A friend of mine, Marco Verzijl, has been fighting for more transparency around data center sustainability and energy consumption for years. Whenever we talk about data centers, energy efficiency or sustainability, Marco usually comes back to the same basic point: claims are easy. Measurements are much more interesting. That is also the central idea behind a recent article he wrote for DCpedia.net (text in Dutch). Marco argues that a sustainable data center should not simply say it is sustainable. It should be able to prove it with reliable, traceable and independently verifiable data. I think that distinction is becoming increasingly important.
AI changes the discussion
Data centers have always consumed substantial amounts of electricity, but AI is rapidly changing the scale of the discussion. Powerful GPUs increase power densities, cooling becomes more demanding and access to sufficient grid capacity is turning into an important economic issue. At the same time, we increasingly depend on data centers. Hospitals, banks, government services, industrial systems, cloud platforms and, of course, AI applications all rely on physical digital infrastructure.
So the useful discussion is probably not whether we should have data centers at all. As Marco puts it, the real question is: which data centers do we need, for which applications, in which locations and with what demonstrable energy and societal performance? Answering that requires data.
PUE is only part of the story
One thing I particularly like about Marco’s argument is his criticism of looking at isolated sustainability indicators. Take PUE, or Power Usage Effectiveness. It is an important metric because it tells us something about how efficiently a data center uses energy for cooling, power distribution and other supporting infrastructure. But it does not tell us whether the servers themselves are doing anything useful.
Marco uses a nice analogy: an extremely fuel-efficient truck that drives around almost empty is still being used inefficiently. The same applies to a data center. A facility may have an excellent PUE while large amounts of IT capacity are hardly being used.
That becomes especially interesting with AI. Two models performing roughly the same task can require very different amounts of computing power and therefore energy. Eventually, we need to look beyond energy consumed per building and start asking how much useful digital output we receive per kilowatt-hour.
Green electricity is not enough
The same applies to renewable energy claims. Saying that a data center uses “100 percent green electricity” sounds convincing, but it does not necessarily mean renewable electricity physically powers that facility every hour of every day. Certificates and annual contractual arrangements can make the reality considerably more complicated. Water consumption, backup generators, heat reuse, hardware utilisation and even the lifetime and recycling of servers should also be part of the picture.
Which brings us back to transparency. Marco writes that sustainability data should be based on actual measurements, connected to known measuring points, traceable to source data and independently verifiable. Otherwise, sustainability risks becoming primarily a communications exercise. That seems like a useful principle far beyond the data center industry. Because in the end, as Marco concludes, a sustainable data center is not one that calls itself sustainable. It is one that can prove it.
You can read his article here: https://dcpedia.net/een-duurzaam-datacenter-begint-niet-bij-een-belofte-maar-bij-controleerbaar-bewijs/.
