I like the article, but I am not sure that I agree with the terminology: I would not call "buffering" a form of back pressure. Imho there is really only one type of back pressure: the one the author calls "control". The other 2 are just ways to "release" pressure.
I agree. The author has interpreted “backpressure” to mean pressure from behind, but my understanding of the term is the other direction, like water pooling up at a partially blocked drain. Water is prevented from entering the pipe because the pipe is at capacity.
Backpressure is an implicit signal from consumer to producer that there is not enough capacity. It propagates backwards from flow like water in a network of pipes.
In their example, the conveyor belt keeps adding chocolates because there is no backpressure. The effect is that Lucy engages in load shedding, and the producer of the chocolates has no say or insight into what happens when that load has to be shed. If there was backpressure, the producer gets to choose what happens.
Yup, this is what WHATWG's Streams spec[0] (linked in the article) says. It defines backpressure as a "process of normalizing flow from the original source according to how fast the chain can process chunks" where the reader "propagates a signal backwards through the pipe chain".
Mozilla's documentation[1] similarly defines backpressure as "the process by which a single stream or a pipe chain regulates the speed of reading/writing".
The article confuses backpressure (the signal used for regulation of the flow) with the reason backpressure is needed (producers and consumers working at different speeds). It should be fairly clear from the metaphor, I would have thought: With a pipe of unbounded size there is no pressure. The pressure builds up in a fixed-size pipe when consumer is slower than producer, which in turn slows down the producer. (Or the pipe explodes, or springs a leak and has to drop data on the ground.)
Edit: I think the article also misses one of the most important ways to release pressure. And that is scaling throughput either horizontally (e.g. by adding more servers) or vertically (e.g. by optimization of software)
The first is not always possible (not all systems are elastic or can be, due to money/resources), and the second is not really a way to handle back-pressure. You could have back-pressure in the most optimized system.
Note that I meant "handling (forward) pressure (or preventing back-pressure) can be done by simply having your system be performant enough. Of course this is not a dynamic property you can adjust at runtime, just wanted to add for the sake of completeness, because it should be part of the mindset. Sometimes a database falling over simply needs a few queries optimized.
> You could have back-pressure in the most optimized system.
Most batch processing systems. But you don't want back pressure in interactive or real-time systems, like graphics, gaming, audio, cars, planes, or even just real time collaboration systems (e.g. Figma). In all these cases back pressure is to be avoided.
