Back-pressure
What back-pressure is and how systems use it to stay stable under load: fast producers and slow consumers, unbounded queues and memory exhaustion, bounded buffers, blocking, dropping and sampling, rejecting with 429 and 503, load shedding, back-pressure in TCP, Node.js streams, reactive streams and Kafka, and designing systems that degrade gracefully.
CodexBash, , 6 min read
Whenever one part of a system produces work faster than the next part can consume it, something has to give. Without a plan, work piles up in queues and buffers until memory runs out, latency climbs to minutes and the system collapses, often taking healthy components with it. Back-pressure is the plan: a way for a slow consumer to signal upstream "slow down", so the system stays within its capacity and degrades gracefully instead of falling over. This article explains the problem, the strategies, and how back-pressure appears in networks, languages and messaging systems.
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