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Enabling auto-scaling nodes on GKE

3 minute read

Google Kubernetes Engine supports node auto-scaling by enabling the option in the GKE console.

  1. Go to GKE console

  2. Select your cluster.

  3. Click Edit.

  4. Under Node Pools, set Autoscaling to on.

  5. Adjust autoscaling limits by setting Minimum size and Maximum size.

Auto-scaling considerations for GKE

While scaling up functionality is straightforward, scaling down is potentially more problematic. Scaling down involve moving workload to different nodes if the node to reclaim has still some utilization but is below the reclamation threshold. Moving agent workload would potentially mean build interruption (failed build) and moving operations center/managed controller workload would mean downtime.

Distinct node pools

One way to deal with scaling down is to treat each workload differently by using separate node pools and thus apply different logic to control the scaling down.

Managed controller and operations center workload

By assigning managed controller and operations center workload to a dedicated pool, the scaling down of nodes can be prevented by restricting eviction of managed controller or operations center deployments. Scale up will happen normally when resources need to be increased in order to deploy additional managed controllers, but scale down will only happen when the nodes are free of operations center or managed controller workload. This might be acceptable since controllers are meant to be stable and permanent, meaning that they are not ephemeral but long lived.

This is achieved by adding the following annotation to operations center and managed controllers: "": "false"

For operations center, the annotation is added to the cloudbees-core.yml in the CJOC "StatefulSet" definition under "spec - template - metadata - annotations"

apiVersion: "apps/v1beta1"
kind: "StatefulSet"
  name: cjoc
    com.cloudbees.cje.type: cjoc
    com.cloudbees.cje.tenant: cjoc
  serviceName: cjoc
  replicas: 1
    type: RollingUpdate

For managed controller, the annotation is added in the configuration page under the 'Advanced Configuration - YAML' parameter. The YAML snippet to add would look like:

kind: StatefulSet

Agent workload

By assigning Jenkins agent workload to a dedicated pool, the scaling could be handled by the default logic. Since agents are Pods that are not backed by a Kubernetes controller, they prevent scale down of nodes until no pods are running on a particular node. This prevents nodes to be reclaimed while agents are running and agent to be interrupted even though the autoscaler is below its reclamation threshold.

To create a dedicated pool for agent workload, we need to prevent other types of workload to be deployed on the dedicated pool nodes. This is accomplished by tainting the dedicated pool nodes. Then to allow scheduling of agent workload on the dedicated pool nodes, the agent pod will use a corresponding taint tolerations and a node selector.

When nodes are created dynamically by the Kubernetes autoscaler, they need to be created with the proper taint and label.

In the Google console, the taint and label can be specified when creating the NodePool:

gke nodepool label taint

The first parameter will automatically add the label workload=build to the newly created nodes. This label will then be used as the NodeSelector for the agent. The second parameter will automatically add the nodeType=build:NoSchedule taint to the node.

The agent template will then need to add the corresponding 'toleration' to allow the scheduling of agent workload on those nodes.

agent toleration selector

For Pipelines, 'toleration' can be added to podTemplate using the yaml parameter as follows:

    def label = "mypodtemplate-${UUID.randomUUID().toString()}"
    def nodeSelector = "workload=build"
    podTemplate(label: label, yaml: """
    apiVersion: v1
    kind: Pod
      - key: nodeType
        operator: Equal
        value: build
        effect: NoSchedule
    """, nodeSelector: nodeSelector, containers: [
      containerTemplate(name: 'maven', image: 'maven:3.3.9-jdk-8-alpine', ttyEnabled: true, command: 'cat')
    ]) {
      node(label) {
        stage('Run maven') {
          container('maven') {
            sh 'mvn --version'