I have an application based on Akka streams. The application takes the input from one Kafka topic, processes it and again sends the processed data to another Kafka topic. Basically, the application takes data from one Kafka topic and pushes the data to other Kafka topic based on some property.
This application is running in Kubernetes cluster and we are using 2 pods as of now. Whenever a load is generated, the CPU utilization for one pod is 70-80% where as for the other pod its 20-30%.
We have used Load Balancer with Round - Robin algorithm.
Can anyone suggest what could be the best approach or how to solve the high CPU utilisation of one POD and low of the other and also state the reason for such behaviour.
Also, we have tried with single POD and autoscale at 60% but still after auto scaling there is more than 30% difference in CPU utilisation across the PODS.