[ignoramous]

> Asynchronous computing @Facebook: Driving efficiency and developer productivity ... optimization (queuing + time shifting), capacity regulation along with user delay tolerance ...

  We can infer a more detailed priority by understanding how long each of these asynchronous requests can be delayed ... For each job to be executed, we try to execute it as close as possible to its delay tolerance.

  ... we defer jobs with a long delay tolerance so that the workload is spread over a longer time window. Queueing plays an important role in selecting the most urgent job to execute first.

  ...  Time shifting ... optimize capacity in Async:

  1. Predictive compute collects the data people used yesterday. Predicated on which data people may need, it precomputes before peak hours and stores the data in cache ... This moves the computing lift from peak hours to off-peak hours and trades a little cache miss for better efficiency. 

  2. Deferred compute ... schedules a job as part of user request handling but runs at much later time. For instance, the "people you may know" list is processed during off-peak hours, then shown when people are online (generally during peak hours). 

https://engineering.fb.com/2020/08/17/production-engineering... / https://archive.vn/A87hl

[motorest]

> Asynchronous computing @Facebook

I feel tha I'm missing something obvious. Isn't this doc reinventing the wheel in terms of what very basic task queue systems do? It describes task queues and task prioritization, and how it supports tasks that cache user data. What am I missing?

[ignoramous]

Yes, what is described in the blog post is (by now) a fairly established way to deal with task queues at scale (if you're familiar with those kinds of systems, but not everyone is).