Back-Pressure
A flow control mechanism where a system signals upstream components to slow down when it cannot process incoming data fast enough, preventing resource exhaustion and maintaining system stability.
Back-pressure is a system's way of saying "slow down, I can't keep up." When a consumer processes messages slower than the producer generates them, unbounded queues grow until memory is exhausted and the system crashes. Back-pressure prevents this by propagating flow control signals upstream, forcing producers to reduce their rate or buffer more carefully.
Implementation strategies include bounded queues that reject new items when full, pull-based consumption where consumers request work at their own pace, rate-limiting at the source, and load shedding where excess requests are intentionally dropped with appropriate error responses.
For AI inference systems, back-pressure is critical. GPU-based model serving has hard throughput limits, and queuing too many requests leads to memory exhaustion and cascading failures. Effective back-pressure signals clients to retry later (via 429 responses), scales up inference capacity if possible, and sheds low-priority load to protect high-value requests. Without back-pressure, a traffic spike can take down the entire serving infrastructure.
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