Million Dollar Lines of Code: an Engineering Perspective on Cloud Cost Optimization

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Video with transcript included on InfoQ: bit.ly/3QGY6o7
Erik Peterson discusses the right timing and approach for engineering cost optimization and how to use cost efficiency metrics as powerful constraints that drive innovation, and engineer profit.
#CloudComputing #CostOptimization #InfoQ
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[@k_tully]

Excellent work.

[@canismajorisvy]

thanks for this talk!

[@borisjoffe]

dhh said they spent tons of time optimizing cloud costs and it was still overpriced - that's why the switched to their own servers. The fact that it's so easy to make mistakes costing millions is a serious problem with the cloud. If you look at the basic economics, cloud companies have to make a profit, so they're going to charge more for a server. And the layers of virtualization hurt performance compared to a bare server. So for many companies with steady traffic, on-premise is simpler and cheaper. For services with very variable demand, the cloud can be more cost effective

[@FlaviusAspra]

So what's the single character we're talking about at 20:00?

[@piengeng]

typo on the company's url?

[@AntonioDoesMetal]

It was a typo in the url for the word “company” as the other person mentioned. This means that when the function download_update_metadata ran its response code was never 200 because it was a bad URL. So it fell back to doing a full download and file based hash every single time in the wake condition