Autoscaling DataPower Pods

Horizontal Pod Autoscaling (HPA)

In this method, pods are added or removed based on current resource utilization. For e.g when average memory utilization across existing pods is above certain level say 90%, horizontal scaling will add new pods in order to bring down the average utilization to the target value 90%. Similarly, when resource utilization is lower than the target, pods will be removed in order to bring the utilization back up to target level. For more information on how horizontal pod autoscaling works, please look at Horizontal Pod Autoscaler.

Vertical Pod Autoscaling (VPA)

This method of scaling does not affect the number of pods. Instead, it affects the resources made available to existing pods. For e.g when a pod is consuming all of its current memory limit, vertical scaling will automatically increase the limit. Similarly, if the pod is not using much of its resource limit, it will automatically decrease the limit for the pods and thus freeing up those unused resources. For more information on how vertical pod autoscaling works, please look at Vertical Pod Autoscaler.

HPA example

To enable horizontal scaling of DataPower Pods on both memory and CPU:

apiVersion: datapower.ibm.com/v1beta3
kind: DataPowerService
metadata:
  name: example-dpservice
spec:
  podAutoScaling:
    method: HPA
    hpa:
      targetCPUUtilizationPercentage: 90
      targetMemoryUtilizationPercentage: 80
      maxReplicas: 6
      minReplicas: 2

The above example attempts to maintain CPU usage at 90% and memory usage at 80% with a limit of maximum 6 pods. When CPU utilization goes above 90%, new pods will be created upto a maximum of 6. When CPU utilization falls below 90%, one or more pods will be removed to maintain CPU utilization at 90%. Similar logic is used for maintaining memory utilization. When targetCPUUtilizationPercentage is not specified or set to 0, CPU scaling is disabled. Similarly, when targetMemoryUtilizationPercentage is not specified or set to 0, memory scaling is disabled. Value specified in minReplicas field acts as a floor for replica count in horizontal scaling. This means, at any point in time, total number of DataPower pods will not be lower than the minReplicas.

VPA example

To enable vertical scaling of DataPower Pods on both memory and CPU:

apiVersion: datapower.ibm.com/v1beta3
kind: DataPowerService
metadata:
  name: example-dpservice
spec:
  podAutoScaling:
    method: VPA
    vpa:
      maxAllowedCPU: 8
      maxAllowedMemory: 16Gi

The above example allows a maximum limit of 8 CPU cores and 16GB memory per DataPower pod. When current memory utilization of DataPower container exceeds the resource limit for memory specified in pod.yaml, vertical pod autoscaler will automatically increase the resource limit accordingly and restart the corresponding DataPower Pod. It will not increase the limit beyond maxAllowedMemory. Similar logic is used when increasing CPU limit. Values specified in Resources.Request in DataPowerService custom resource acts as a floor for vertical scaling. In other words, when utilization stays low, vertical pod autoscaling will lower the resource limits up to but not lower than what was specified in Resources.Request.

Note: Prior to enabling VPA, ensure that the installation prerequisites have been met.