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Comment by bob1029 | Hacker News Reader

I hope figures like this make developers think twice about about throwing yet another layer of abstraction on to the pile.

How many VMs does an average business actually require, assuming the software wasn't written like total ass?

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I feel like not running a datacenter on backup diesel generators is going to have a slightly bigger impact than cutting back a few VMs

How so? Large diesel generators are respectably efficient at perhaps 40%. Not as efficient as a CCGT plant at 60% but also not in a different order of magnitude.

Because a 20% drop in efficiency is substantial, and because the alternative to diesel generators isn’t just CCGT. You could also use solar, wind, nuclear, tidal etc etc

Carbon output of a diesel generator is horrific compared to just about any form of large scale energy production.

To be fair, I've seen devs use 1000s of times, even millions of times the resources required.

It usually all goes wrong the moment someone is granted permission to use a 2nd computer to solve some problem.

If you're allowed to use a second computer, you need at least 4 to match the performance you previously had on the single machine.

http://www.frankmcsherry.org/assets/COST.pdf

It can't happen unless software buyers were ready to pay for more development time. That abstraction layer and total-ass quality is frequently the only way to meet the deadline and budget.

If people were ready to pay some upfront costs, it would be possible to lower long-term costs, but that's CAPEX vs OPEX decision that is not in the hands of the software developers.

If one is aware of the basics of performance optimization, you can often find low hanging fruit even in Python.

Basic profiling can often find bottlenecks that are easy to fix, usually just a result of a simple oversight.

No one is asking for every piece of software to be rewritten in Assembly whilst taking advantage of every possible algorithmic improvement.

> Basic profiling can often find bottlenecks that are easy to fix, usually just a result of a simple oversight.

But it requires already scarce developers to spend even more time on one task. Those same developers which aready have two missed deadlines in their task queue. What should be done is always nice, but typically doesn't match reality.

How much time is spent in milliseconds crunching data aka doing work, vs sitting around waiting to work?

CPUs use much less power while idle - if there are too many idle CPUs, that's either because the datacenter is not efficiently managed (e.g. machines are always on regardless of load), or because the standby capacity is needed at short notice.

Which sounds like something a search engine/big company like Yandex would need, this rendering performance a little less relevant since the CPUs aren't pegged at 100% all the time

No, but you see, we need a distributed Kubernetes cluster because that would totallypad out my resume, uh, I mean, make development easier!

And dynamically typed languages.

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