For reinforcement learning training pipelines where AI-generated code is evaluated in sandboxes across potentially untrusted workers, the threat model is both the code and the worker. You need isolation in both directions, which pushes toward microVMs or gVisor with defense-in-depth layering.
For implementers, backpressure adds complexity without providing guarantees. The machinery to track queue sizes, compute desiredSize, and invoke pull() at the right times must all be implemented correctly. However, since these signals are advisory, all that work doesn't actually prevent the problems backpressure is supposed to solve.
，这一点在谷歌浏览器【最新下载地址】中也有详细论述
self.base_url = "https://example.com"
Greek: mostly fine, with exceptions