How does Scala support adaptive stream processing with dynamic scaling of operators?

Scala stream systems dynamically scale operators based on load, lag, and backpressure signals.

Adaptive stream processing adjusts parallelism at runtime. Frameworks like Flink or Akka Streams monitor metrics such as queue size, processing latency, and consumer lag. Operators are repartitioned dynamically to handle load spikes. This reduces bottlenecks and improves throughput. State is redistributed safely using checkpointing and state snapshots.