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Comment by closeparen | Hacker News Reader

I think this is taking an expansive view of labor e.g. writing all datacenter applications as optimal code in low level languages.

The general disinterest in performance/efficiency work even for large scale datacenters is a major theme of Dan Luu’s writing. I’m not sure how that applies to the rest of the industry but I can attest that my company’s performance engineering team has been zeroed in every round of layoffs we’ve ever had.

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> but I can attest that my company’s performance engineering team has been zeroed in every round of layoffs we’ve ever had.

That doesn't necessarily mean management doesn't care about efficiency and performance, it just means they don't value the performance team (right or wrong).

It's certainly possible for an organization to fail to benefit from performance work. They can make all the servers twice as fast but if all that does is lower the utilization from 10% to 5%, that organization saves nothing, and Amazon pockets the difference in energy usage.

The larger your footprint in the cloud is, the larger incentive you have to make it more efficient though. I think it’s a somewhat self-correcting problem.

The biggest players are running highly, highly efficient software.

Dan Luu’s point is the big players are in fact leaving 7+ figure optimizations on the table all the time, and not really caring when they get found. We’re of course free to disbelieve him, but it tracks with my experience.

The larger you get, the better electricity rates you can negotiate, increasing the opportunity cost of focusing on efficiency.

As long as the industry is growing (it is), the opportunity cost will be high. It seems more likely it's the opposite of a self correcting problem. My 2 cents.

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