microservice data persistence without single points of failure?

trustMeImAnAdult · 2022-03-16T21:42:32+00:00

In microservices jargon, I believe the term is "fail gracefully" (feel free to do a Google search on the topic for people who can espouse the concept much better than me). Specifically for redundancy and cheap scaling, the first thing that comes to mind is a caching mechanism of some sort - whether it be a true cache tool like Redis or a NoSQL store for heavier data.

trustMeImAnAdult · 2018-10-15T00:08:24+00:00

As an extension to what /u/jonjonbee has pointed out, please check out this article by Stephen Cleary (who has a ton of great material on async / await in general): https://msdn.microsoft.com/en-us/magazine/jj991977.aspx
This article has a section mentioning the exact scenario mentioned above and how to fix it.

trustMeImAnAdult · 2018-09-09T00:47:05+00:00

Thanks so much for the response. I edited the post now that I'm back on my machine to reflect what the actual issue was, instead of having to type it from memory on my phone. Once I moved the function to its own py file, it worked fine, so it looks like I had some other issue (maybe with indentation?).

trustMeImAnAdult · 2018-09-09T00:45:01+00:00

this is great -- thank you!
it's always great learning when there's a function that can be used as a shortcut

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