Cluster Proportional Autoscaler

Cluster Proportional Autoscaler (CPA) is a controller that automatically scales a specified deployment based on the number of nodes in the cluster. It is especially useful when a service needs to be available on every node or should scale proportionally to the overall cluster resources.

Unlike traditional autoscalers, CPA does not rely on load metrics. Instead, it uses proportional formulas that are manually defined.

Modes of Operation

CPA supports two modes for calculating the number of replicas:

Linear Mode

In linear mode, the number of replicas is calculated using the following formula:

replicas = max(min, min(max, cores / coresPerReplica, nodes / nodesPerReplica))

You can use both parameters (coresPerReplica and nodesPerReplica) or just one. The min and max values set the lower and upper limits for the number of replicas.

Example configuration:

config:
  linear:
    coresPerReplica: 2
    nodesPerReplica: 1
    min: 2
    max: 20
    preventSinglePointFailure: true
    includeUnschedulableNodes: true

In this example:

• One pod is created per node
• An additional pod is created for every 2 CPU cores
• Always at least 2 pods, maximum 20
• If there's only one node, 2 pods will be created to prevent a single point of failure
• Unschedulable nodes are also taken into account

Ladder Mode

In ladder mode, the number of replicas is explicitly defined using a lookup table. This is useful when you need an exact number of pods for specific cluster sizes.

Example configuration:

config:
  ladder:
    coresToReplicas:
      - [ 1, 1 ]
      - [ 64, 3 ]
      - [ 512, 5 ]
      - [ 1024, 7 ]
      - [ 2048, 10 ]
    nodesToReplicas:
      - [ 1, 1 ]
      - [ 2, 2 ]
      - [ 5, 3 ]

In this example:

• With 1 node → 1 pod
• With 2 nodes → 2 pods
• With 5 or more nodes → 3 pods
• CPU cores are also considered in parallel:
  • 64 cores → 3 pods
  • 2048 cores → 10 pods

Installation via Control Panel

To install Cluster Proportional Autoscaler:

1. Go to the Kubernetes section and click on the cluster.
2. In the Addons tab, click on Cluster Proportional Autoscaler.
3. In the installation wizard, you can adjust the configuration by editing the manifest in the Configuration section.

By default, the autoscaler is configured to scale the metrics-server in the kube-system namespace using linear mode, creating one pod per node:

config:
  linear:
    coresPerReplica: 1
    nodesPerReplica: 1
    min: 1
    max: 100
    preventSinglePointFailure: true
    includeUnschedulableNodes: true

options:
  logToStdErr: true
  logLevel: 7
  namespace: kube-system
  target: deployment/metrics-server

If you want to scale a different service—for example, nginx in the default namespace—change the target and namespace parameters before installing.

To switch scaling modes or parameters, edit the config section. For instance, you can uncomment the ladder parameters and use that mode instead of linear.

When installing via the web UI, only one target resource can be specified using the target parameter.

 

If you want to scale multiple resources—such as both metrics-server and coredns—you need to use manual installation with multiple autoscaler instances.

Manual Installation

If you need more flexibility or want to deploy multiple autoscalers for different services, use Helm for installation.

Step 1: Add the Helm chart repository:

helm repo add cluster-proportional-autoscaler https://kubernetes-sigs.github.io/cluster-proportional-autoscaler

This adds an external source from which the autoscaler can be installed.

Step 2: Update chart list:

helm repo update

Step 3: Create a values.yaml file with the following content:

config:
  linear:
    coresPerReplica: 1
    nodesPerReplica: 1
    min: 1
    max: 100
    preventSinglePointFailure: true
    includeUnschedulableNodes: true

options:
  logToStdErr: true
  logLevel: 7
  namespace: kube-system
  target: deployment/metrics-server

serviceAccount:
  create: true

This configuration:

• Uses linear mode, creating one pod per node (nodesPerReplica: 1)
• Limits replicas between 1 and 100
• Enables preventSinglePointFailure (adds an extra pod if only one node exists)
• Includes unschedulable nodes in calculations
• Specifies the target deployment and namespace
• Automatically creates a service account with the required permissions

Step 4: Install the autoscaler with Helm:

helm upgrade --install metrics-autoscaler cluster-proportional-autoscaler/cluster-proportional-autoscaler --values values.yaml

Step 5: Verify the pod is running:

kubectl get pods -n kube-system

Scaling Multiple Services

With manual installation, you can run multiple independent autoscaler instances for different services.

To do so:

1. Create a separate values-nginx.yaml file
2. Update the target and namespace parameters for the deployment (e.g., nginx in the default namespace)
3. Install using a different release name:

helm upgrade --install nginx-autoscaler cluster-proportional-autoscaler/cluster-proportional-autoscaler --values values-nginx.yaml

This method allows you to scale any number of services with individual settings.