Gartner predicts that by 2025, half of cloud data centres will deploy advanced robots with AI and machine learning capabilities. But what does this mean?
As net-zero carbon goals are at the forefront of all data centre manager’s minds, so too is increasing efficiency and reducing costs. AI has been touted by some as the next step to increase efficiency, reduce costs, minimise human error and redeploy those mundane but essential tasks that we all groan at. On the face of it, what’s not to love?
Advances in AI technology, especially when considered from a machine-learning viewpoint, seems to give data centre managers and teams all they need from this exciting new frontier. But is that the whole story? Can AI really act as the magic bullet that will solve many of the common issues found in the quest to run a data space both effectively and efficiently?
AI services, combined with an intelligent and reactive DCIM system could be the powerful combination data centre managers have been waiting for. But enough with the theory – it’s also important to look into what real-life roles AI could play in a data centre to make a difference to day to day running, affect net-zero targets and improve functionality.
Three major ways AI is transforming the way data centres are run is in power efficiency, cooling and staffing. Once those areas have been optimised, data centres will see efficiencies in performance, reliability, reduced costs and environmental impact.
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AI Knows What to Cool and Where
Limited visibility on data centre cooling meant real-time operational changes weren’t a possibility, particularly in larger data centres with racks upon racks of servers to account for.
The challenge is to achieve optimum cooling practices across a vast range of equipment and over a range of locations. And that’s before considering the number of obsolete and idle servers that could be needlessly using energy and being included in operations and maintenance schedules.
That’s where AI comes in. Knowing what to cool… and where… and how much… is made simple when AI capabilities and machine learning are integrated with DCIM in data centres.
AI systems open up the ability to monitor and predict cooling requirements based on real-time data. When combined with AI, DCIM can semi-independently optimise the entire data centre space taking advantage of weather conditions and changes in operations to seamlessly adjust cooling levels and reach peak efficiency.
Don’t believe us? Ask Google. They credit AI for halving their energy usage and saving 30% on their energy bill. These kinds of efficiencies and savings are likely to become commonplace for data centres.
Relieve Pressure on Staffing Levels with AI
As data demands continue to grow, so too does the need for extra staff. The Uptime Institute predicts that by 2025 there will be an estimated 2.3 million full time staff needed to run data centres. However, there is a serious skill shortage of skilled data centre professionals and data centres are struggling to attract talented staff or even retain existing staff.
We know that AI can take over the more mundane and everyday tasks needed in a data centre. Could this be the answer? Robots are already being tested in data centres to carry out basic maintenance tasks.
“Data centres are an ideal sector to pair robots and AI to deliver a more secure, accurate and efficient environment that requires much less human intervention.” says Sid Nag, Research Vice President at Gartner.
But no matter how many robots you deploy, there will always be a need for skilled staff to oversee the automated workforce and make key decisions
Outages Could Be a Thing of the Past
As outages become more and more common, being able to react quickly to downtime, or even prevent it, is incredibly important.
If AI can effectively and systematically carry out maintenance tasks on schedule as well as predict where future maintenance might be needed as well as prevent overheating and human error, outages in data centres could be avoided.
Here Comes AI with its Safety Helmet
Data centres are up there as one of the most hazardous environments to work in, with risks ranging from electrical shock to exposure to dangerous chemicals.
Tech giant Meta is looking into how their AI can model data centres operating under extreme environmental conditions that would be unsafe for their human staff.
AI systems and robots aren’t just good for the mundane tasks, they can be deployed in physical environments that present significant risks to traditional workers.
So, Is AI Worth the Hype?
But hang on a minute, it’s not all sunshine and rainbows. In fact, emerging technology such as AI and machine learning is accounting for an increase in computing capacity which, in turn, means an increase in energy usage and carbon emissions.
Is it enough that AI can also work to reduce both power consumption and carbon emissions? Does this outweigh the negative environmental effect AI use within all industries is having?
To really get the most out of AI in data centres, it needs to work hand in hand with existing operations. Combined with a DCIM that can gather key data, AI can be used for good and identify patterns within data centres where actionable insights can be achieved.
Then, DCIM can provide data centres with clear visibility of all assets, as well as having prescience over future issues and operations. With AI by its side, DCIM has the option to upgrade from regular monitoring and reporting on data to having a level of autonomous decision making to help reach optimum efficiency.
The power to make even the smallest of adjustments to individual pieces of equipment can ensure cooling and power usage is as efficient as can be, server life is prolonged, and outages are prevented.
The way things are going, AI DCIM could almost eliminate risk from human error one day in the not so distant future, and ensure there is the capacity that will be needed in the era of big data.
So, it seems that AI has a lot more going for it than against it.
As demand increases and data centres increase in complexity, we will be relying more and more on the cloud and AI, which will become commonplace in modern data centres. To ensure data centres can keep up with these advancements, they’ll need top notch DCIM.
