Hi Experts, I have my flink application running on Kubernetes, initially with 1 Job Manager, and 2 Task Managers.
Then we have the custom operator that watches for the CRD, when the CRD replicas changed, it will patch the Flink Job Manager deployment parallelism and max parallelism according to the replicas from CRD (parallelism can be configured via env variables for our application). which causes the job manager restart. hence a new Flink job. But the consumer group does not change, so it will continue from the offset where it left. In addition, operator will also update Task Manager's deployment replicas, and will adjust the pod number. In case of scale up, the existing task manager pods do not get killed, but new task manager pods will be created. And we observed a skew in the partition offset consumed. e.g. some partitions have huge lags and other partitions have small lags. (observed from burrow) This is also validated by the metrics from Flink UI, showing the throughput differs for slotss Any clue why this is the case? Thanks a lot! Eleanore
