CRAC (air circulation). That means for every watt of power used in the server, we pay for another 1-2 watts of support power.
And to actually get all this power, we have to pay for the infrastructure required to get the power into and throughout the datacenter. Hennessy & Patterson estimate that of the $90M cost of an example datacenter (just the facilities -- not the servers), 82% is associated with power and cooling1. The servers in the datacenter are estimated to only cost $70M. It's not fair to compare those numbers directly since servers need to get replaced more often than datacenters; once you take into account the cost over the entire lifetime of the datacenter, the amortized cost of power and cooling comes out to be 33% of the total cost, when servers have a 3 year lifetime and infrastructure has a 10-15 year lifetime.
If we look at all the costs, the breakdown is:
category | % |
---|---|
server machines | 53 |
power & cooling infra | 20 |
power use | 13 |
networking | 8 |
other infra | 4 |
humans | 2 |
Power use and people are the cost of operating the datacenter (OPEX), whereas server machines, networking, power & cooling infra, and other infra are capital expenditures that are amortized across the lifetime of the datacenter (CAPEX).
Computation uses a lot of power. We used to build steel mills near cheap sources of power, but now that's where we build datacenters. As companies start considering the full cost of applications, we're seeing a lot more power optimized solutions2. Unfortunately, this is really hard. On the software side, with the exceptions of toy microbenchmark examples, best practices for writing power efficient code still aren't well understood. On the hardware side, Intel recently released a new generation of chips with significantly improved performance per watt that doesn't have much better absolute performance than the previous generation. On the hardware accelerator front, some large companies are building dedicated power-efficient hardware for specific computations. But with existing tools, hardware accelerators are costly enough that dedicated hardware only makes sense for the largest companies. There isn't an easy answer to this problem.
If you liked this post, you'd probably like chapter 6 of Hennessy & Patterson, which walks through not only the cost of power, but a number of related back of the envelope calculations relating to datacenter performance and cost.
Apologies for the quickly scribbled down post. I jotted this down shortly before signing an NDA for an interview where I expected to learn some related information and I wanted to make sure I had my thoughts written down before there was any possibility of being contaminated with information that's under NDA.
Thanks to Justin Blank for comments/corrections/discussion.
Although this figure is widely cited, I'm unsure about the original source. This is probably the most suspicious figure in this entire post. Hennessy & Patterson cite “Hamilton 2010”, which appears to be a reference to this presentation. That presentation doesn't make the source of the number obvious, although this post by Hamilton does cite a reference for that figure, but the citation points to this post, which seems to be about putting datacenters in tents, not the fraction of infrastructure that's dedicated to power and cooling.
Some other works, such as this one cite this article. However, that article doesn't directly state 82% anywhere, and it makes a number of estimates that the authors acknowledge are very rough, with qualifiers like “While, admittedly, the authors state that there is a large error band around this equation, it is very useful in capturing the magnitude of infrastructure cost.”
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