Greg Low talks about backpressure:
In any real-time data system, there’s a point where the incoming event rate can exceed what the system can process. This condition is known as backpressure.
Backpressure can occur for a few reasons — a sudden spike in data volume, slow or overloaded consumers, or limited throughput in one part of the pipeline. If it’s not handled properly, it can cascade through the system, eventually causing delays or even a complete stall in event processing.
There are several strategies to handle backpressure effectively.
Click through for those mechanisms. The pedant in me who hates how “real-time” has replaced “online” in terms of systems terminology—not Greg’s fault in the least—would point out that if you truly have a real-time system, you can’t afford to have backpressure because any sort of delay would be inimical to it being real-time.