> This is true in some senses, but also, response latency isn't the only thing a web application does or is evaluated by. Many applications have, for example, background jobs, that do arbitrarily complex processing outside of the request/response cycle.
Yeah, for sure -- I deal with a web app that does complex, time-consuming analytics in data pipelines with Python, and Rust could help a lot with improving some of the complex calculations. But again, that's more using Rust as a C++ replacement rather than looking at replacing, say, the Python-Flask frontend that serves up the results of those analytics.
> Additionally, people who write web services in Rust talk about decreased memory usage, consistent memory usage, and lower CPU usage. In a cloud context, that can translate directly to revenue saved, by spending less. If that tradeoff is right for you depends on a variety of things, of course. "speed" isn't the only relevant metric that you may want to optimize for.
It'd definitely reduce costs, but yeah, be sure to get a full picture here from a business perspective. Engineers love to optimize AWS costs, but it isn't appropriate in a lot of situations. In my case, I'm paying a nontrivial 5-figure monthly AWS bill, but if my company's AWS costs went to $0/month... it wouldn't move our death date, and it wouldn't change our valuation. This is especially true if there were any loss in developer productivity/feature releases. I would gladly double my AWS bill if I could get features out even 20% faster, though that's not how it works, obviously.
Yeah, for sure -- I deal with a web app that does complex, time-consuming analytics in data pipelines with Python, and Rust could help a lot with improving some of the complex calculations. But again, that's more using Rust as a C++ replacement rather than looking at replacing, say, the Python-Flask frontend that serves up the results of those analytics.
> Additionally, people who write web services in Rust talk about decreased memory usage, consistent memory usage, and lower CPU usage. In a cloud context, that can translate directly to revenue saved, by spending less. If that tradeoff is right for you depends on a variety of things, of course. "speed" isn't the only relevant metric that you may want to optimize for.
It'd definitely reduce costs, but yeah, be sure to get a full picture here from a business perspective. Engineers love to optimize AWS costs, but it isn't appropriate in a lot of situations. In my case, I'm paying a nontrivial 5-figure monthly AWS bill, but if my company's AWS costs went to $0/month... it wouldn't move our death date, and it wouldn't change our valuation. This is especially true if there were any loss in developer productivity/feature releases. I would gladly double my AWS bill if I could get features out even 20% faster, though that's not how it works, obviously.