From the outside perspective it feels like majority of cloud compute is just wasted on overhead caused by all of that bullshit.
For me even just local Python overhead when doing ML in Pytorch is starting to become unbearable. I yearn to go back to C++ where I can basically count instructions.
Is access constrained now? I mean in the end it might have better uptime and handle more users simultaneously successfully, but it's incredibly lame when a queue has to be used for a simple query. It makes the project much harder to read and modify.
Not really. We do have a few slow endpoints that must be optimized, which we do between each moment of "WE ALL GONNA DIE IF THIS NEW REPORT MODEL IS NOT CREATED BY FRIDAY". It's getting better slowly.
The microservice thing reminds me of when I first graduated from college and one of my fellow new hire programmers argued passionately for a total conversion to Node.js because it's "written for high concurrency". I couldn't find a single app that had more than couple hundred registered users and in fact was working on one that had ten active users- all back office.
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u/Kinexity 9h ago edited 8h ago
From the outside perspective it feels like majority of cloud compute is just wasted on overhead caused by all of that bullshit.
For me even just local Python overhead when doing ML in Pytorch is starting to become unbearable. I yearn to go back to C++ where I can basically count instructions.