Handling Backpressure

Backpressure matters whenever producers can outpace consumers. If you don’t handle it, you end up with unbounded queues, memory blow-ups, and latency spikes that show up as “random” incidents in production.

This section explains the core choices: bounded buffers, dropping/sliding buffers, or pushing back (blocking/parking) so the system naturally slows down under load.

For Java engineers, think of this as the difference between a bounded BlockingQueue that applies pressure versus a runaway unbounded queue that only fails when you hit the wall.

In this section

• Understanding Backpressure in Asynchronous Systems
  Explore the concept of backpressure in asynchronous systems, its importance, and how Clojure handles it effectively.
• Implementing Backpressure with core.async: Managing Flow and Overflow in Clojure
  Learn how to handle backpressure in Clojure using core.async's buffered channels, control flow mechanisms, and advanced techniques like alt! and alt!! for efficient asynchronous programming.
• Flow Control Strategies in Clojure's Asynchronous Programming
  Explore flow control strategies in Clojure's asynchronous programming, including throttling, batching, and prioritization, with practical examples using core.async.