cpu and memory autoscaling handled by KubernetesHorizontal Pod Autoscaloing (HPA) governs the spinning and deletion of additional pods when the existing resources (CPU and Memory) of the microservice are exhausted. In Adeptia Connect, Autoscaling is by default disabled. You can enable HPA in Adeptia Connect by setting the required parameters in the global values.yaml file.
Follow the steps given below to configure HPA.
- Set the following parameters shown in the in the global values.yaml file.
Runtime HPA:
no of pf in queued state - shared/Autoscaling
Run time pod (RabbitMQ_Concurrency :10)
For shared queue - runtime
Autoscaliing: Threshold : 5
12 PF : 10 Running , 2 Queue
16PF : 10 running, 6: queue
For dedicated queue, we have option in UI.
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