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As the EC Deployment uses the metrics that are exposed by the Prometheus Adapter, it is crucial for you to know how to use the adapter to expose the metrics that you want the EC Deployment to use to scale itself. You can refer to Creating Custom Metrics on Prometheus Adapter(4.0) for more information about how to create your own metrics.

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Scaling

This is an example of how you can use your custom metrics in an EC Deployment. The metrics field is the same as for a normal horizontal pod autoscaler. Read more about autoscaling here: https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/ .

Note that a target type of “AverageValue” means the average value of all the running pods. Scale happens when the value is above the target averageValue.

Info

This section of the document is written based on creating ECDs with yaml and not via Desktop. There is no out-of-the-box yaml file to create an ECD, so for this method you should create your very first ECD using Desktop and then extract the yaml and edit it as below. Eventually Desktop might include options to set non-CPU based scaling, although in the first releases of

We don't have a way to export this inline extension.

version 10 only CPU based scaling is supported by Desktop.

Code Block

autoscale: 
  minReplicas: 1 
  maxReplicas: 3 
  metrics: 
  - type: Pods 
    pods: 
      metric: 
        name: com_digitalroute_wf_Workflow_Pico_Heap_Memory_Used_Percentage 
      target: 
        type: AverageValue 
        averageValue: "3" 
  - type: Pods 
    pods: 
      metric: 
        name: workflows_throughput_avg 
      target: 
        type: AverageValue

        averageValue: "50"

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Scaling