Tune Flink job operator chaining and slot sharing groups to control physical task layout and resource isolation on a cluster

Steps

1. By default Flink chains adjacent operators into tasks sharing a slot; disable chaining globally with StreamExecutionEnvironment.disableOperatorChaining() or per-operator with operator.disableChaining() to isolate CPU-heavy operators
2. Assign operators to named slot sharing groups using operator.slotSharingGroup(groupName); operators in the same group co-locate in one slot, while operators in different groups require separate slots
3. Set the parallelism of a source operator independently from downstream operators using source.setParallelism(N) to match the Kafka partition count without over-parallelizing CPU-bound transformations
4. Use operator.startNewChain() to break an operator chain at a specific point and start a new chain from that operator onward without disabling chaining globally
5. Monitor task slot utilization in the Flink Web UI under the job graph view to verify that operators in different slot sharing groups are allocated to separate task slots