.openshift.io/cluster-api-machine-role: <role>
        machine.openshift.io/cluster-api-machine-type: <role>
        machine.openshift.io/cluster-api-machineset: <infrastructure_id>-<role>
    spec:
      providerSpec: (3)
        ...
      1 The cluster infrastructure ID.
      2 A default node label.

      For clusters that have user-provisioned infrastructure, a compute machine set can only create worker and infra type machines.
      3 The values in the <providerSpec> section of the compute machine set CR are platform-specific. For more information about <providerSpec> parameters in the CR, see the sample compute machine set CR configuration for your provider.

  3. Create a MachineSet CR by running the following command:

    $ oc create -f <file_name>.yaml
Verification

  • View the list of compute machine sets by running the following command:

    $ oc get machineset -n openshift-machine-api
    Example output
    NAME                                DESIRED   CURRENT   READY   AVAILABLE   AGE
agl030519-vplxk-infra-us-east-1a    1         1         1       1           11m
agl030519-vplxk-worker-us-east-1a   1         1         1       1           55m
agl030519-vplxk-worker-us-east-1b   1         1         1       1           55m
agl030519-vplxk-worker-us-east-1c   1         1         1       1           55m
agl030519-vplxk-worker-us-east-1d   0         0                             55m
agl030519-vplxk-worker-us-east-1e   0         0                             55m
agl030519-vplxk-worker-us-east-1f   0         0                             55m

    When the new compute machine set is available, the DESIRED and CURRENT values match. If the compute machine set is not available, wait a few minutes and run the command again.

Creating an infrastructure node

See Creating infrastructure machine sets for installer-provisioned infrastructure environments or for any cluster where the control plane nodes are managed by the machine API.

Requirements of the cluster dictate that infrastructure, also called infra nodes, be provisioned. The installer only provides provisions for control plane and worker nodes. Worker nodes can be designated as infrastructure nodes or application, also called app, nodes through labeling.

Procedure

  1. Add a label to the worker node that you want to act as application node:

    $ oc label node <node-name> node-role.kubernetes.io/app=""

  2. Add a label to the worker nodes that you want to act as infrastructure nodes:

    $ oc label node <node-name> node-role.kubernetes.io/infra=""

  3. Check to see if applicable nodes now have the infra role and app roles:

    $ oc get nodes

  4. Create a default cluster-wide node selector. The default node selector is applied to pods created in all namespaces. This creates an intersection with any existing node selectors on a pod, which additionally constrains the pod’s selector.

    If the default node selector key conflicts with the key of a pod’s label, then the default node selector is not applied.

    However, do not set a default node selector that might cause a pod to become unschedulable. For example, setting the default node selector to a specific node role, such as node-role.kubernetes.io/infra="", when a pod’s label is set to a different node role, such as node-role.kubernetes.io/master="", can cause the pod to become unschedulable. For this reason, use caution when setting the default node selector to specific node roles.

    You can alternatively use a project node selector to avoid cluster-wide node selector key conflicts.

    1. Edit the Scheduler object:

      $ oc edit scheduler cluster

    2. Add the defaultNodeSelector field with the appropriate node selector:

      apiVersion: config.openshift.io/v1
kind: Scheduler
metadata:
  name: cluster
spec:
  defaultNodeSelector: node-role.kubernetes.io/infra="" (1)
# ...
      1 This example node selector deploys pods on infrastructure nodes by default.

    3. Save the file to apply the changes.

You can now move infrastructure resources to the newly labeled infra nodes.

Additional resources

  • For information on how to configure project node selectors to avoid cluster-wide node selector key conflicts, see Project node selectors.

Creating a machine config pool for infrastructure machines

If you need infrastructure machines to have dedicated configurations, you must create an infra pool.

Creating a custom machine configuration pool overrides default worker pool configurations if they refer to the same file or unit.
Procedure

  1. Add a label to the node you want to assign as the infra node with a specific label:

    $ oc label node <node_name> <label>
    $ oc label node ci-ln-n8mqwr2-f76d1-xscn2-worker-c-6fmtx node-role.kubernetes.io/infra=

  2. Create a machine config pool that contains both the worker role and your custom role as machine config selector:

    $ cat infra.mcp.yaml
    Example output
    apiVersion: machineconfiguration.openshift.io/v1
kind: MachineConfigPool
metadata:
  name: infra
spec:
  machineConfigSelector:
    matchExpressions:
      - {key: machineconfiguration.openshift.io/role, operator: In, values: [worker,infra]} (1)
  nodeSelector:
    matchLabels:
      node-role.kubernetes.io/infra: "" (2)
    1 Add the worker role and your custom role.
    2 Add the label you added to the node as a nodeSelector.

    Custom machine config pools inherit machine configs from the worker pool. Custom pools use any machine config targeted for the worker pool, but add the ability to also deploy changes that are targeted at only the custom pool. Because a custom pool inherits resources from the worker pool, any change to the worker pool also affects the custom pool.

  3. After you have the YAML file, you can create the machine config pool:

    $ oc create -f infra.mcp.yaml

  4. Check the machine configs to ensure that the infrastructure configuration rendered successfully:

    $ oc get machineconfig
    Example output
    NAME                                                        GENERATEDBYCONTROLLER                      IGNITIONVERSION   CREATED
00-master                                                   365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
00-worker                                                   365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
01-master-container-runtime                                 365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
01-master-kubelet                                           365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
01-worker-container-runtime                                 365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
01-worker-kubelet                                           365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
99-master-1ae2a1e0-a115-11e9-8f14-005056899d54-registries   365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
99-master-ssh                                                                                          3.2.0             31d
99-worker-1ae64748-a115-11e9-8f14-005056899d54-registries   365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
99-worker-ssh                                                                                          3.2.0             31d
rendered-infra-4e48906dca84ee702959c71a53ee80e7             365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             23m
rendered-master-072d4b2da7f88162636902b074e9e28e            5b6fb8349a29735e48446d435962dec4547d3090   3.2.0             31d
rendered-master-3e88ec72aed3886dec061df60d16d1af            02c07496ba0417b3e12b78fb32baf6293d314f79   3.2.0             31d
rendered-master-419bee7de96134963a15fdf9dd473b25            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             17d
rendered-master-53f5c91c7661708adce18739cc0f40fb            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             13d
rendered-master-a6a357ec18e5bce7f5ac426fc7c5ffcd            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             7d3h
rendered-master-dc7f874ec77fc4b969674204332da037            5b6fb8349a29735e48446d435962dec4547d3090   3.2.0             31d
rendered-worker-1a75960c52ad18ff5dfa6674eb7e533d            5b6fb8349a29735e48446d435962dec4547d3090   3.2.0             31d
rendered-worker-2640531be11ba43c61d72e82dc634ce6            5b6fb8349a29735e48446d435962dec4547d3090   3.2.0             31d
rendered-worker-4e48906dca84ee702959c71a53ee80e7            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             7d3h
rendered-worker-4f110718fe88e5f349987854a1147755            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             17d
rendered-worker-afc758e194d6188677eb837842d3b379            02c07496ba0417b3e12b78fb32baf6293d314f79   3.2.0             31d
rendered-worker-daa08cc1e8f5fcdeba24de60cd955cc3            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             13d

    You should see a new machine config, with the rendered-infra-* prefix.

  5. Optional: To deploy changes to a custom pool, create a machine config that uses the custom pool name as the label, such as infra. Note that this is not required and only shown for instructional purposes. In this manner, you can apply any custom configurations specific to only your infra nodes.

    After you create the new machine config pool, the MCO generates a new rendered config for that pool, and associated nodes of that pool reboot to apply the new configuration.

    1. Create a machine config:

      $ cat infra.mc.yaml
      Example output
      apiVersion: machineconfiguration.openshift.io/v1
kind: MachineConfig
metadata:
  name: 51-infra
  labels:
    machineconfiguration.openshift.io/role: infra (1)
spec:
  config:
    ignition:
      version: 3.2.0
    storage:
      files:
      - path: /etc/infratest
        mode: 0644
        contents:
          source: data:,infra
      1 Add the label you added to the node as a nodeSelector.

    2. Apply the machine config to the infra-labeled nodes:

      $ oc create -f infra.mc.yaml

  6. Confirm that your new machine config pool is available:

    $ oc get mcp
    Example output
    NAME     CONFIG                                             UPDATED   UPDATING   DEGRADED   MACHINECOUNT   READYMACHINECOUNT   UPDATEDMACHINECOUNT   DEGRADEDMACHINECOUNT   AGE
infra    rendered-infra-60e35c2e99f42d976e084fa94da4d0fc    True      False      False      1              1                   1                     0                      4m20s
master   rendered-master-9360fdb895d4c131c7c4bebbae099c90   True      False      False      3              3                   3                     0                      91m
worker   rendered-worker-60e35c2e99f42d976e084fa94da4d0fc   True      False      False      2              2                   2                     0                      91m

    In this example, a worker node was changed to an infra node.

Additional resources

Assigning machine set resources to infrastructure nodes

After creating an infrastructure machine set, the worker and infra roles are applied to new infra nodes. Nodes with the infra role are not counted toward the total number of subscriptions that are required to run the environment, even when the worker role is also applied.

However, when an infra node is assigned the worker role, there is a chance that user workloads can get assigned inadvertently to the infra node. To avoid this, you can apply a taint to the infra node and tolerations for the pods that you want to control.

Binding infrastructure node workloads using taints and tolerations

If you have an infra node that has the infra and worker roles assigned, you must configure the node so that user workloads are not assigned to it.

It is recommended that you preserve the dual infra,worker label that is created for infra nodes and use taints and tolerations to manage nodes that user workloads are scheduled on. If you remove the worker label from the node, you must create a custom pool to manage it. A node with a label other than master or worker is not recognized by the MCO without a custom pool. Maintaining the worker label allows the node to be managed by the default worker machine config pool, if no custom pools that select the custom label exists. The infra label communicates to the cluster that it does not count toward the total number of subscriptions.
Prerequisites

  • Configure additional MachineSet objects in your OKD cluster.

Procedure

  1. Add a taint to the infra node to prevent scheduling user workloads on it:

    1. Determine if the node has the taint:

      $ oc describe nodes <node_name>
      Sample output
      oc describe node ci-ln-iyhx092-f76d1-nvdfm-worker-b-wln2l
Name:               ci-ln-iyhx092-f76d1-nvdfm-worker-b-wln2l
Roles:              worker
 ...
Taints:             node-role.kubernetes.io/infra:NoSchedule
 ...

      This example shows that the node has a taint. You can proceed with adding a toleration to your pod in the next step.

    2. If you have not configured a taint to prevent scheduling user workloads on it:

      $ oc adm taint nodes <node_name> <key>=<value>:<effect>

      For example:

      $ oc adm taint nodes node1 node-role.kubernetes.io/infra=reserved:NoSchedule

      You can alternatively apply the following YAML to add the taint:

      kind: Node
apiVersion: v1
metadata:
  name: <node_name>
  labels:
    ...
spec:
  taints:
    - key: node-role.kubernetes.io/infra
      effect: NoSchedule
      value: reserved
  ...

      This example places a taint on node1 that has key node-role.kubernetes.io/infra and taint effect NoSchedule. Nodes with the NoSchedule effect schedule only pods that tolerate the taint, but allow existing pods to remain scheduled on the node.

      If a descheduler is used, pods violating node taints could be evicted from the cluster.

    3. Add the taint with NoExecute Effect along with the above taint with NoSchedule Effect:

      $ oc adm taint nodes <node_name> <key>=<value>:<effect>

      For example:

      $ oc adm taint nodes node1 node-role.kubernetes.io/infra=reserved:NoExecute

      You can alternatively apply the following YAML to add the taint:

      kind: Node
apiVersion: v1
metadata:
  name: <node_name>
  labels:
    ...
spec:
  taints:
    - key: node-role.kubernetes.io/infra
      effect: NoExecute
      value: reserved
  ...

      This example places a taint on node1 that has the key node-role.kubernetes.io/infra and taint effect NoExecute. Nodes with the NoExecute effect schedule only pods that tolerate the taint. The effect will remove any existing pods from the node that do not have a matching toleration.

  2. Add tolerations for the pod configurations you want to schedule on the infra node, like router, registry, and monitoring workloads. Add the following code to the Pod object specification:

    tolerations:
  - effect: NoSchedule (1)
    key: node-role.kubernetes.io/infra (2)
    value: reserved (3)
  - effect: NoExecute (4)
    key: node-role.kubernetes.io/infra (5)
    operator: Exists (6)
    value: reserved (7)
    1 Specify the effect that you added to the node.
    2 Specify the key that you added to the node.
    3 Specify the value of the key-value pair taint that you added to the node.
    4 Specify the effect that you added to the node.
    5 Specify the key that you added to the node.
    6 Specify the Exists Operator to require a taint with the key node-role.kubernetes.io/infra to be present on the node.
    7 Specify the value of the key-value pair taint that you added to the node.

    This toleration matches the taint created by the oc adm taint command. A pod with this toleration can be scheduled onto the infra node.

    Moving pods for an Operator installed via OLM to an infra node is not always possible. The capability to move Operator pods depends on the configuration of each Operator.

  3. Schedule the pod to the infra node using a scheduler. See the documentation for Controlling pod placement onto nodes for details.

Additional resources

Moving resources to infrastructure machine sets

Some of the infrastructure resources are deployed in your cluster by default. You can move them to the infrastructure machine sets that you created.

Moving the router

You can deploy the router pod to a different compute machine set. By default, the pod is deployed to a worker node.

Prerequisites

  • Configure additional compute machine sets in your OKD cluster.

Procedure

  1. View the IngressController custom resource for the router Operator:

    $ oc get ingresscontroller default -n openshift-ingress-operator -o yaml

    The command output resembles the following text:

    apiVersion: operator.openshift.io/v1
kind: IngressController
metadata:
  creationTimestamp: 2019-04-18T12:35:39Z
  finalizers:
  - ingresscontroller.operator.openshift.io/finalizer-ingresscontroller
  generation: 1
  name: default
  namespace: openshift-ingress-operator
  resourceVersion: "11341"
  selfLink: /apis/operator.openshift.io/v1/namespaces/openshift-ingress-operator/ingresscontrollers/default
  uid: 79509e05-61d6-11e9-bc55-02ce4781844a
spec: {}
status:
  availableReplicas: 2
  conditions:
  - lastTransitionTime: 2019-04-18T12:36:15Z
    status: "True"
    type: Available
  domain: apps.<cluster>.example.com
  endpointPublishingStrategy:
    type: LoadBalancerService
  selector: ingresscontroller.operator.openshift.io/deployment-ingresscontroller=default

  2. Edit the ingresscontroller resource and change the nodeSelector to use the infra label:

    $ oc edit ingresscontroller default -n openshift-ingress-operator
      spec:
    nodePlacement:
      nodeSelector: (1)
        matchLabels:
          node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
    1 Add a nodeSelector parameter with the appropriate value to the component you want to move. You can use a nodeSelector in the format shown or use <key>: <value> pairs, based on the value specified for the node. If you added a taint to the infrastructure node, also add a matching toleration.

  3. Confirm that the router pod is running on the infra node.

    1. View the list of router pods and note the node name of the running pod:

      $ oc get pod -n openshift-ingress -o wide
      Example output
      NAME                              READY     STATUS        RESTARTS   AGE       IP           NODE                           NOMINATED NODE   READINESS GATES
router-default-86798b4b5d-bdlvd   1/1      Running       0          28s       10.130.2.4   ip-10-0-217-226.ec2.internal   <none>           <none>
router-default-955d875f4-255g8    0/1      Terminating   0          19h       10.129.2.4   ip-10-0-148-172.ec2.internal   <none>           <none>

      In this example, the running pod is on the ip-10-0-217-226.ec2.internal node.

    2. View the node status of the running pod:

      $ oc get node <node_name> (1)
      1 Specify the <node_name> that you obtained from the pod list.
      Example output
      NAME                          STATUS  ROLES         AGE   VERSION
ip-10-0-217-226.ec2.internal  Ready   infra,worker  17h   v1.29.4

      Because the role list includes infra, the pod is running on the correct node.

Moving the default registry

You configure the registry Operator to deploy its pods to different nodes.

Prerequisites

  • Configure additional compute machine sets in your OKD cluster.

Procedure

  1. View the config/instance object:

    $ oc get configs.imageregistry.operator.openshift.io/cluster -o yaml
    Example output
    apiVersion: imageregistry.operator.openshift.io/v1
kind: Config
metadata:
  creationTimestamp: 2019-02-05T13:52:05Z
  finalizers:
  - imageregistry.operator.openshift.io/finalizer
  generation: 1
  name: cluster
  resourceVersion: "56174"
  selfLink: /apis/imageregistry.operator.openshift.io/v1/configs/cluster
  uid: 36fd3724-294d-11e9-a524-12ffeee2931b
spec:
  httpSecret: d9a012ccd117b1e6616ceccb2c3bb66a5fed1b5e481623
  logging: 2
  managementState: Managed
  proxy: {}
  replicas: 1
  requests:
    read: {}
    write: {}
  storage:
    s3:
      bucket: image-registry-us-east-1-c92e88cad85b48ec8b312344dff03c82-392c
      region: us-east-1
status:
...

  2. Edit the config/instance object:

    $ oc edit configs.imageregistry.operator.openshift.io/cluster
    spec:
  affinity:
    podAntiAffinity:
      preferredDuringSchedulingIgnoredDuringExecution:
      - podAffinityTerm:
          namespaces:
          - openshift-image-registry
          topologyKey: kubernetes.io/hostname
        weight: 100
  logLevel: Normal
  managementState: Managed
  nodeSelector: (1)
    node-role.kubernetes.io/infra: ""
  tolerations:
  - effect: NoSchedule
    key: node-role.kubernetes.io/infra
    value: reserved
  - effect: NoExecute
    key: node-role.kubernetes.io/infra
    value: reserved
    1 Add a nodeSelector parameter with the appropriate value to the component you want to move. You can use a nodeSelector in the format shown or use <key>: <value> pairs, based on the value specified for the node. If you added a taint to the infrasructure node, also add a matching toleration.

  3. Verify the registry pod has been moved to the infrastructure node.

    1. Run the following command to identify the node where the registry pod is located:

      $ oc get pods -o wide -n openshift-image-registry

    2. Confirm the node has the label you specified:

      $ oc describe node <node_name>

      Review the command output and confirm that node-role.kubernetes.io/infra is in the LABELS list.

Moving the monitoring solution

The monitoring stack includes multiple components, including Prometheus, Thanos Querier, and Alertmanager. The Cluster Monitoring Operator manages this stack. To redeploy the monitoring stack to infrastructure nodes, you can create and apply a custom config map.

Procedure

  1. Edit the cluster-monitoring-config config map and change the nodeSelector to use the infra label:

    $ oc edit configmap cluster-monitoring-config -n openshift-monitoring
    apiVersion: v1
kind: ConfigMap
metadata:
  name: cluster-monitoring-config
  namespace: openshift-monitoring
data:
  config.yaml: |+
    alertmanagerMain:
      nodeSelector: (1)
        node-role.kubernetes.io/infra: ""
      tolerations:
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoSchedule
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoExecute
    prometheusK8s:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoSchedule
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoExecute
    prometheusOperator:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoSchedule
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoExecute
    metricsServer:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoSchedule
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoExecute
    kubeStateMetrics:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoSchedule
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoExecute
    telemeterClient:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoSchedule
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoExecute
    openshiftStateMetrics:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoSchedule
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoExecute
    thanosQuerier:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoSchedule
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoExecute
    monitoringPlugin:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoSchedule
      - key: node-role.kubernetes.io/infra
        value: reserved
        effect: NoExecute
    1 Add a nodeSelector parameter with the appropriate value to the component you want to move. You can use a nodeSelector in the format shown or use <key>: <value> pairs, based on the value specified for the node. If you added a taint to the infrastructure node, also add a matching toleration.

  2. Watch the monitoring pods move to the new machines:

    $ watch 'oc get pod -n openshift-monitoring -o wide'

  3. If a component has not moved to the infra node, delete the pod with this component:

    $ oc delete pod -n openshift-monitoring <pod>

    The component from the deleted pod is re-created on the infra node.

Moving logging resources

For information about moving logging resources, see:

About the cluster autoscaler

The cluster autoscaler adjusts the size of an OKD cluster to meet its current deployment needs. It uses declarative, Kubernetes-style arguments to provide infrastructure management that does not rely on objects of a specific cloud provider. The cluster autoscaler has a cluster scope, and is not associated with a particular namespace.

The cluster autoscaler increases the size of the cluster when there are pods that fail to schedule on any of the current worker nodes due to insufficient resources or when another node is necessary to meet deployment needs. The cluster autoscaler does not increase the cluster resources beyond the limits that you specify.

The cluster autoscaler computes the total memory, CPU, and GPU on all nodes the cluster, even though it does not manage the control plane nodes. These values are not single-machine oriented. They are an aggregation of all the resources in the entire cluster. For example, if you set the maximum memory resource limit, the cluster autoscaler includes all the nodes in the cluster when calculating the current memory usage. That calculation is then used to determine if the cluster autoscaler has the capacity to add more worker resources.

Ensure that the maxNodesTotal value in the ClusterAutoscaler resource definition that you create is large enough to account for the total possible number of machines in your cluster. This value must encompass the number of control plane machines and the possible number of compute machines that you might scale to.

Every 10 seconds, the cluster autoscaler checks which nodes are unnecessary in the cluster and removes them. The cluster autoscaler considers a node for removal if the following conditions apply:

  • The node utilization is less than the node utilization level threshold for the cluster. The node utilization level is the sum of the requested resources divided by the allocated resources for the node. If you do not specify a value in the ClusterAutoscaler custom resource, the cluster autoscaler uses a default value of 0.5, which corresponds to 50% utilization.

  • The cluster autoscaler can move all pods running on the node to the other nodes. The Kubernetes scheduler is responsible for scheduling pods on the nodes.

  • The cluster autoscaler does not have scale down disabled annotation.

If the following types of pods are present on a node, the cluster autoscaler will not remove the node:

  • Pods with restrictive pod disruption budgets (PDBs).

  • Kube-system pods that do not run on the node by default.

  • Kube-system pods that do not have a PDB or have a PDB that is too restrictive.

  • Pods that are not backed by a controller object such as a deployment, replica set, or stateful set.

  • Pods with local storage.

  • Pods that cannot be moved elsewhere because of a lack of resources, incompatible node selectors or affinity, matching anti-affinity, and so on.

  • Unless they also have a "cluster-autoscaler.kubernetes.io/safe-to-evict": "true" annotation, pods that have a "cluster-autoscaler.kubernetes.io/safe-to-evict": "false" annotation.

For example, you set the maximum CPU limit to 64 cores and configure the cluster autoscaler to only create machines that have 8 cores each. If your cluster starts with 30 cores, the cluster autoscaler can add up to 4 more nodes with 32 cores, for a total of 62.

If you configure the cluster autoscaler, additional usage restrictions apply:

  • Do not modify the nodes that are in autoscaled node groups directly. All nodes within the same node group have the same capacity and labels and run the same system pods.

  • Specify requests for your pods.

  • If you have to prevent pods from being deleted too quickly, configure appropriate PDBs.

  • Confirm that your cloud provider quota is large enough to support the maximum node pools that you configure.

  • Do not run additional node group autoscalers, especially the ones offered by your cloud provider.

The horizontal pod autoscaler (HPA) and the cluster autoscaler modify cluster resources in different ways. The HPA changes the deployment’s or replica set’s number of replicas based on the current CPU load. If the load increases, the HPA creates new replicas, regardless of the amount of resources available to the cluster. If there are not enough resources, the cluster autoscaler adds resources so that the HPA-created pods can run. If the load decreases, the HPA stops some replicas. If this action causes some nodes to be underutilized or completely empty, the cluster autoscaler deletes the unnecessary nodes.

The cluster autoscaler takes pod priorities into account. The Pod Priority and Preemption feature enables scheduling pods based on priorities if the cluster does not have enough resources, but the cluster autoscaler ensures that the cluster has resources to run all pods. To honor the intention of both features, the cluster autoscaler includes a priority cutoff function. You can use this cutoff to schedule "best-effort" pods, which do not cause the cluster autoscaler to increase resources but instead run only when spare resources are available.

Pods with priority lower than the cutoff value do not cause the cluster to scale up or prevent the cluster from scaling down. No new nodes are added to run the pods, and nodes running these pods might be deleted to free resources.

Cluster autoscaling is supported for the platforms that have machine API available on it.

Cluster autoscaler resource definition

This ClusterAutoscaler resource definition shows the parameters and sample values for the cluster autoscaler.

apiVersion: "autoscaling.openshift.io/v1"
kind: "ClusterAutoscaler"
metadata:
  name: "default"
spec:
  podPriorityThreshold: -10 (1)
  resourceLimits:
    maxNodesTotal: 24 (2)
    cores:
      min: 8 (3)
      max: 128 (4)
    memory:
      min: 4 (5)
      max: 256 (6)
    gpus:
      - type: nvidia.com/gpu (7)
        min: 0 (8)
        max: 16 (9)
      - type: amd.com/gpu
        min: 0
        max: 4
  logVerbosity: 4 (10)
  scaleDown: (11)
    enabled: true (12)
    delayAfterAdd: 10m (13)
    delayAfterDelete: 5m (14)
    delayAfterFailure: 30s (15)
    unneededTime: 5m (16)
    utilizationThreshold: "0.4" (17)
  expanders: ["Random"] (18)
1 Specify the priority that a pod must exceed to cause the cluster autoscaler to deploy additional nodes. Enter a 32-bit integer value. The podPriorityThreshold value is compared to the value of the PriorityClass that you assign to each pod.
2 Specify the maximum number of nodes to deploy. This value is the total number of machines that are deployed in your cluster, not just the ones that the autoscaler controls. Ensure that this value is large enough to account for all of your control plane and compute machines and the total number of replicas that you specify in your MachineAutoscaler resources.
3 Specify the minimum number of cores to deploy in the cluster.
4 Specify the maximum number of cores to deploy in the cluster.
5 Specify the minimum amount of memory, in GiB, in the cluster.
6 Specify the maximum amount of memory, in GiB, in the cluster.
7 Optional: Specify the type of GPU node to deploy. Only nvidia.com/gpu and amd.com/gpu are valid types.
8 Specify the minimum number of GPUs to deploy in the cluster.
9 Specify the maximum number of GPUs to deploy in the cluster.
10 Specify the logging verbosity level between 0 and 10. The following log level thresholds are provided for guidance:

  • 1: (Default) Basic information about changes.

  • 4: Debug-level verbosity for troubleshooting typical issues.

  • 9: Extensive, protocol-level debugging information.

If you do not specify a value, the default value of 1 is used.
11 In this section, you can specify the period to wait for each action by using any valid ParseDuration interval, including ns, us, ms, s, m, and h.
12 Specify whether the cluster autoscaler can remove unnecessary nodes.
13 Optional: Specify the period to wait before deleting a node after a node has recently been added. If you do not specify a value, the default value of 10m is used.
14 Optional: Specify the period to wait before deleting a node after a node has recently been deleted. If you do not specify a value, the default value of 0s is used.
15 Optional: Specify the period to wait before deleting a node after a scale down failure occurred. If you do not specify a value, the default value of 3m is used.
16 Optional: Specify a period of time before an unnecessary node is eligible for deletion. If you do not specify a value, the default value of 10m is used.
17 Optional: Specify the node utilization level. Nodes below this utilization level are eligible for deletion.

The node utilization level is the sum of the requested resources divided by the allocated resources for the node, and must be a value greater than "0" but less than "1". If you do not specify a value, the cluster autoscaler uses a default value of "0.5", which corresponds to 50% utilization. You must express this value as a string.
18 Optional: Specify any expanders that you want the cluster autoscaler to use. The following values are valid:

  • LeastWaste: Selects the machine set that minimizes the idle CPU after scaling. If multiple machine sets would yield the same amount of idle CPU, the selection minimizes unused memory.

  • Priority: Selects the machine set with the highest user-assigned priority. To use this expander, you must create a config map that defines the priority of your machine sets. For more information, see "Configuring a priority expander for the cluster autoscaler."

  • Random: (Default) Selects the machine set randomly.

If you do not specify a value, the default value of Random is used.

You can specify multiple expanders by using the [LeastWaste, Priority] format. The cluster autoscaler applies each expander according to the specified order.

In the [LeastWaste, Priority] example, the cluster autoscaler first evaluates according to the LeastWaste criteria. If more than one machine set satisfies the LeastWaste criteria equally well, the cluster autoscaler then evaluates according to the Priority criteria. If more than one machine set satisfies all of the specified expanders equally well, the cluster autoscaler selects one to use at random.

When performing a scaling operation, the cluster autoscaler remains within the ranges set in the ClusterAutoscaler resource definition, such as the minimum and maximum number of cores to deploy or the amount of memory in the cluster. However, the cluster autoscaler does not correct the current values in your cluster to be within those ranges.

The minimum and maximum CPUs, memory, and GPU values are determined by calculating those resources on all nodes in the cluster, even if the cluster autoscaler does not manage the nodes. For example, the control plane nodes are considered in the total memory in the cluster, even though the cluster autoscaler does not manage the control plane nodes.

Deploying a cluster autoscaler

To deploy a cluster autoscaler, you create an instance of the ClusterAutoscaler resource.

Procedure

  1. Create a YAML file for a ClusterAutoscaler resource that contains the custom resource definition.

  2. Create the custom resource in the cluster by running the following command:

    $ oc create -f <filename>.yaml (1)
    1 <filename> is the name of the custom resource file.

About the machine autoscaler

The machine autoscaler adjusts the number of Machines in the compute machine sets that you deploy in an OKD cluster. You can scale both the default worker compute machine set and any other compute machine sets that you create. The machine autoscaler makes more Machines when the cluster runs out of resources to support more deployments. Any changes to the values in MachineAutoscaler resources, such as the minimum or maximum number of instances, are immediately applied to the compute machine set they target.

You must deploy a machine autoscaler for the cluster autoscaler to scale your machines. The cluster autoscaler uses the annotations on compute machine sets that the machine autoscaler sets to determine the resources that it can scale. If you define a cluster autoscaler without also defining machine autoscalers, the cluster autoscaler will never scale your cluster.

Machine autoscaler resource definition

This MachineAutoscaler resource definition shows the parameters and sample values for the machine autoscaler.

apiVersion: "autoscaling.openshift.io/v1beta1"
kind: "MachineAutoscaler"
metadata:
  name: "worker-us-east-1a" (1)
  namespace: "openshift-machine-api"
spec:
  minReplicas: 1 (2)
  maxReplicas: 12 (3)
  scaleTargetRef: (4)
    apiVersion: machine.openshift.io/v1beta1
    kind: MachineSet (5)
    name: worker-us-east-1a (6)
1 Specify the machine autoscaler name. To make it easier to identify which compute machine set this machine autoscaler scales, specify or include the name of the compute machine set to scale. The compute machine set name takes the following form: <clusterid>-<machineset>-<region>.
2 Specify the minimum number machines of the specified type that must remain in the specified zone after the cluster autoscaler initiates cluster scaling. If running in AWS, GCP, Azure, OpenStack, or vSphere, this value can be set to 0. For other providers, do not set this value to 0.

You can save on costs by setting this value to 0 for use cases such as running expensive or limited-usage hardware that is used for specialized workloads, or by scaling a compute machine set with extra large machines. The cluster autoscaler scales the compute machine set down to zero if the machines are not in use.

Do not set the spec.minReplicas value to 0 for the three compute machine sets that are created during the OKD installation process for an installer provisioned infrastructure.
3 Specify the maximum number machines of the specified type that the cluster autoscaler can deploy in the specified zone after it initiates cluster scaling. Ensure that the maxNodesTotal value in the ClusterAutoscaler resource definition is large enough to allow the machine autoscaler to deploy this number of machines.
4 In this section, provide values that describe the existing compute machine set to scale.
5 The kind parameter value is always MachineSet.
6 The name value must match the name of an existing compute machine set, as shown in the metadata.name parameter value.

Deploying a machine autoscaler

To deploy a machine autoscaler, you create an instance of the MachineAutoscaler resource.

Procedure

  1. Create a YAML file for a MachineAutoscaler resource that contains the custom resource definition.

  2. Create the custom resource in the cluster by running the following command:

    $ oc create -f <filename>.yaml (1)
    1 <filename> is the name of the custom resource file.

Configuring Linux cgroup

OKD uses Linux control group version 2 (cgroup v2) in your cluster.

cgroup v2 is the current version of the Linux cgroup API. cgroup v2 offers several improvements over cgroup v1, including a unified hierarchy, safer sub-tree delegation, new features such as Pressure Stall Information, and enhanced resource management and isolation. However, cgroup v2 has different CPU, memory, and I/O management characteristics than cgroup v1. Therefore, some workloads might experience slight differences in memory or CPU usage on clusters that run cgroup v2.

You can change between cgroup v1 and cgroup v2, as needed. Enabling cgroup v1 in OKD disables all cgroup v2 controllers and hierarchies in your cluster.

cgroup v1 is a deprecated feature. Deprecated functionality is still included in OKD and continues to be supported; however, it will be removed in a future release of this product and is not recommended for new deployments.

For the most recent list of major functionality that has been deprecated or removed within OKD, refer to the Deprecated and removed features section of the OKD release notes.
Prerequisites

  • You have a running OKD cluster that uses version 4.12 or later.

  • You are logged in to the cluster as a user with administrative privileges.

Procedure

  1. Enable cgroup v1 on nodes:

    1. Edit the node.config object:

      $ oc edit nodes.config/cluster

    2. Add spec.cgroupMode: "v1":

      Example node.config object
      apiVersion: config.openshift.io/v2
kind: Node
metadata:
  annotations:
    include.release.openshift.io/ibm-cloud-managed: "true"
    include.release.openshift.io/self-managed-high-availability: "true"
    include.release.openshift.io/single-node-developer: "true"
    release.openshift.io/create-only: "true"
  creationTimestamp: "2022-07-08T16:02:51Z"
  generation: 1
  name: cluster
  ownerReferences:
  - apiVersion: config.openshift.io/v2
    kind: ClusterVersion
    name: version
    uid: 36282574-bf9f-409e-a6cd-3032939293eb
  resourceVersion: "1865"
  uid: 0c0f7a4c-4307-4187-b591-6155695ac85b
spec:
  cgroupMode: "v1" (1)
...
      1 Enables cgroup v1.
Verification

  1. Check the machine configs to see that the new machine configs were added:

    $ oc get mc
    Example output
    NAME                                               GENERATEDBYCONTROLLER                      IGNITIONVERSION   AGE
00-master                                          52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
00-worker                                          52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
01-master-container-runtime                        52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
01-master-kubelet                                  52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
01-worker-container-runtime                        52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
01-worker-kubelet                                  52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
97-master-generated-kubelet                        52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
99-worker-generated-kubelet                        52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
99-master-generated-registries                     52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
99-master-ssh                                                                                 3.2.0             40m
99-worker-generated-registries                     52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
99-worker-ssh                                                                                 3.2.0             40m
rendered-master-23d4317815a5f854bd3553d689cfe2e9   52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             10s (1)
rendered-master-23e785de7587df95a4b517e0647e5ab7   52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
rendered-worker-5d596d9293ca3ea80c896a1191735bb1   52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
rendered-worker-dcc7f1b92892d34db74d6832bcc9ccd4   52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             10s
    1 New machine configs are created, as expected.

  2. Check that the new kernelArguments were added to the new machine configs:

    $ oc describe mc <name>
    Example output for cgroup v1
    apiVersion: machineconfiguration.openshift.io/v2
kind: MachineConfig
metadata:
  labels:
    machineconfiguration.openshift.io/role: worker
  name: 05-worker-kernelarg-selinuxpermissive
spec:
  kernelArguments:
    systemd.unified_cgroup_hierarchy=0 (1)
    systemd.legacy_systemd_cgroup_controller=1 (2)
    1 Disables cgroup v2.
    2 Enables cgroup v1 in systemd.

  3. Check the nodes to see that scheduling on the nodes is disabled. This indicates that the change is being applied:

    $ oc get nodes
    Example output
    NAME                                       STATUS                     ROLES    AGE   VERSION
ci-ln-fm1qnwt-72292-99kt6-master-0         Ready,SchedulingDisabled   master   58m   v1.29.4
ci-ln-fm1qnwt-72292-99kt6-master-1         Ready                      master   58m   v1.29.4
ci-ln-fm1qnwt-72292-99kt6-master-2         Ready                      master   58m   v1.29.4
ci-ln-fm1qnwt-72292-99kt6-worker-a-h5gt4   Ready,SchedulingDisabled   worker   48m   v1.29.4
ci-ln-fm1qnwt-72292-99kt6-worker-b-7vtmd   Ready                      worker   48m   v1.29.4
ci-ln-fm1qnwt-72292-99kt6-worker-c-rhzkv   Ready                      worker   48m   v1.29.4

  4. After a node returns to the Ready state, start a debug session for that node:

    $ oc debug node/<node_name>

  5. Set /host as the root directory within the debug shell:

    sh-4.4# chroot /host

  6. Check that the sys/fs/cgroup/cgroup2fs file is present on your nodes. This file is created by cgroup v1:

    $ stat -c %T -f /sys/fs/cgroup
    Example output
    cgroup2fs
Additional resources

Enabling Technology Preview features using FeatureGates

You can turn on a subset of the current Technology Preview features on for all nodes in the cluster by editing the FeatureGate custom resource (CR).

Understanding feature gates

You can use the FeatureGate custom resource (CR) to enable specific feature sets in your cluster. A feature set is a collection of OKD features that are not enabled by default.

You can activate the following feature set by using the FeatureGate CR:

  • TechPreviewNoUpgrade. This feature set is a subset of the current Technology Preview features. This feature set allows you to enable these Technology Preview features on test clusters, where you can fully test them, while leaving the features disabled on production clusters.

    Enabling the TechPreviewNoUpgrade feature set on your cluster cannot be undone and prevents minor version updates. You should not enable this feature set on production clusters.

    The following Technology Preview features are enabled by this feature set:

    • External cloud providers. Enables support for external cloud providers for clusters on vSphere, AWS, Azure, and GCP. Support for OpenStack is GA. This is an internal feature that most users do not need to interact with. (ExternalCloudProvider)

    • Shared Resources CSI Driver in OpenShift Builds. Enables the Container Storage Interface (CSI). (CSIDriverSharedResource)

    • Swap memory on nodes. Enables swap memory use for OKD workloads on a per-node basis. (NodeSwap)

    • OpenStack Machine API Provider. This gate has no effect and is planned to be removed from this feature set in a future release. (MachineAPIProviderOpenStack)

    • Insights Operator. Enables the InsightsDataGather CRD, which allows users to configure some Insights data gathering options. The feature set also enables the DataGather CRD, which allows users to run Insights data gathering on-demand. (InsightsConfigAPI)

    • Retroactive Default Storage Class. Enables OKD to retroactively assign the default storage class to PVCs if there was no default storage class when the PVC was created.(RetroactiveDefaultStorageClass)

    • Dynamic Resource Allocation API. Enables a new API for requesting and sharing resources between pods and containers. This is an internal feature that most users do not need to interact with. (DynamicResourceAllocation)

    • Pod security admission enforcement. Enables the restricted enforcement mode for pod security admission. Instead of only logging a warning, pods are rejected if they violate pod security standards. (OpenShiftPodSecurityAdmission)

    • StatefulSet pod availability upgrading limits. Enables users to define the maximum number of statefulset pods unavailable during updates which reduces application downtime. (MaxUnavailableStatefulSet)

    • MatchConditions is a list of conditions that must be met for a request to be sent to this webhook. Match conditions filter requests that have already been matched by the rules, namespaceSelector, and objectSelector. An empty list of matchConditions matches all requests. (admissionWebhookMatchConditions)

    • gcpLabelsTags

    • vSphereStaticIPs

    • routeExternalCertificate

    • automatedEtcdBackup

    • gcpClusterHostedDNS

    • vSphereControlPlaneMachineset

    • dnsNameResolver

    • machineConfigNodes

    • metricsServer

    • installAlternateInfrastructureAWS

    • sdnLiveMigration

    • mixedCPUsAllocation

    • managedBootImages

    • onClusterBuild

    • signatureStores

    • DisableKubeletCloudCredentialProviders

    • BareMetalLoadBalancer

    • ClusterAPIInstallAWS

    • ClusterAPIInstallNutanix

    • ClusterAPIInstallOpenStack

    • ClusterAPIInstallVSphere

    • HardwareSpeed

    • KMSv1

    • NetworkDiagnosticsConfig

    • VSphereDriverConfiguration

    • ExternalOIDC

    • ChunkSizeMiB

    • ClusterAPIInstallGCP

    • ClusterAPIInstallPowerVS

    • EtcdBackendQuota

    • Example

    • ImagePolicy

    • InsightsConfig

    • InsightsOnDemandDataGather

    • MetricsCollectionProfiles

    • NewOLM

    • NodeDisruptionPolicy

    • PinnedImages

    • PlatformOperators

    • ServiceAccountTokenNodeBinding

    • ServiceAccountTokenNodeBindingValidation

    • ServiceAccountTokenPodNodeInfo

    • TranslateStreamCloseWebsocketRequests

    • UpgradeStatus

    • VSphereMultiVCenters

    • VolumeGroupSnapshot

Enabling feature sets using the web console

You can use the OKD web console to enable feature sets for all of the nodes in a cluster by editing the FeatureGate custom resource (CR).

Procedure

To enable feature sets:

  1. In the OKD web console, switch to the Administration → Custom Resource Definitions page.

  2. On the Custom Resource Definitions page, click FeatureGate.

  3. On the Custom Resource Definition Details page, click the Instances tab.

  4. Click the cluster feature gate, then click the YAML tab.

  5. Edit the cluster instance to add specific feature sets:

    Enabling the TechPreviewNoUpgrade feature set on your cluster cannot be undone and prevents minor version updates. You should not enable this feature set on production clusters.
    Sample Feature Gate custom resource
    apiVersion: config.openshift.io/v1
kind: FeatureGate
metadata:
  name: cluster (1)
# ...
spec:
  featureSet: TechPreviewNoUpgrade (2)
    1 The name of the FeatureGate CR must be cluster.
    2 Add the feature set that you want to enable:

    • TechPreviewNoUpgrade enables specific Technology Preview features.

    After you save the changes, new machine configs are created, the machine config pools are updated, and scheduling on each node is disabled while the change is being applied.

Verification

You can verify that the feature gates are enabled by looking at the kubelet.conf file on a node after the nodes return to the ready state.

  1. From the Administrator perspective in the web console, navigate to Compute → Nodes.

  2. Select a node.

  3. In the Node details page, click Terminal.

  4. In the terminal window, change your root directory to /host:

    sh-4.2# chroot /host

  5. View the kubelet.conf file:

    sh-4.2# cat /etc/kubernetes/kubelet.conf
    Sample output
    # ...
featureGates:
  InsightsOperatorPullingSCA: true,
  LegacyNodeRoleBehavior: false
# ...

    The features that are listed as true are enabled on your cluster.

    The features listed vary depending upon the OKD version.

Enabling feature sets using the CLI

You can use the OpenShift CLI (oc) to enable feature sets for all of the nodes in a cluster by editing the FeatureGate custom resource (CR).

Prerequisites

  • You have installed the OpenShift CLI (oc).

Procedure

To enable feature sets:

  1. Edit the FeatureGate CR named cluster:

    $ oc edit featuregate cluster

    Enabling the TechPreviewNoUpgrade feature set on your cluster cannot be undone and prevents minor version updates. You should not enable this feature set on production clusters.
    Sample FeatureGate custom resource
    apiVersion: config.openshift.io/v1
kind: FeatureGate
metadata:
  name: cluster (1)
# ...
spec:
  featureSet: TechPreviewNoUpgrade (2)
    1 The name of the FeatureGate CR must be cluster.
    2 Add the feature set that you want to enable:

    • TechPreviewNoUpgrade enables specific Technology Preview features.

    After you save the changes, new machine configs are created, the machine config pools are updated, and scheduling on each node is disabled while the change is being applied.

Verification

You can verify that the feature gates are enabled by looking at the kubelet.conf file on a node after the nodes return to the ready state.

  1. From the Administrator perspective in the web console, navigate to Compute → Nodes.

  2. Select a node.

  3. In the Node details page, click Terminal.

  4. In the terminal window, change your root directory to /host:

    sh-4.2# chroot /host

  5. View the kubelet.conf file:

    sh-4.2# cat /etc/kubernetes/kubelet.conf
    Sample output
    # ...
featureGates:
  InsightsOperatorPullingSCA: true,
  LegacyNodeRoleBehavior: false
# ...

    The features that are listed as true are enabled on your cluster.

    The features listed vary depending upon the OKD version.

etcd tasks

Back up etcd, enable or disable etcd encryption, or defragment etcd data.

About etcd encryption

By default, etcd data is not encrypted in OKD. You can enable etcd encryption for your cluster to provide an additional layer of data security. For example, it can help protect the loss of sensitive data if an etcd backup is exposed to the incorrect parties.

When you enable etcd encryption, the following OpenShift API server and Kubernetes API server resources are encrypted:

  • Secrets

  • Config maps

  • Routes

  • OAuth access tokens

  • OAuth authorize tokens

When you enable etcd encryption, encryption keys are created. You must have these keys to restore from an etcd backup.

Etcd encryption only encrypts values, not keys. Resource types, namespaces, and object names are unencrypted.

If etcd encryption is enabled during a backup, the static_kuberesources_<datetimestamp>.tar.gz file contains the encryption keys for the etcd snapshot. For security reasons, store this file separately from the etcd snapshot. However, this file is required to restore a previous state of etcd from the respective etcd snapshot.

Supported encryption types

The following encryption types are supported for encrypting etcd data in OKD:

AES-CBC

Uses AES-CBC with PKCS#7 padding and a 32 byte key to perform the encryption. The encryption keys are rotated weekly.

AES-GCM

Uses AES-GCM with a random nonce and a 32 byte key to perform the encryption. The encryption keys are rotated weekly.

Enabling etcd encryption

You can enable etcd encryption to encrypt sensitive resources in your cluster.

Do not back up etcd resources until the initial encryption process is completed. If the encryption process is not completed, the backup might be only partially encrypted.

After you enable etcd encryption, several changes can occur:

  • The etcd encryption might affect the memory consumption of a few resources.

  • You might notice a transient affect on backup performance because the leader must serve the backup.

  • A disk I/O can affect the node that receives the backup state.

You can encrypt the etcd database in either AES-GCM or AES-CBC encryption.

To migrate your etcd database from one encryption type to the other, you can modify the API server’s spec.encryption.type field. Migration of the etcd data to the new encryption type occurs automatically.
Prerequisites

  • Access to the cluster as a user with the cluster-admin role.

Procedure

  1. Modify the APIServer object:

    $ oc edit apiserver

  2. Set the spec.encryption.type field to aesgcm or aescbc:

    spec:
  encryption:
    type: aesgcm (1)
    1 Set to aesgcm for AES-GCM encryption or aescbc for AES-CBC encryption.

  3. Save the file to apply the changes.

    The encryption process starts. It can take 20 minutes or longer for this process to complete, depending on the size of the etcd database.

  4. Verify that etcd encryption was successful.

    1. Review the Encrypted status condition for the OpenShift API server to verify that its resources were successfully encrypted:

      $ oc get openshiftapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows EncryptionCompleted upon successful encryption:

      EncryptionCompleted
All resources encrypted: routes.route.openshift.io

      If the output shows EncryptionInProgress, encryption is still in progress. Wait a few minutes and try again.

    2. Review the Encrypted status condition for the Kubernetes API server to verify that its resources were successfully encrypted:

      $ oc get kubeapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows EncryptionCompleted upon successful encryption:

      EncryptionCompleted
All resources encrypted: secrets, configmaps

      If the output shows EncryptionInProgress, encryption is still in progress. Wait a few minutes and try again.

    3. Review the Encrypted status condition for the OpenShift OAuth API server to verify that its resources were successfully encrypted:

      $ oc get authentication.operator.openshift.io -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows EncryptionCompleted upon successful encryption:

      EncryptionCompleted
All resources encrypted: oauthaccesstokens.oauth.openshift.io, oauthauthorizetokens.oauth.openshift.io

      If the output shows EncryptionInProgress, encryption is still in progress. Wait a few minutes and try again.

Disabling etcd encryption

You can disable encryption of etcd data in your cluster.

Prerequisites

  • Access to the cluster as a user with the cluster-admin role.

Procedure

  1. Modify the APIServer object:

    $ oc edit apiserver

  2. Set the encryption field type to identity:

    spec:
  encryption:
    type: identity (1)
    1 The identity type is the default value and means that no encryption is performed.

  3. Save the file to apply the changes.

    The decryption process starts. It can take 20 minutes or longer for this process to complete, depending on the size of your cluster.

  4. Verify that etcd decryption was successful.

    1. Review the Encrypted status condition for the OpenShift API server to verify that its resources were successfully decrypted:

      $ oc get openshiftapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows DecryptionCompleted upon successful decryption:

      DecryptionCompleted
Encryption mode set to identity and everything is decrypted

      If the output shows DecryptionInProgress, decryption is still in progress. Wait a few minutes and try again.

    2. Review the Encrypted status condition for the Kubernetes API server to verify that its resources were successfully decrypted:

      $ oc get kubeapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows DecryptionCompleted upon successful decryption:

      DecryptionCompleted
Encryption mode set to identity and everything is decrypted

      If the output shows DecryptionInProgress, decryption is still in progress. Wait a few minutes and try again.

    3. Review the Encrypted status condition for the OpenShift OAuth API server to verify that its resources were successfully decrypted:

      $ oc get authentication.operator.openshift.io -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows DecryptionCompleted upon successful decryption:

      DecryptionCompleted
Encryption mode set to identity and everything is decrypted

      If the output shows DecryptionInProgress, decryption is still in progress. Wait a few minutes and try again.

Backing up etcd data

Follow these steps to back up etcd data by creating an etcd snapshot and backing up the resources for the static pods. This backup can be saved and used at a later time if you need to restore etcd.

Only save a backup from a single control plane host. Do not take a backup from each control plane host in the cluster.
Prerequisites

  • You have access to the cluster as a user with the cluster-admin role.

  • You have checked whether the cluster-wide proxy is enabled.

    You can check whether the proxy is enabled by reviewing the output of oc get proxy cluster -o yaml. The proxy is enabled if the httpProxy, httpsProxy, and noProxy fields have values set.
Procedure

  1. Start a debug session as root for a control plane node:

    $ oc debug --as-root node/<node_name>

  2. Change your root directory to /host in the debug shell:

    sh-4.4# chroot /host

  3. If the cluster-wide proxy is enabled, export the NO_PROXY, HTTP_PROXY, and HTTPS_PROXY environment variables by running the following commands:

    $ export HTTP_PROXY=http://<your_proxy.example.com>:8080
    $ export HTTPS_PROXY=https://<your_proxy.example.com>:8080
    $ export NO_PROXY=<example.com>

  4. Run the cluster-backup.sh script in the debug shell and pass in the location to save the backup to.

    The cluster-backup.sh script is maintained as a component of the etcd Cluster Operator and is a wrapper around the etcdctl snapshot save command.

    		 
    sh-4.4# /usr/local/bin/cluster-backup.sh /home/core/assets/backup
    Example script output
    found latest kube-apiserver: /etc/kubernetes/static-pod-resources/kube-apiserver-pod-6
found latest kube-controller-manager: /etc/kubernetes/static-pod-resources/kube-controller-manager-pod-7
found latest kube-scheduler: /etc/kubernetes/static-pod-resources/kube-scheduler-pod-6
found latest etcd: /etc/kubernetes/static-pod-resources/etcd-pod-3
ede95fe6b88b87ba86a03c15e669fb4aa5bf0991c180d3c6895ce72eaade54a1
etcdctl version: 3.4.14
API version: 3.4
{"level":"info","ts":1624647639.0188997,"caller":"snapshot/v3_snapshot.go:119","msg":"created temporary db file","path":"/home/core/assets/backup/snapshot_2021-06-25_190035.db.part"}
{"level":"info","ts":"2021-06-25T19:00:39.030Z","caller":"clientv3/maintenance.go:200","msg":"opened snapshot stream; downloading"}
{"level":"info","ts":1624647639.0301006,"caller":"snapshot/v3_snapshot.go:127","msg":"fetching snapshot","endpoint":"https://10.0.0.5:2379"}
{"level":"info","ts":"2021-06-25T19:00:40.215Z","caller":"clientv3/maintenance.go:208","msg":"completed snapshot read; closing"}
{"level":"info","ts":1624647640.6032252,"caller":"snapshot/v3_snapshot.go:142","msg":"fetched snapshot","endpoint":"https://10.0.0.5:2379","size":"114 MB","took":1.584090459}
{"level":"info","ts":1624647640.6047094,"caller":"snapshot/v3_snapshot.go:152","msg":"saved","path":"/home/core/assets/backup/snapshot_2021-06-25_190035.db"}
Snapshot saved at /home/core/assets/backup/snapshot_2021-06-25_190035.db
{"hash":3866667823,"revision":31407,"totalKey":12828,"totalSize":114446336}
snapshot db and kube resources are successfully saved to /home/core/assets/backup

    In this example, two files are created in the /home/core/assets/backup/ directory on the control plane host:

    • snapshot_<datetimestamp>.db: This file is the etcd snapshot. The cluster-backup.sh script confirms its validity.

    • static_kuberesources_<datetimestamp>.tar.gz: This file contains the resources for the static pods. If etcd encryption is enabled, it also contains the encryption keys for the etcd snapshot.

      If etcd encryption is enabled, it is recommended to store this second file separately from the etcd snapshot for security reasons. However, this file is required to restore from the etcd snapshot.

      Keep in mind that etcd encryption only encrypts values, not keys. This means that resource types, namespaces, and object names are unencrypted.

Defragmenting etcd data

For large and dense clusters, etcd can suffer from poor performance if the keyspace grows too large and exceeds the space quota. Periodically maintain and defragment etcd to free up space in the data store. Monitor Prometheus for etcd metrics and defragment it when required; otherwise, etcd can raise a cluster-wide alarm that puts the cluster into a maintenance mode that accepts only key reads and deletes.

Monitor these key metrics:

  • etcd_server_quota_backend_bytes, which is the current quota limit

  • etcd_mvcc_db_total_size_in_use_in_bytes, which indicates the actual database usage after a history compaction

  • etcd_mvcc_db_total_size_in_bytes, which shows the database size, including free space waiting for defragmentation

Defragment etcd data to reclaim disk space after events that cause disk fragmentation, such as etcd history compaction.

History compaction is performed automatically every five minutes and leaves gaps in the back-end database. This fragmented space is available for use by etcd, but is not available to the host file system. You must defragment etcd to make this space available to the host file system.

Defragmentation occurs automatically, but you can also trigger it manually.

Automatic defragmentation is good for most cases, because the etcd operator uses cluster information to determine the most efficient operation for the user.

Automatic defragmentation

The etcd Operator automatically defragments disks. No manual intervention is needed.

Verify that the defragmentation process is successful by viewing one of these logs:

  • etcd logs

  • cluster-etcd-operator pod

  • operator status error log

Automatic defragmentation can cause leader election failure in various OpenShift core components, such as the Kubernetes controller manager, which triggers a restart of the failing component. The restart is harmless and either triggers failover to the next running instance or the component resumes work again after the restart.
Example log output for successful defragmentation
etcd member has been defragmented: <member_name>, memberID: <member_id>
Example log output for unsuccessful defragmentation
failed defrag on member: <member_name>, memberID: <member_id>: <error_message>

Manual defragmentation

A Prometheus alert indicates when you need to use manual defragmentation. The alert is displayed in two cases:

  • When etcd uses more than 50% of its available space for more than 10 minutes

  • When etcd is actively using less than 50% of its total database size for more than 10 minutes

You can also determine whether defragmentation is needed by checking the etcd database size in MB that will be freed by defragmentation with the PromQL expression: (etcd_mvcc_db_total_size_in_bytes - etcd_mvcc_db_total_size_in_use_in_bytes)/1024/1024

Defragmenting etcd is a blocking action. The etcd member will not respond until defragmentation is complete. For this reason, wait at least one minute between defragmentation actions on each of the pods to allow the cluster to recover.

Follow this procedure to defragment etcd data on each etcd member.

Prerequisites

  • You have access to the cluster as a user with the cluster-admin role.

Procedure

  1. Determine which etcd member is the leader, because the leader should be defragmented last.

    1. Get the list of etcd pods:

      $ oc -n openshift-etcd get pods -l k8s-app=etcd -o wide
      Example output
      etcd-ip-10-0-159-225.example.redhat.com                3/3     Running     0          175m   10.0.159.225   ip-10-0-159-225.example.redhat.com   <none>           <none>
etcd-ip-10-0-191-37.example.redhat.com                 3/3     Running     0          173m   10.0.191.37    ip-10-0-191-37.example.redhat.com    <none>           <none>
etcd-ip-10-0-199-170.example.redhat.com                3/3     Running     0          176m   10.0.199.170   ip-10-0-199-170.example.redhat.com   <none>           <none>

    2. Choose a pod and run the following command to determine which etcd member is the leader:

      $ oc rsh -n openshift-etcd etcd-ip-10-0-159-225.example.redhat.com etcdctl endpoint status --cluster -w table
      Example output
      Defaulting container name to etcdctl.
Use 'oc describe pod/etcd-ip-10-0-159-225.example.redhat.com -n openshift-etcd' to see all of the containers in this pod.
+---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+
|         ENDPOINT          |        ID        | VERSION | DB SIZE | IS LEADER | IS LEARNER | RAFT TERM | RAFT INDEX | RAFT APPLIED INDEX | ERRORS |
+---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+
|  https://10.0.191.37:2379 | 251cd44483d811c3 |   3.5.9 |  104 MB |     false |      false |         7 |      91624 |              91624 |        |
| https://10.0.159.225:2379 | 264c7c58ecbdabee |   3.5.9 |  104 MB |     false |      false |         7 |      91624 |              91624 |        |
| https://10.0.199.170:2379 | 9ac311f93915cc79 |   3.5.9 |  104 MB |      true |      false |         7 |      91624 |              91624 |        |
+---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+

      Based on the IS LEADER column of this output, the https://10.0.199.170:2379 endpoint is the leader. Matching this endpoint with the output of the previous step, the pod name of the leader is etcd-ip-10-0-199-170.example.redhat.com.

  2. Defragment an etcd member.

    1. Connect to the running etcd container, passing in the name of a pod that is not the leader:

      $ oc rsh -n openshift-etcd etcd-ip-10-0-159-225.example.redhat.com

    2. Unset the ETCDCTL_ENDPOINTS environment variable:

      sh-4.4# unset ETCDCTL_ENDPOINTS

    3. Defragment the etcd member:

      sh-4.4# etcdctl --command-timeout=30s --endpoints=https://localhost:2379 defrag
      Example output
      Finished defragmenting etcd member[https://localhost:2379]

      If a timeout error occurs, increase the value for --command-timeout until the command succeeds.

    4. Verify that the database size was reduced:

      sh-4.4# etcdctl endpoint status -w table --cluster
      Example output
      +---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+
|         ENDPOINT          |        ID        | VERSION | DB SIZE | IS LEADER | IS LEARNER | RAFT TERM | RAFT INDEX | RAFT APPLIED INDEX | ERRORS |
+---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+
|  https://10.0.191.37:2379 | 251cd44483d811c3 |   3.5.9 |  104 MB |     false |      false |         7 |      91624 |              91624 |        |
| https://10.0.159.225:2379 | 264c7c58ecbdabee |   3.5.9 |   41 MB |     false |      false |         7 |      91624 |              91624 |        | (1)
| https://10.0.199.170:2379 | 9ac311f93915cc79 |   3.5.9 |  104 MB |      true |      false |         7 |      91624 |              91624 |        |
+---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+

      This example shows that the database size for this etcd member is now 41 MB as opposed to the starting size of 104 MB.

    5. Repeat these steps to connect to each of the other etcd members and defragment them. Always defragment the leader last.

      Wait at least one minute between defragmentation actions to allow the etcd pod to recover. Until the etcd pod recovers, the etcd member will not respond.

  3. If any NOSPACE alarms were triggered due to the space quota being exceeded, clear them.

    1. Check if there are any NOSPACE alarms:

      sh-4.4# etcdctl alarm list
      Example output
      memberID:12345678912345678912 alarm:NOSPACE

    2. Clear the alarms:

      sh-4.4# etcdctl alarm disarm

Restoring to a previous cluster state

You can use a saved etcd backup to restore a previous cluster state or restore a cluster that has lost the majority of control plane hosts.

If your cluster uses a control plane machine set, see "Troubleshooting the control plane machine set" for a more simple etcd recovery procedure.

When you restore your cluster, you must use an etcd backup that was taken from the same z-stream release. For example, an OKD 4.7.2 cluster must use an etcd backup that was taken from 4.7.2.
Prerequisites

  • Access to the cluster as a user with the cluster-admin role through a certificate-based kubeconfig file, like the one that was used during installation.

  • A healthy control plane host to use as the recovery host.

  • SSH access to control plane hosts.

  • A backup directory containing both the etcd snapshot and the resources for the static pods, which were from the same backup. The file names in the directory must be in the following formats: snapshot_<datetimestamp>.db and static_kuberesources_<datetimestamp>.tar.gz.

For non-recovery control plane nodes, it is not required to establish SSH connectivity or to stop the static pods. You can delete and recreate other non-recovery, control plane machines, one by one.
Procedure

  1. Select a control plane host to use as the recovery host. This is the host that you will run the restore operation on.

  2. Establish SSH connectivity to each of the control plane nodes, including the recovery host.

    kube-apiserver becomes inaccessible after the restore process starts, so you cannot access the control plane nodes. For this reason, it is recommended to establish SSH connectivity to each control plane host in a separate terminal.

    If you do not complete this step, you will not be able to access the control plane hosts to complete the restore procedure, and you will be unable to recover your cluster from this state.

  3. Copy the etcd backup directory to the recovery control plane host.

    This procedure assumes that you copied the backup directory containing the etcd snapshot and the resources for the static pods to the /home/core/ directory of your recovery control plane host.

  4. Stop the static pods on any other control plane nodes.

    You do not need to stop the static pods on the recovery host.

    1. Access a control plane host that is not the recovery host.

    2. Move the existing etcd pod file out of the kubelet manifest directory by running:

      $ sudo mv -v /etc/kubernetes/manifests/etcd-pod.yaml /tmp

    3. Verify that the etcd pods are stopped by using:

      $ sudo crictl ps | grep etcd | egrep -v "operator|etcd-guard"

      If the output of this command is not empty, wait a few minutes and check again.

    4. Move the existing kube-apiserver file out of the kubelet manifest directory by running:

      $ sudo mv -v /etc/kubernetes/manifests/kube-apiserver-pod.yaml /tmp

    5. Verify that the kube-apiserver containers are stopped by running:

      $ sudo crictl ps | grep kube-apiserver | egrep -v "operator|guard"

      If the output of this command is not empty, wait a few minutes and check again.

    6. Move the existing kube-controller-manager file out of the kubelet manifest directory by using:

      $ sudo mv -v /etc/kubernetes/manifests/kube-controller-manager-pod.yaml /tmp

    7. Verify that the kube-controller-manager containers are stopped by running:

      $ sudo crictl ps | grep kube-controller-manager | egrep -v "operator|guard"

      If the output of this command is not empty, wait a few minutes and check again.

    8. Move the existing kube-scheduler file out of the kubelet manifest directory by using:

      $ sudo mv -v /etc/kubernetes/manifests/kube-scheduler-pod.yaml /tmp

    9. Verify that the kube-scheduler containers are stopped by using:

      $ sudo crictl ps | grep kube-scheduler | egrep -v "operator|guard"

      If the output of this command is not empty, wait a few minutes and check again.

    10. Move the etcd data directory to a different location with the following example:

      $ sudo mv -v /var/lib/etcd/ /tmp

    11. If the /etc/kubernetes/manifests/keepalived.yaml file exists and the node is deleted, follow these steps:

      1. Move the /etc/kubernetes/manifests/keepalived.yaml file out of the kubelet manifest directory:

        $ sudo mv -v /etc/kubernetes/manifests/keepalived.yaml /tmp

      2. Verify that any containers managed by the keepalived daemon are stopped:

        $ sudo crictl ps --name keepalived

        The output of this command should be empty. If it is not empty, wait a few minutes and check again.

      3. Check if the control plane has any Virtual IPs (VIPs) assigned to it:

        $ ip -o address | egrep '<api_vip>|<ingress_vip>'

      4. For each reported VIP, run the following command to remove it:

        $ sudo ip address del <reported_vip> dev <reported_vip_device>

    12. Repeat this step on each of the other control plane hosts that is not the recovery host.

  5. Access the recovery control plane host.

  6. If the keepalived daemon is in use, verify that the recovery control plane node owns the VIP:

    $ ip -o address | grep <api_vip>

    The address of the VIP is highlighted in the output if it exists. This command returns an empty string if the VIP is not set or configured incorrectly.

  7. If the cluster-wide proxy is enabled, be sure that you have exported the NO_PROXY, HTTP_PROXY, and HTTPS_PROXY environment variables.

    You can check whether the proxy is enabled by reviewing the output of oc get proxy cluster -o yaml. The proxy is enabled if the httpProxy, httpsProxy, and noProxy fields have values set.

  8. Run the restore script on the recovery control plane host and pass in the path to the etcd backup directory:

    $ sudo -E /usr/local/bin/cluster-restore.sh /home/core/assets/backup
    Example script output
    ...stopping kube-scheduler-pod.yaml
...stopping kube-controller-manager-pod.yaml
...stopping etcd-pod.yaml
...stopping kube-apiserver-pod.yaml
Waiting for container etcd to stop
.complete
Waiting for container etcdctl to stop
.............................complete
Waiting for container etcd-metrics to stop
complete
Waiting for container kube-controller-manager to stop
complete
Waiting for container kube-apiserver to stop
..........................................................................................complete
Waiting for container kube-scheduler to stop
complete
Moving etcd data-dir /var/lib/etcd/member to /var/lib/etcd-backup
starting restore-etcd static pod
starting kube-apiserver-pod.yaml
static-pod-resources/kube-apiserver-pod-7/kube-apiserver-pod.yaml
starting kube-controller-manager-pod.yaml
static-pod-resources/kube-controller-manager-pod-7/kube-controller-manager-pod.yaml
starting kube-scheduler-pod.yaml
static-pod-resources/kube-scheduler-pod-8/kube-scheduler-pod.yaml

    The cluster-restore.sh script must show that etcd, kube-apiserver, kube-controller-manager, and kube-scheduler pods are stopped and then started at the end of the restore process.

    The restore process can cause nodes to enter the NotReady state if the node certificates were updated after the last etcd backup.

  9. Check the nodes to ensure they are in the Ready state.

    1. Run the following command:

      $ oc get nodes -w
      Sample output
      NAME                STATUS  ROLES          AGE     VERSION
host-172-25-75-28   Ready   master         3d20h   v1.29.4
host-172-25-75-38   Ready   infra,worker   3d20h   v1.29.4
host-172-25-75-40   Ready   master         3d20h   v1.29.4
host-172-25-75-65   Ready   master         3d20h   v1.29.4
host-172-25-75-74   Ready   infra,worker   3d20h   v1.29.4
host-172-25-75-79   Ready   worker         3d20h   v1.29.4
host-172-25-75-86   Ready   worker         3d20h   v1.29.4
host-172-25-75-98   Ready   infra,worker   3d20h   v1.29.4

      It can take several minutes for all nodes to report their state.

    2. If any nodes are in the NotReady state, log in to the nodes and remove all of the PEM files from the /var/lib/kubelet/pki directory on each node. You can SSH into the nodes or use the terminal window in the web console.

      $  ssh -i <ssh-key-path> core@<master-hostname>
      Sample pki directory
      sh-4.4# pwd
/var/lib/kubelet/pki
sh-4.4# ls
kubelet-client-2022-04-28-11-24-09.pem  kubelet-server-2022-04-28-11-24-15.pem
kubelet-client-current.pem              kubelet-server-current.pem

  10. Restart the kubelet service on all control plane hosts.

    1. From the recovery host, run:

      $ sudo systemctl restart kubelet.service

    2. Repeat this step on all other control plane hosts.

  11. Approve the pending Certificate Signing Requests (CSRs):

    Clusters with no worker nodes, such as single-node clusters or clusters consisting of three schedulable control plane nodes, will not have any pending CSRs to approve. You can skip all the commands listed in this step.

    1. Get the list of current CSRs by running:

      $ oc get csr
      Example output
      NAME        AGE    SIGNERNAME                                    REQUESTOR                                                                   CONDITION
csr-2s94x   8m3s   kubernetes.io/kubelet-serving                 system:node:<node_name>                                                     Pending (1)
csr-4bd6t   8m3s   kubernetes.io/kubelet-serving                 system:node:<node_name>                                                     Pending (1)
csr-4hl85   13m    kubernetes.io/kube-apiserver-client-kubelet   system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending (2)
csr-zhhhp   3m8s   kubernetes.io/kube-apiserver-client-kubelet   system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending (2)
...
      1 A pending kubelet serving CSR, requested by the node for the kubelet serving endpoint.
      2 A pending kubelet client CSR, requested with the node-bootstrapper node bootstrap credentials.

    2. Review the details of a CSR to verify that it is valid by running:

      $ oc describe csr <csr_name> (1)
      1 <csr_name> is the name of a CSR from the list of current CSRs.

    3. Approve each valid node-bootstrapper CSR by running:

      $ oc adm certificate approve <csr_name>

    4. For user-provisioned installations, approve each valid kubelet service CSR by running:

      $ oc adm certificate approve <csr_name>

  12. Verify that the single member control plane has started successfully.

    1. From the recovery host, verify that the etcd container is running by using:

      $ sudo crictl ps | grep etcd | egrep -v "operator|etcd-guard"
      Example output
      3ad41b7908e32       36f86e2eeaaffe662df0d21041eb22b8198e0e58abeeae8c743c3e6e977e8009                                                         About a minute ago   Running             etcd                                          0                   7c05f8af362f0

    2. From the recovery host, verify that the etcd pod is running by using:

      $ oc -n openshift-etcd get pods -l k8s-app=etcd
      Example output
      NAME                                             READY   STATUS      RESTARTS   AGE
etcd-ip-10-0-143-125.ec2.internal                1/1     Running     1          2m47s

      If the status is Pending, or the output lists more than one running etcd pod, wait a few minutes and check again.

  13. If you are using the OVNKubernetes network plugin, you must restart ovnkube-controlplane pods.

    1. Delete all of the ovnkube-controlplane pods by running:

      $ oc -n openshift-ovn-kubernetes delete pod -l app=ovnkube-control-plane

    2. Verify that all of the ovnkube-controlplane pods were redeployed by using:

      $ oc -n openshift-ovn-kubernetes get pod -l app=ovnkube-control-plane

  14. If you are using the OVN-Kubernetes network plugin, restart the Open Virtual Network (OVN) Kubernetes pods on all the nodes one by one. Use the following steps to restart OVN-Kubernetes pods on each node:

    Restart OVN-Kubernetes pods in the following order

    1. The recovery control plane host

    2. The other control plane hosts (if available)

    3. The other nodes

    Validating and mutating admission webhooks can reject pods. If you add any additional webhooks with the failurePolicy set to Fail, then they can reject pods and the restoration process can fail. You can avoid this by saving and deleting webhooks while restoring the cluster state. After the cluster state is restored successfully, you can enable the webhooks again.

    Alternatively, you can temporarily set the failurePolicy to Ignore while restoring the cluster state. After the cluster state is restored successfully, you can set the failurePolicy to Fail.

    1. Remove the northbound database (nbdb) and southbound database (sbdb). Access the recovery host and the remaining control plane nodes by using Secure Shell (SSH) and run:

      $ sudo rm -f /var/lib/ovn-ic/etc/*.db

    2. Restart the OpenVSwitch services. Access the node by using Secure Shell (SSH) and run the following command:

      $ sudo systemctl restart ovs-vswitchd ovsdb-server

    3. Delete the ovnkube-node pod on the node by running the following command, replacing <node> with the name of the node that you are restarting:

      $ oc -n openshift-ovn-kubernetes delete pod -l app=ovnkube-node --field-selector=spec.nodeName==<node>

    4. Verify that the ovnkube-node pod is running again with:

      $ oc -n openshift-ovn-kubernetes get pod -l app=ovnkube-node --field-selector=spec.nodeName==<node>

      It might take several minutes for the pods to restart.

  15. Delete and re-create other non-recovery, control plane machines, one by one. After the machines are re-created, a new revision is forced and etcd automatically scales up.

    • If you use a user-provisioned bare metal installation, you can re-create a control plane machine by using the same method that you used to originally create it. For more information, see "Installing a user-provisioned cluster on bare metal".

      Do not delete and re-create the machine for the recovery host.

    • If you are running installer-provisioned infrastructure, or you used the Machine API to create your machines, follow these steps:

      Do not delete and re-create the machine for the recovery host.

      For bare metal installations on installer-provisioned infrastructure, control plane machines are not re-created. For more information, see "Replacing a bare-metal control plane node".

      1. Obtain the machine for one of the lost control plane hosts.

        In a terminal that has access to the cluster as a cluster-admin user, run the following command:

        $ oc get machines -n openshift-machine-api -o wide

        Example output:

        NAME                                        PHASE     TYPE        REGION      ZONE         AGE     NODE                           PROVIDERID                              STATE
clustername-8qw5l-master-0                  Running   m4.xlarge   us-east-1   us-east-1a   3h37m   ip-10-0-131-183.ec2.internal   aws:///us-east-1a/i-0ec2782f8287dfb7e   stopped (1)
clustername-8qw5l-master-1                  Running   m4.xlarge   us-east-1   us-east-1b   3h37m   ip-10-0-143-125.ec2.internal   aws:///us-east-1b/i-096c349b700a19631   running
clustername-8qw5l-master-2                  Running   m4.xlarge   us-east-1   us-east-1c   3h37m   ip-10-0-154-194.ec2.internal    aws:///us-east-1c/i-02626f1dba9ed5bba  running
clustername-8qw5l-worker-us-east-1a-wbtgd   Running   m4.large    us-east-1   us-east-1a   3h28m   ip-10-0-129-226.ec2.internal   aws:///us-east-1a/i-010ef6279b4662ced   running
clustername-8qw5l-worker-us-east-1b-lrdxb   Running   m4.large    us-east-1   us-east-1b   3h28m   ip-10-0-144-248.ec2.internal   aws:///us-east-1b/i-0cb45ac45a166173b   running
clustername-8qw5l-worker-us-east-1c-pkg26   Running   m4.large    us-east-1   us-east-1c   3h28m   ip-10-0-170-181.ec2.internal   aws:///us-east-1c/i-06861c00007751b0a   running
        1 This is the control plane machine for the lost control plane host, ip-10-0-131-183.ec2.internal.

      2. Delete the machine of the lost control plane host by running:

        $ oc delete machine -n openshift-machine-api clustername-8qw5l-master-0 (1)
        1 Specify the name of the control plane machine for the lost control plane host.

        A new machine is automatically provisioned after deleting the machine of the lost control plane host.

      3. Verify that a new machine has been created by running:

        $ oc get machines -n openshift-machine-api -o wide

        Example output:

        NAME                                        PHASE          TYPE        REGION      ZONE         AGE     NODE                           PROVIDERID                              STATE
clustername-8qw5l-master-1                  Running        m4.xlarge   us-east-1   us-east-1b   3h37m   ip-10-0-143-125.ec2.internal   aws:///us-east-1b/i-096c349b700a19631   running
clustername-8qw5l-master-2                  Running        m4.xlarge   us-east-1   us-east-1c   3h37m   ip-10-0-154-194.ec2.internal    aws:///us-east-1c/i-02626f1dba9ed5bba  running
clustername-8qw5l-master-3                  Provisioning   m4.xlarge   us-east-1   us-east-1a   85s     ip-10-0-173-171.ec2.internal    aws:///us-east-1a/i-015b0888fe17bc2c8  running (1)
clustername-8qw5l-worker-us-east-1a-wbtgd   Running        m4.large    us-east-1   us-east-1a   3h28m   ip-10-0-129-226.ec2.internal   aws:///us-east-1a/i-010ef6279b4662ced   running
clustername-8qw5l-worker-us-east-1b-lrdxb   Running        m4.large    us-east-1   us-east-1b   3h28m   ip-10-0-144-248.ec2.internal   aws:///us-east-1b/i-0cb45ac45a166173b   running
clustername-8qw5l-worker-us-east-1c-pkg26   Running        m4.large    us-east-1   us-east-1c   3h28m   ip-10-0-170-181.ec2.internal   aws:///us-east-1c/i-06861c00007751b0a   running
        1 The new machine, clustername-8qw5l-master-3 is being created and is ready after the phase changes from Provisioning to Running.

        It might take a few minutes for the new machine to be created. The etcd cluster Operator will automatically sync when the machine or node returns to a healthy state.

      4. Repeat these steps for each lost control plane host that is not the recovery host.

  16. Turn off the quorum guard by entering:

    $ oc patch etcd/cluster --type=merge -p '{"spec": {"unsupportedConfigOverrides": {"useUnsupportedUnsafeNonHANonProductionUnstableEtcd": true}}}'

    This command ensures that you can successfully re-create secrets and roll out the static pods.

  17. In a separate terminal window within the recovery host, export the recovery kubeconfig file by running:

    $ export KUBECONFIG=/etc/kubernetes/static-pod-resources/kube-apiserver-certs/secrets/node-kubeconfigs/localhost-recovery.kubeconfig

  18. Force etcd redeployment.

    In the same terminal window where you exported the recovery kubeconfig file, run:

    $ oc patch etcd cluster -p='{"spec": {"forceRedeploymentReason": "recovery-'"$( date --rfc-3339=ns )"'"}}' --type=merge (1)
    1 The forceRedeploymentReason value must be unique, which is why a timestamp is appended.

    The etcd redeployment starts.

    When the etcd cluster Operator performs a redeployment, the existing nodes are started with new pods similar to the initial bootstrap scale up.

  19. Turn the quorum guard back on by entering:

    $ oc patch etcd/cluster --type=merge -p '{"spec": {"unsupportedConfigOverrides": null}}'

  20. You can verify that the unsupportedConfigOverrides section is removed from the object by running:

    $ oc get etcd/cluster -oyaml

  21. Verify all nodes are updated to the latest revision.

    In a terminal that has access to the cluster as a cluster-admin user, run:

    $ oc get etcd -o=jsonpath='{range .items[0].status.conditions[?(@.type=="NodeInstallerProgressing")]}{.reason}{"\n"}{.message}{"\n"}'

    Review the NodeInstallerProgressing status condition for etcd to verify that all nodes are at the latest revision. The output shows AllNodesAtLatestRevision upon successful update:

    AllNodesAtLatestRevision
3 nodes are at revision 7 (1)
    1 In this example, the latest revision number is 7.

    If the output includes multiple revision numbers, such as 2 nodes are at revision 6; 1 nodes are at revision 7, this means that the update is still in progress. Wait a few minutes and try again.

  22. After etcd is redeployed, force new rollouts for the control plane. kube-apiserver will reinstall itself on the other nodes because the kubelet is connected to API servers using an internal load balancer.

    In a terminal that has access to the cluster as a cluster-admin user, run:

    1. Force a new rollout for kube-apiserver:

      $ oc patch kubeapiserver cluster -p='{"spec": {"forceRedeploymentReason": "recovery-'"$( date --rfc-3339=ns )"'"}}' --type=merge

      Verify all nodes are updated to the latest revision.

      $ oc get kubeapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="NodeInstallerProgressing")]}{.reason}{"\n"}{.message}{"\n"}'

      Review the NodeInstallerProgressing status condition to verify that all nodes are at the latest revision. The output shows AllNodesAtLatestRevision upon successful update:

      AllNodesAtLatestRevision
3 nodes are at revision 7 (1)
      1 In this example, the latest revision number is 7.

      If the output includes multiple revision numbers, such as 2 nodes are at revision 6; 1 nodes are at revision 7, this means that the update is still in progress. Wait a few minutes and try again.

    2. Force a new rollout for the Kubernetes controller manager by running the following command:

      $ oc patch kubecontrollermanager cluster -p='{"spec": {"forceRedeploymentReason": "recovery-'"$( date --rfc-3339=ns )"'"}}' --type=merge

      Verify all nodes are updated to the latest revision by running:

      $ oc get kubecontrollermanager -o=jsonpath='{range .items[0].status.conditions[?(@.type=="NodeInstallerProgressing")]}{.reason}{"\n"}{.message}{"\n"}'

      Review the NodeInstallerProgressing status condition to verify that all nodes are at the latest revision. The output shows AllNodesAtLatestRevision upon successful update:

      AllNodesAtLatestRevision
3 nodes are at revision 7 (1)
      1 In this example, the latest revision number is 7.

      If the output includes multiple revision numbers, such as 2 nodes are at revision 6; 1 nodes are at revision 7, this means that the update is still in progress. Wait a few minutes and try again.

    3. Force a new rollout for the kube-scheduler by running:

      $ oc patch kubescheduler cluster -p='{"spec": {"forceRedeploymentReason": "recovery-'"$( date --rfc-3339=ns )"'"}}' --type=merge

      Verify all nodes are updated to the latest revision by using:

      $ oc get kubescheduler -o=jsonpath='{range .items[0].status.conditions[?(@.type=="NodeInstallerProgressing")]}{.reason}{"\n"}{.message}{"\n"}'

      Review the NodeInstallerProgressing status condition to verify that all nodes are at the latest revision. The output shows AllNodesAtLatestRevision upon successful update:

      AllNodesAtLatestRevision
3 nodes are at revision 7 (1)
      1 In this example, the latest revision number is 7.

      If the output includes multiple revision numbers, such as 2 nodes are at revision 6; 1 nodes are at revision 7, this means that the update is still in progress. Wait a few minutes and try again.

  23. Monitor the platform Operators by running:

    $ oc adm wait-for-stable-cluster

    This process can take up to 15 minutes.

  24. Verify that all control plane hosts have started and joined the cluster.

    In a terminal that has access to the cluster as a cluster-admin user, run the following command:

    $ oc -n openshift-etcd get pods -l k8s-app=etcd
    Example output
    etcd-ip-10-0-143-125.ec2.internal                2/2     Running     0          9h
etcd-ip-10-0-154-194.ec2.internal                2/2     Running     0          9h
etcd-ip-10-0-173-171.ec2.internal                2/2     Running     0          9h

To ensure that all workloads return to normal operation following a recovery procedure, restart all control plane nodes.

On completion of the previous procedural steps, you might need to wait a few minutes for all services to return to their restored state. For example, authentication by using oc login might not immediately work until the OAuth server pods are restarted.

Consider using the system:admin kubeconfig file for immediate authentication. This method basis its authentication on SSL/TLS client certificates as against OAuth tokens. You can authenticate with this file by issuing the following command:

$ export KUBECONFIG=<installation_directory>/auth/kubeconfig

Issue the following command to display your authenticated user name:

$ oc whoami
Additional resources

Issues and workarounds for restoring a persistent storage state

If your OKD cluster uses persistent storage of any form, a state of the cluster is typically stored outside etcd. It might be an Elasticsearch cluster running in a pod or a database running in a StatefulSet object. When you restore from an etcd backup, the status of the workloads in OKD is also restored. However, if the etcd snapshot is old, the status might be invalid or outdated.

The contents of persistent volumes (PVs) are never part of the etcd snapshot. When you restore an OKD cluster from an etcd snapshot, non-critical workloads might gain access to critical data, or vice-versa.

The following are some example scenarios that produce an out-of-date status:

  • MySQL database is running in a pod backed up by a PV object. Restoring OKD from an etcd snapshot does not bring back the volume on the storage provider, and does not produce a running MySQL pod, despite the pod repeatedly attempting to start. You must manually restore this pod by restoring the volume on the storage provider, and then editing the PV to point to the new volume.

  • Pod P1 is using volume A, which is attached to node X. If the etcd snapshot is taken while another pod uses the same volume on node Y, then when the etcd restore is performed, pod P1 might not be able to start correctly due to the volume still being attached to node Y. OKD is not aware of the attachment, and does not automatically detach it. When this occurs, the volume must be manually detached from node Y so that the volume can attach on node X, and then pod P1 can start.

  • Cloud provider or storage provider credentials were updated after the etcd snapshot was taken. This causes any CSI drivers or Operators that depend on the those credentials to not work. You might have to manually update the credentials required by those drivers or Operators.

  • A device is removed or renamed from OKD nodes after the etcd snapshot is taken. The Local Storage Operator creates symlinks for each PV that it manages from /dev/disk/by-id or /dev directories. This situation might cause the local PVs to refer to devices that no longer exist.

    To fix this problem, an administrator must:

    1. Manually remove the PVs with invalid devices.

    2. Remove symlinks from respective nodes.

    3. Delete LocalVolume or LocalVolumeSet objects (see Storage → Configuring persistent storage → Persistent storage using local volumes → Deleting the Local Storage Operator Resources).

Pod disruption budgets

Understand and configure pod disruption budgets.

Understanding how to use pod disruption budgets to specify the number of pods that must be up

A pod disruption budget allows the specification of safety constraints on pods during operations, such as draining a node for maintenance.

PodDisruptionBudget is an API object that specifies the minimum number or percentage of replicas that must be up at a time. Setting these in projects can be helpful during node maintenance (such as scaling a cluster down or a cluster upgrade) and is only honored on voluntary evictions (not on node failures).

A PodDisruptionBudget object’s configuration consists of the following key parts:

  • A label selector, which is a label query over a set of pods.

  • An availability level, which specifies the minimum number of pods that must be available simultaneously, either:

    • minAvailable is the number of pods must always be available, even during a disruption.

    • maxUnavailable is the number of pods can be unavailable during a disruption.

Available refers to the number of pods that has condition Ready=True. Ready=True refers to the pod that is able to serve requests and should be added to the load balancing pools of all matching services.

A maxUnavailable of 0% or 0 or a minAvailable of 100% or equal to the number of replicas is permitted but can block nodes from being drained.

The default setting for maxUnavailable is 1 for all the machine config pools in OKD. It is recommended to not change this value and update one control plane node at a time. Do not change this value to 3 for the control plane pool.

You can check for pod disruption budgets across all projects with the following:

$ oc get poddisruptionbudget --all-namespaces

The following example contains some values that are specific to OKD on AWS.
Example output
NAMESPACE                              NAME                                    MIN AVAILABLE   MAX UNAVAILABLE   ALLOWED DISRUPTIONS   AGE
openshift-apiserver                    openshift-apiserver-pdb                 N/A             1                 1                     121m
openshift-cloud-controller-manager     aws-cloud-controller-manager            1               N/A               1                     125m
openshift-cloud-credential-operator    pod-identity-webhook                    1               N/A               1                     117m
openshift-cluster-csi-drivers          aws-ebs-csi-driver-controller-pdb       N/A             1                 1                     121m
openshift-cluster-storage-operator     csi-snapshot-controller-pdb             N/A             1                 1                     122m
openshift-cluster-storage-operator     csi-snapshot-webhook-pdb                N/A             1                 1                     122m
openshift-console                      console                                 N/A             1                 1                     116m
#...

The PodDisruptionBudget is considered healthy when there are at least minAvailable pods running in the system. Every pod above that limit can be evicted.

Depending on your pod priority and preemption settings, lower-priority pods might be removed despite their pod disruption budget requirements.

Specifying the number of pods that must be up with pod disruption budgets

You can use a PodDisruptionBudget object to specify the minimum number or percentage of replicas that must be up at a time.

Procedure

To configure a pod disruption budget:

  1. Create a YAML file with the an object definition similar to the following:

    apiVersion: policy/v1 (1)
kind: PodDisruptionBudget
metadata:
  name: my-pdb
spec:
  minAvailable: 2  (2)
  selector:  (3)
    matchLabels:
      name: my-pod
    1 PodDisruptionBudget is part of the policy/v1 API group.
    2 The minimum number of pods that must be available simultaneously. This can be either an integer or a string specifying a percentage, for example, 20%.
    3 A label query over a set of resources. The result of matchLabels and matchExpressions are logically conjoined. Leave this parameter blank, for example selector {}, to select all pods in the project.

    Or:

    apiVersion: policy/v1 (1)
kind: PodDisruptionBudget
metadata:
  name: my-pdb
spec:
  maxUnavailable: 25% (2)
  selector: (3)
    matchLabels:
      name: my-pod
    1 PodDisruptionBudget is part of the policy/v1 API group.
    2 The maximum number of pods that can be unavailable simultaneously. This can be either an integer or a string specifying a percentage, for example, 20%.
    3 A label query over a set of resources. The result of matchLabels and matchExpressions are logically conjoined. Leave this parameter blank, for example selector {}, to select all pods in the project.

  2. Run the following command to add the object to project:

    $ oc create -f </path/to/file> -n <project_name>

Specifying the eviction policy for unhealthy pods

When you use pod disruption budgets (PDBs) to specify how many pods must be available simultaneously, you can also define the criteria for how unhealthy pods are considered for eviction.

You can choose one of the following policies:

IfHealthyBudget

Running pods that are not yet healthy can be evicted only if the guarded application is not disrupted.

AlwaysAllow

Running pods that are not yet healthy can be evicted regardless of whether the criteria in the pod disruption budget is met. This policy can help evict malfunctioning applications, such as ones with pods stuck in the CrashLoopBackOff state or failing to report the Ready status.

It is recommended to set the unhealthyPodEvictionPolicy field to AlwaysAllow in the PodDisruptionBudget object to support the eviction of misbehaving applications during a node drain. The default behavior is to wait for the application pods to become healthy before the drain can proceed.
Procedure

  1. Create a YAML file that defines a PodDisruptionBudget object and specify the unhealthy pod eviction policy:

    Example pod-disruption-budget.yaml file
    apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
  name: my-pdb
spec:
  minAvailable: 2
  selector:
    matchLabels:
      name: my-pod
  unhealthyPodEvictionPolicy: AlwaysAllow (1)
    1 Choose either IfHealthyBudget or AlwaysAllow as the unhealthy pod eviction policy. The default is IfHealthyBudget when the unhealthyPodEvictionPolicy field is empty.

  2. Create the PodDisruptionBudget object by running the following command:

    $ oc create -f pod-disruption-budget.yaml

With a PDB that has the AlwaysAllow unhealthy pod eviction policy set, you can now drain nodes and evict the pods for a malfunctioning application guarded by this PDB.

Additional resources