Cloud, colocation or on-premise? Consider all options

Spencer Lamb, chief commercial officer of datacentre operator Kao Data, is more sceptical about the fate of on-premise. Beyond hardware that needs to be retained for regulatory or data sovereignty reasons, most businesses will be sourcing future data capacity from their current cloud providers, he predicts.

That’s not necessarily the cheapest option for enterprises, however. “It might be quite meaningful from a cost perspective,” he says. 

Following the rush to the cloud, the cost implications should have prompted some companies to move back to on-premise, but it hasn’t, according to Lamb. “I thought it might happen with AI, because potentially the core per hour rate for AI is going to be far higher, but it hasn’t.” 

Lamb’s advice for CIOs is to be wary of being tied into particular providers or AI models, noting that Microsoft is creating models and not charging for them, knowing that companies will still be paying for the compute to use them. 

Lamb also says that, whether we’re talking on-premise, colocation or cloud, the potential for retrofitting existing capacity is limited, at least when it comes to capacity aimed at AI. 

After all, those GPUs often require liquid cooling to the chip. This changes the infrastructure equation, says Lamb, increasing the footprint for cooling infrastructure in comparison to compute. Quite apart from the real estate impact, this isn’t something most enterprises will want to tackle. 

Also, cooling and power will only become more complicated. Andrew Bradner, Schnieder Electric’s general manager for cooling, is confident that many sectors will continue to operate on-premise datacentre capacity – life sciences, fintech and financial, for example. But he also expects power and cooling requirements to continue to rise, so they must be considered for new builds. 

“If you’re designing for today’s chips, you also have to think about two or three generations that might come into the datacentre during that time, and how you design for that without a full retrofit of your infrastructure.” 

It’s not just on the cooling side, he adds. “It’s on the power side, because as you start to get over 200 kilowatts of rack, you have to fully redesign how you get power to those racks and servers.” That includes heavier gauge cable, bigger breakers and ultimately a shift from AC power to DC power. 

“How do you address these challenges? Because they’re real, they’re immediate, and we’re going to have to figure out how to do this as we look at that next generation of silicon that’s going to be coming,” he says.

So, will there be net new datacentres? Undoubtedly. And CIOs will likely demand a mix of capacity – cloud, colocation and possibly some on-premise – depending on what their long-term strategy is. 

IDC’s Madsen advises approaching datacentres from a data governance stance right from the outset. 

“You need to start thinking about this at the very beginning of projects because the investment as you go through that project is really high,” she says. “So, consider what your return on investment is going to be, what your appetite for risk is with the data that’s going to be used.”  

And you need to have transparency on costs and pricing – generative AI projects are being measured as business projects, not pure technology projects, she adds. 

And, given that cloud providers or datacentre providers are likely to be part of your strategy, Madsen advises having conversations around the innovation roadmap of those providers.

Few will be able to go it entirely alone. “I think you’re going to see a lot of movement over the course of the next year, as things stabilise and people go, “Actually, we do need a trusted partner to help with it’.”