Backpressure in distributed systems is a mechanism that helps manage the flow of data between components, preventing system overload and ensuring stability. It occurs when a downstream component cannot process incoming data at the rate it is received, prompting upstream components to slow down or halt their data transmission.

In a typical distributed architecture, components like producers and consumers may operate at different processing speeds. When a producer generates data faster than a consumer can handle, it risks overwhelming the consumer, leading to resource exhaustion or failure. Backpressure addresses this issue by signaling upstream components to reduce the data flow until the consumer can catch up.

One common implementation of backpressure involves the use of buffers or queues. When a consumer's processing capacity is reached, it may signal back to the producer to pause sending more data. This can be achieved through various protocols, such as TCP’s congestion control mechanisms, which dynamically adjust the transmission rate based on network feedback. In more application-specific contexts, frameworks like Apache Kafka or reactive programming libraries (e.g., Project Reactor) incorporate backpressure by providing APIs that allow consumers to specify the desired rate of data consumption.

Technical designs for backpressure often include strategies like token bucket algorithms, where an upstream component sends data only if it has a token that represents its ability to process more data. This allows for dynamic control over the flow of data based on real-time consumption metrics.

In summary, backpressure is a critical component of distributed systems that helps maintain performance and reliability by regulating data flow between components, allowing systems to adapt to varying workloads and prevent bottlenecks. For further reading on this topic, you can refer to sources like [Confluent’s guide on backpressure](https://www.confluent.io/blog/what-is-backpressure/) and [the Reactive Streams specification](https://www.reactive-streams.org/).