Recommended cluster scaling practices

Recommended practices for scaling the cluster
Modifying a machine set
About machine health checks
- Limitations when deploying machine health checks
Sample MachineHealthCheck resource
- Short-circuiting machine health check remediation
Creating a MachineHealthCheck resource

The guidance in this section is only relevant for installations with cloud provider integration.

These guidelines apply to OKD with software-defined networking (SDN), not Open Virtual Network (OVN).

Apply the following best practices to scale the number of worker machines in your OKD cluster. You scale the worker machines by increasing or decreasing the number of replicas that are defined in the worker machine set.

Recommended practices for scaling the cluster

When scaling up the cluster to higher node counts:

Spread nodes across all of the available zones for higher availability.
Scale up by no more than 25 to 50 machines at once.
Consider creating new machine sets in each available zone with alternative instance types of similar size to help mitigate any periodic provider capacity constraints. For example, on AWS, use m5.large and m5d.large.

Cloud providers might implement a quota for API services. Therefore, gradually scale the cluster.

The controller might not be able to create the machines if the replicas in the machine sets are set to higher numbers all at one time. The number of requests the cloud platform, which OKD is deployed on top of, is able to handle impacts the process. The controller will start to query more while trying to create, check, and update the machines with the status. The cloud platform on which OKD is deployed has API request limits and excessive queries might lead to machine creation failures due to cloud platform limitations.

Enable machine health checks when scaling to large node counts. In case of failures, the health checks monitor the condition and automatically repair unhealthy machines.

When scaling large and dense clusters to lower node counts, it might take large amounts of time as the process involves draining or evicting the objects running on the nodes being terminated in parallel. Also, the client might start to throttle the requests if there are too many objects to evict. The default client QPS and burst rates are currently set to 5 and 10 respectively and they cannot be modified in OKD.

Modifying a machine set

To make changes to a machine set, edit the MachineSet YAML. Then, remove all machines associated with the machine set by deleting each machine or scaling down the machine set to 0 replicas. Then, scale the replicas back to the desired number. Changes you make to a machine set do not affect existing machines.

If you need to scale a machine set without making other changes, you do not need to delete the machines.

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 machine set to 0 unless you first relocate the router pods.

Prerequisites

Install an OKD cluster and the oc command line.
Log in to oc as a user with cluster-admin permission.

Procedure

Edit the machine set:

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

Scale down the machine set to 0:

$ oc scale --replicas=0 machineset <machineset> -n openshift-machine-api

Or:

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

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

apiVersion: machine.openshift.io/v1beta1
kind: MachineSet
metadata:
  name: <machineset>
  namespace: openshift-machine-api
spec:
  replicas: 0

Wait for the machines to be removed.

Scale up the machine set as needed:

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

Or:

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

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

apiVersion: machine.openshift.io/v1beta1
kind: MachineSet
metadata:
  name: <machineset>
  namespace: openshift-machine-api
spec:
  replicas: 2

Wait for the machines to start. The new machines contain changes you made to the machine set.

About machine health checks

Machine health checks automatically repair unhealthy machines in a particular machine pool.

To monitor machine health, create a resource to define the configuration for a controller. Set a condition to check, such as staying in the NotReady status for five minutes or displaying a permanent condition in the node-problem-detector, and a label for the set of machines to monitor.

You cannot apply a machine health check to a machine with the master role.

The controller that observes a MachineHealthCheck resource checks for the defined condition. If a machine fails the health check, the machine is automatically deleted and one is created to take its place. When a machine is deleted, you see a machine deleted event.

To limit disruptive impact of the machine deletion, the controller drains and deletes only one node at a time. If there are more unhealthy machines than the maxUnhealthy threshold allows for in the targeted pool of machines, remediation stops and therefore enables manual intervention.

Consider the timeouts carefully, accounting for workloads and requirements.

Long timeouts can result in long periods of downtime for the workload on the unhealthy machine.
Too short timeouts can result in a remediation loop. For example, the timeout for checking the NotReady status must be long enough to allow the machine to complete the startup process.

To stop the check, remove the resource.

Limitations when deploying machine health checks

There are limitations to consider before deploying a machine health check:

Only machines owned by a machine set are remediated by a machine health check.
Control plane machines are not currently supported and are not remediated if they are unhealthy.
If the node for a machine is removed from the cluster, a machine health check considers the machine to be unhealthy and remediates it immediately.
If the corresponding node for a machine does not join the cluster after the nodeStartupTimeout, the machine is remediated.
A machine is remediated immediately if the Machine resource phase is Failed.

Sample MachineHealthCheck resource

The MachineHealthCheck resource for all cloud-based installation types, and other than bare metal, resembles the following YAML file:

apiVersion: machine.openshift.io/v1beta1
kind: MachineHealthCheck
metadata:
  name: example (1)
  namespace: openshift-machine-api
spec:
  selector:
    matchLabels:
      machine.openshift.io/cluster-api-machine-role: <role> (2)
      machine.openshift.io/cluster-api-machine-type: <role> (2)
      machine.openshift.io/cluster-api-machineset: <cluster_name>-<label>-<zone> (3)
  unhealthyConditions:
  - type:    "Ready"
    timeout: "300s" (4)
    status: "False"
  - type:    "Ready"
    timeout: "300s" (4)
    status: "Unknown"
  maxUnhealthy: "40%" (5)
  nodeStartupTimeout: "10m" (6)

1	Specify the name of the machine health check to deploy.
2	Specify a label for the machine pool that you want to check.
3	Specify the machine set to track in `<cluster_name>-<label>-<zone>` format. For example, `prod-node-us-east-1a`.
4	Specify the timeout duration for a node condition. If a condition is met for the duration of the timeout, the machine will be remediated. Long timeouts can result in long periods of downtime for a workload on an unhealthy machine.
5	Specify the amount of machines allowed to be concurrently remediated in the targeted pool. This can be set as a percentage or an integer. If the number of unhealthy machines exceeds the limit set by `maxUnhealthy`, remediation is not performed.
6	Specify the timeout duration that a machine health check must wait for a node to join the cluster before a machine is determined to be unhealthy.

The matchLabels are examples only; you must map your machine groups based on your specific needs.

Short-circuiting machine health check remediation

Short circuiting ensures that machine health checks remediate machines only when the cluster is healthy. Short-circuiting is configured through the maxUnhealthy field in the MachineHealthCheck resource.

If the user defines a value for the maxUnhealthy field, before remediating any machines, the MachineHealthCheck compares the value of maxUnhealthy with the number of machines within its target pool that it has determined to be unhealthy. Remediation is not performed if the number of unhealthy machines exceeds the maxUnhealthy limit.

If maxUnhealthy is not set, the value defaults to 100% and the machines are remediated regardless of the state of the cluster.

The appropriate maxUnhealthy value depends on the scale of the cluster you deploy and how many machines the MachineHealthCheck covers. For example, you can use the maxUnhealthy value to cover multiple machine sets across multiple availability zones so that if you lose an entire zone, your maxUnhealthy setting prevents further remediation within the cluster.

The maxUnhealthy field can be set as either an integer or percentage. There are different remediation implementations depending on the maxUnhealthy value.

Setting `maxUnhealthy` by using an absolute value

If maxUnhealthy is set to 2:

Remediation will be performed if 2 or fewer nodes are unhealthy
Remediation will not be performed if 3 or more nodes are unhealthy

These values are independent of how many machines are being checked by the machine health check.

Setting `maxUnhealthy` by using percentages

If maxUnhealthy is set to 40% and there are 25 machines being checked:

Remediation will be performed if 10 or fewer nodes are unhealthy
Remediation will not be performed if 11 or more nodes are unhealthy

If maxUnhealthy is set to 40% and there are 6 machines being checked:

Remediation will be performed if 2 or fewer nodes are unhealthy
Remediation will not be performed if 3 or more nodes are unhealthy

The allowed number of machines is rounded down when the percentage of maxUnhealthy machines that are checked is not a whole number.

Creating a MachineHealthCheck resource

You can create a MachineHealthCheck resource for all MachineSets in your cluster. You should not create a MachineHealthCheck resource that targets control plane machines.