Google Cloud takes a gap year. It may come back with very different ideas
Twelve months without refreshment can break an addiction
Opinion Taking a look at the latest financial results from Google/Alphabet made some of us do a double-take ... and not because of the $40bn+ in ad revenue.
If you read closely, you'll see that Google Cloud has lessened its habitual loss by extending the operational lifespan of its cloud servers by a year, and stretching out some of its other infrastructure for longer.
Google is not a bit player on the market; it could push ahead with its upgrade cycle with some adjustments if it wanted to, and say as much, but no. It is opting out
So what, you might say, wearily playing along in the office with hardware that gets refreshed less often than an octogenarian teetotaller. But this is Google Cloud, one of the headline players in the most important enterprise IT market of our time.
If it's saying that it's improving its competitive offer by not bothering to upgrade its core CPU farm, that says a lot about the cloud, the processor market, and the future of both.
You can see the cloud as it is sold to you, easing the capex/opex ratio, adding flexibility, dialled-in scale, and performance while reducing managerial overhead. In a different light, it's also a fantastic experiment in abstracting what IT actually means in business: paying other people to worry about all the boring stuff on your behalf.
Security, energy, hardware tending, meeting demand at a global scale – or just giving you an instant few cores of server to run up an idea or proof of concept without you having to buy so much as a multiway plug.
So when Google says in effect it doesn't care about upgrading CPUs this time around, you can believe it. Issues like the chip shortage and global economic uncertainty will factor into the decision, but reports from the front line of the server industry indicate that if you've got the clout, you get your share. Google is not a bit player on the market; it could push ahead with its upgrade cycle with some adjustments if it wanted to, and say as much, but no. It is opting out.
This is even more significant because Google is one of the most processor-focused providers. It reveals the processors it uses for different classes of task, sometimes even letting you pick the ones you want, and sometimes they'll even be in the region and the available configuration that you fancy.
Compare that to the choices offered by Amazon AWS EC2, which are number of cores per instance and whether you want multithreading. That's it, and that's much more typical of cloud service providers (CSPs). For most workloads, these firms don't compete on CPU. Storage tiers get the works with latency versus capacity versus cost, but compute performance? Acceptable is good enough. You will get virtual machines running on virtual CPUs, and you will like it.
This leaves the chip companies with some hard questions. They really can't shake the "performance" metric as the drug of choice, and it's still an easy sell to investors.
Headline numbers look good, HPC is always a happy place to be, and you can find plenty of other places where you need lots of performance grunt. General-purpose CPUs have to face off against GPUs and other hardware-optimised silicon there – although massively parallel tasks mostly don't care about x86's legacy.
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And, as Apple has proven with its M1 architecture, x86 legacy doesn't have to count for that much elsewhere these days. It's not that CSPs and data centres are gagging for M1s, which work so well because they are so highly evolved for Apple's market.
The x86 emulation overhead is perfectly bearable there while the ecosystem catches up with native versions; acceptable is good enough, and the path forward is clear.
But CSPs aren't gagging for the latest x86 magic either; they'll happily take it at the right price and at the right time, but they'll leave it for a while too. That's a gap, which is suddenly much more interesting. MacBook owners like battery life, but CSPs really don't like the new era of accelerating energy costs.
Chancing your Arm
The ARM-ification of servers at scale has been predicted a few times now, although it's never been quite clear how you get there from here. The M1, however, is a great proof of concept: and the energy bills, specifically, are a great motivator to pay attention.
It is easy now to imagine what the M1's cloud-component cousin would look like. It could be a system-on-chip with a set of computing cores that are intrinsically efficient and can be even more so with the right workload, very tightly coupled to IO and integrated memory, but instead of being tuned for an Apple machine, the SoC would work very well for a particularly configured VM – and work acceptably for others. There would be nothing here that would be beyond the talents of a competent design team, no matter where they work.
With a sea of these, a CSP could have a new, performant, and very competitively priced tier that rewards workloads that are optimised for the native, highly efficient modes, but one that would remain competitive for the older tasks that would otherwise be happy running on the older hardware already in the racks.
The CSPs would get enough wriggle room to price-nudge the clientele into the low-energy workload domain while still picking up a bit more margin.
The world has already moved into the sort of containerised, multi-platform, open-dev, automated regime with the necessary tools and techniques for making apps for such an architecture. That means not much novel engineering would be needed at the codeface.
The motivation is there, the methods are at hand, and the barriers to transition are much reduced. Maybe Google's gap year is an indication that business will not resume as usual. ®