Many companies are in a dilemma of choosing cloud or on-prem for their infrastructure. Somehow it has become a “truth” that cloud services are cheaper than local operations. But do you know how much your cloud services cost and what your total cost is? And how you compare it to others? Here is an AI service which gives you full control.
Putting your hand on your heart, do you know if it pays to move your infrastructure over to one of the IT giants’ cloud services? Probably not, but that’s not surprising. If you work in a large organisation, it’s incredibly complex to calculate an actual total cost (TCO of IT). Let alone figuring what TCO you’d end up with after upgrading local hardware to cloud services like Azure or AWS.
”Until recently, the cost of calculating an accurate TCO of IT, even with a TCO calculator, has been high, both in terms of time and consulting hours. Now it is possible to speed up calculations significantly and achieve higher precision thanks to artificial intelligence,” says Peter Werdenhoff, Hybrid IT Specialist Sales Manager at Hewlett Packard Enterprise in Sweden.
HPE collaborated with Denmark’s Kostner to create an AI-based service, called Clarity, for calculating TCO of IT across multiple scenarios. And in the Nordic region, this service saves several large organisations a significant amount of time and money, says Peter Werdenhoff.
”With this type of service, the criteria for deciding where to place your load becomes much more granular and accurate. Of course, leading to better decisions.”
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In many of the cases HPE and Kostner worked with, it seemed local operations were cheaper than the cloud. Thus, the established truth that cloud service costs less does not always hold. But calculations often don’t show this, because many companies don’t have good enough control over their TCO of IT.
”I’ve seen so many examples where people take a chance on which form of operation is best. Because the alternative is weeks or months of work together with consultants to reach a decision. But it’s now possible to achieve a well-informed decision in just three days, from start to finish.”
But are there any drawbacks to relying on artificial intelligence to figure out the basis instead of consultants? Peter Werdenhoff believes that in some cases, it can certainly help to augment decision making with consultancy support. At least for the time being.
”It builds on machine learning, meaning all the data points loaded connects to an AI engine, which then compares – anonymously of course – to other cases. So the more customers who use the system, the better the service becomes. The service will sharpen itself over time, becoming better and better.”
Clarity is primarily an optimisation tool, but it’s not only a matter of comparing what a cloud service costs against local operations. It’s also an effective way of creating an inventory for local systems and licenses. The critical thing to remember is that there are no simple solutions. In some cases, a cloud service may be the right choice, in another a local operation and a third a service provider.
”This service enables you to get a timely and accurate picture of utilisation with minimal effort and to be able to streamline your systems. It’s high time everyone leaves the guessing game and makes decisions based on facts,” concludes Peter Werdenhoff.
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