[fleitz]

It might be, then again I see a lot of wheel reinvention in tech / NIH syndrome.

I'm the kind of hacker who if a service runs out of memory every 2 hours, writes a crontab to restart it every hour after X random minutes so they don't all restart at the same time. It gets a lot of eye rolls from the other engineers searching for perfection, but it tends to produce services quickly that are highly reliable.

And look now the engineers who like chaos monkey don't even have to set that up. It's built in.

It looks like most of the savings were in switching from pillow to opencv, something that thumbor already does. https://github.com/thumbor/opencv-engine

[brightball]

Part of it is just Discord’s operating scale. They are already leveraging Elixir clustering to an extremely high rate of concurrency and when you start thinking about problems from that standpoint Go becomes a much more natural fit within the stack for low level micro services.

[Karrot_Kream]

I agree that tech in general and Silicon Valley in particular has a lot of NIH, but I also think this isn't really the case here. In particular, we're discussing a Python service that performs slow image resize calls. They would have (probably, speculation on my part/experience) had to do 2 things:

1. Add profiling and telemetry to their Python code. Refactor the codebase based on insights from this.

2. Write a C<->Python interop for their image libraries.

I can't see the cost of #2 being any different than the cost they paid on writing it in Go. As for #1, depending on how the code is structured, a rewrite may have been less time than profiling spaghetti code. At that point, it depends on how much Go experience the team has.