Automation setup instruction

Set up PerfectScale Automation in minutes and start seeing instant optimization results with just a few simple steps

Automation is currently available for workloads with type Deployment, DaemonSet, StatefulSet, CronJob and Job.

PerfectScale does not support automating workloads that use the OnDelete update strategy. The OnDelete strategy requires manual intervention to update pods, which falls outside the scope of PerfectScale's automated optimization capabilities.

Step 1: Install PerfectScale Automation Agent

Deploy the PerfectScale automation agent. In order to install the PerfectScale automation agent, run the following commands:

helm repo add perfectscale https://perfectscale-io.github.io --force-update

and

helm upgrade --install -n perfectscale psc-autoscaler \
      --set secret.create=false \
      --set settings.psUrl=<https://api-{your-web-ui-url}> \
      --set settings.telemetryUrl=<https://api-{{your-web-ui-url}}/psc-telemetry> \
      perfectscale/psc-autoscaler

If taints and tolerations are defined in the node pool, you must include them in the command too, so it will appear like this:

helm upgrade --install -n perfectscale psc-autoscaler \
      --set tolerations[0].key=node_pool \
      --set tolerations[0].operator=Equal \
      --set tolerations[0].value=tooling \
      --set secret.create=false \
      perfectscale/psc-autoscaler

If you utilize CI/CD tools with auto-sync, ensure to review the additional configuration steps. Automation with GitOps

Follow the troubleshooting instructions provided, or contact support if you encounter any issues.

Step 2: Create Custom Resource (CR)

After the installation of the automation agent, it is important to create a cluster automation configuration, as this step is mandatory:

apiVersion: perfectscale.io/v1
kind: ClusterAutomationConfig
metadata:
  name: cluster-automation-config
spec:
  automation:
    operational:
      stopAllAutomation: false # Global kill switch for automation (default: false)

Automation is only enabled in configurations where automationMode for the workload type is set to "Enabled". This can be configured in the ClusterAutomationConfig, NamespaceAutomationConfig, or WorkloadAutomationConfig.

Example:

apiVersion: perfectscale.io/v1
kind: ClusterAutomationConfig
metadata:
  name: cluster-automation-config
spec:
  automation:
    operational:
      stopAllAutomation: false # Global kill switch for automation (default: false)  
    workloadTypes:
      Deployment:
        operational:
          automationMode: "Enabled" # Enables automation for the workloads with a specific type in the cluster/namespace

This configuration enables automation for all workloads in a cluster with type: Deployment. Learn more about enabling automation for particular workload types in a cluster, specific namespace, or specific workloads.

Only one cluster-level automation configuration can be applied per cluster. To prevent errors, PerfectScale recommends using consistent naming for cluster-level configurations within the same cluster. This ensures that a new configuration will override the previous one without causing any conflicts.

To help you quickly start using PerfectScale Automation and streamline the optimization process, we provide pre-built Custom Resources (CRs) focused on desired optimization goals. You can easily implement the following CRs and customize them if needed.

PerfectScale recommends you start with the cluster cost-saving automation configuration.

👉 Explore more configuration examples at our GitHub.

⚡ Recommended adoption path

To minimize waste and achieve optimal savings, we recommend starting with a simple, cluster-level automation focused on cost reduction.

Create a YAML file with the recommended cluster-level automation configuration using the following template:

apiVersion: perfectscale.io/v1
kind: ClusterAutomationConfig
metadata:
  name: cluster-automation-config
spec:
  automation:
    operational:
      stopAllAutomation: false # Global kill switch for automation (default: false)  
    workloadTypes:
      Deployment:
        operational:
          automationMode: "Enabled" # Enables automation for the workloads with a specific type in the cluster/namespace
          restrictions:
      DaemonSet:
        operational:
          automationMode: "Enabled" # Enables automation for the workloads with a specific type in the cluster/namespace
          restrictions:

Apply the created configuration by running the following command (where cluster-automation-config.yaml - the name of your file created in the previous step):

kubectl apply -f cluster-automation-config.yaml

Combining cost-savings and performance improvement configuration

The following example of a Cluster-level automation configuration allows you to automate the optimization of the entire cluster, enhancing its performance while maintaining optimal costs.

Create a YAML file with the cluster-level automation configuration using the following template:

apiVersion: perfectscale.io/v1
kind: ClusterAutomationConfig
metadata:
  name: cluster-automation-config
spec:
  automation:
    operational:
      stopAllAutomation: false # Global kill switch for automation (default: false)  
    workloadTypes:
      Deployment:
        operational:
          automationMode: "Enabled" # Enables automation for the workloads with a specific type in the cluster/namespace
          restrictions:
            workloadMinWasteUSDPerMonth: 5 # Activates automation only if monthly waste exceeds a set threshold (for example, $5)
            cpuManagement:
              request:
                increaseEnabled: true # Allows PerfectScale Automation to increase CPU requests if the performance risks are observed
                decreaseEnabled: true # Allows PerfectScale Automation to decrease CPU requests to minimize waste
              limit:
                keepLimit: true # Automation will maintain a non-zero CPU limit and will not set the value to zero
            memoryManagement:
              request:
                increaseEnabled: true # Allows PerfectScale Automation to increase Memory requests if the performance risks are observed
                decreaseEnabled: true # Allows PerfectScale Automation to decrease Memory requests to minimize waste
              limit:
                increaseEnabled: true # Allows PerfectScale Automation to increase Memory limit if the performance risks are observed
                decreaseEnabled: true # Allows PerfectScale Automation to decrease Memory limit
      DaemonSet:
        operational:
          automationMode: "Enabled" # Enables automation for the workloads with a specific type in the cluster/namespace
          restrictions:
            workloadMinWasteUSDPerMonth: 5 # Activates automation only if monthly waste exceeds a set threshold (for example, $5)
            cpuManagement:
              request:
                increaseEnabled: true # Allows PerfectScale Automation to increase CPU requests if the performance risks are observed
                decreaseEnabled: true # Allows PerfectScale Automation to decrease CPU requests to minimize waste
              limit:
                keepLimit: true # Automation will maintain a non-zero CPU limit and will not set the value to zero
            memoryManagement:
              request:
                increaseEnabled: true # Allows PerfectScale Automation to increase Memory requests if the performance risks are observed
                decreaseEnabled: true # Allows PerfectScale Automation to decrease Memory requests to minimize waste
              limit:
                increaseEnabled: true # Allows PerfectScale Automation to increase Memory limit if the performance risks are observed
                decreaseEnabled: true # Allows PerfectScale Automation to decrease Memory limit

Apply the created configuration by running the following command (where cluster-automation-config.yaml - the name of your file created in the previous step):

kubectl apply -f cluster-automation-config.yaml

Let's explore additional examples of automation configurations that offer more granular and flexible control over Automation:

• How to include a cluster, namespace, or workload in the Automation configuration

• How to exclude a namespace or workload from the Automation configuration

Automation configuration defaults

Some automation configuration settings have predefined defaults. If you don’t specify a value, PerfectScale will automatically apply the default for that field. Below is the list of configurations and their default values.

stopAllAutomation	false
cleanupAllAutomation	false
automationMode	Enabled
workloadLabelSelectors	nil
wasteMaxAutomationFrequency	Deployment: 30m Rollout: 30m CronJob: 30m Job: 30m DaemonSet: 4h StatefulSet: 24h
fixResiliencyMaxAutomationFrequency	30m
maintenanceWindowIgnoredForResiliency	false
maintenanceWindowIgnoredMinResiliencyLevel	""
maintenanceWindow	monday: - "00:00-23:59" tuesday: - "00:00-23:59" wednesday: - "00:00-23:59" thursday: - "00:00-23:59" friday: - "00:00-23:59" saturday: - "00:00-23:59" sunday: - "00:00-23:59"
workloadMinWasteUSDPerMonth	5
cpuManagement	request: IncreaseEnabled: false DecreaseEnabled: true MinimumCores: -1 // no limit MaximumCores: -1 // no limit limit: KeepLimit: true
memoryManagement	request: IncreaseEnabled: false DecreaseEnabled: true MinimumGiB: -1 // no limit MaximumGib: -1 // no limit limit: IncreaseEnabled: false DecreaseEnabled: false MinimumGiB: -1 // no limit MaximumGib: -1 // no limit maxMemoryIncreaseIterations: Daily: 3 Weekly: 6