This is based on the assumption that server without those optimizations is not fast enough. That used to be definitely true in the nineties, but hardware is getting faster while human reaction time stays relatively flat. Hardware is also getting cheaper, so throwing a beefier server is a much easier and better solution than investing months of error prone and non-scalable human labor.

Everyone is ditching those beautiful and smart CS principles on FE by switching to hybrid apps, walking entire DOM on every update, etc.

There's no reason same wouldn't happen on backend. In fact it already has - interpreted languages, GC, micro services.

For better or worse progress in software always meant worse efficiency, because hardware was always forgiving that.

It matters a lot!

1. Response time. A dedicated machine that stores state in-memory from request to request can respond orders of magnitude quicker than one that does not.

2. Resource Efficiency. 1-2 machines running optimized code will cost less than the 10-20 machines (or 100-200 machines) the cloud provider will have to allocate behind the scenes to run less efficient code.

>hardware is getting faster

Considering that the end of Moore's Law is more or less here already, as pointed out in many HN articles, that's really no longer something we can take for granted.

Moore law != progress

I only dabble in server stuffs, but I have to ask:

Why is that a problem? You can design a system and implement it with AWS Lambda (or similar) and a few other things like their (or another) database, message queue, and data storage. Then, when you find that you've got processes that are bottlenecked by this, move them into dedicated servers or containers with faster routines. Just like we already do when pairing (possibly) slower but higher-level languages with C libraries.

PaaS vendors will optimize the hell out of their higher-value services, with dedicated and possibly customized hardware and networking.