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Pod Autoscaler


  • The experiment aims to check the ability of nodes to accommodate the number of replicas a given application pod.

  • This experiment can be used for other scenarios as well, such as for checking the Node auto-scaling feature. For example, check if the pods are successfully rescheduled within a specified period in cases where the existing nodes are already running at the specified limits.

Scenario: Scale the replicas

Pod Autoscaler


View the uses of the experiment

coming soon


Verify the prerequisites
  • Ensure that Kubernetes Version > 1.16
  • Ensure that the Litmus Chaos Operator is running by executing kubectl get pods in operator namespace (typically, litmus).If not, install from here
  • Ensure that the pod-autoscaler experiment resource is available in the cluster by executing kubectl get chaosexperiments in the desired namespace. If not, install from here

Default Validations

View the default validations

The application pods should be in running state before and after chaos injection.

Minimal RBAC configuration example (optional)


If you are using this experiment as part of a litmus workflow scheduled constructed & executed from chaos-center, then you may be making use of the litmus-admin RBAC, which is pre installed in the cluster as part of the agent setup.

View the Minimal RBAC permissions

apiVersion: v1
kind: ServiceAccount
  name: pod-autoscaler-sa
  namespace: default
    name: pod-autoscaler-sa litmus
kind: ClusterRole
  name: pod-autoscaler-sa
    name: pod-autoscaler-sa litmus
  # Create and monitor the experiment & helper pods
  - apiGroups: [""]
    resources: ["pods"]
    verbs: ["create","delete","get","list","patch","update", "deletecollection"]
  # Performs CRUD operations on the events inside chaosengine and chaosresult
  - apiGroups: [""]
    resources: ["events"]
    verbs: ["create","get","list","patch","update"]
  # Fetch configmaps details and mount it to the experiment pod (if specified)
  - apiGroups: [""]
    resources: ["configmaps"]
    verbs: ["get","list",]
  # Track and get the runner, experiment, and helper pods log 
  - apiGroups: [""]
    resources: ["pods/log"]
    verbs: ["get","list","watch"]  
  # for creating and managing to execute comands inside target container
  - apiGroups: [""]
    resources: ["pods/exec"]
    verbs: ["get","list","create"]
  # performs CRUD operations on the deployments and statefulsets
  - apiGroups: ["apps"]
    resources: ["deployments","statefulsets"]
    verbs: ["list","get","patch","update"]
  # for configuring and monitor the experiment job by the chaos-runner pod
  - apiGroups: ["batch"]
    resources: ["jobs"]
    verbs: ["create","list","get","delete","deletecollection"]
  # for creation, status polling and deletion of litmus chaos resources used within a chaos workflow
  - apiGroups: [""]
    resources: ["chaosengines","chaosexperiments","chaosresults"]
    verbs: ["create","list","get","patch","update","delete"]
kind: ClusterRoleBinding
  name: pod-autoscaler-sa
    name: pod-autoscaler-sa litmus
  kind: ClusterRole
  name: pod-autoscaler-sa
- kind: ServiceAccount
  name: pod-autoscaler-sa
  namespace: default
Use this sample RBAC manifest to create a chaosServiceAccount in the desired (app) namespace. This example consists of the minimum necessary role permissions to execute the experiment.

Experiment tunables

check the experiment tunables

Mandatory Fields

Variables Description Notes
REPLICA_COUNT Number of replicas upto which we want to scale nil

Optional Fields

Variables Description Notes
TOTAL_CHAOS_DURATION The timeout for the chaos experiment (in seconds) Defaults to 60
LIB The chaos lib used to inject the chaos Defaults to litmus
RAMP_TIME Period to wait before and after injection of chaos in sec

Experiment Examples

Common and Pod specific tunables

Refer the common attributes and Pod specific tunable to tune the common tunables for all experiments and pod specific tunables.

Replica counts

It defines the number of replicas, which should be present in the targeted application during the chaos. It can be tuned via REPLICA_COUNT ENV.

Use the following example to tune this:

# provide the number of replicas 
kind: ChaosEngine
  name: engine-nginx
  engineState: "active"
  annotationCheck: "false"
    appns: "default"
    applabel: "app=nginx"
    appkind: "deployment"
  chaosServiceAccount: pod-autoscaler-sa
  - name: pod-autoscaler
        # number of replica, needs to scale
        - name: REPLICA_COUNT
          value: '3'
        - name: TOTAL_CHAOS_DURATION
          value: '60'