Taking the Guesswork Out of Capacity Planning

Is There a Way to Take Guesswork out of Your Capacity Planning?

From small businesses to major corporations, planning capacity is a common preoccupation for those working in IT. Predict too high a demand, and you may end up paying way more than is needed, but under-estimating may cost more in lost productivity and acquisitions that weren’t in the budget.

If, like most IT departments, you’re under the gun to produce more accurate budgets, neither option is attractive. Nobody relishes the walk of shame to the finance director’s office to explain discrepancies.

So, how do you make capacity planning less about guesswork and more about fact?

The IT Capacity Blow-Out

Like many things in IT, there is no perfect answer. A business has many variables, and not all can be neatly predicted. Cloud ‘as a service’ options, of course, offer some neat ways to only pay for what you use, but this is not without its challenges. It is estimated that up to 40% of paid-for cloud capacity sits idle which, if you do the math, can torpedo most budgets.

The perils of on-premise over-provisioning are better known, and at least as tiresome. However, most workplaces have their frequent culprits, high-demand applications and peak-time misery, so it is not uncommon to squeeze a little more out of the budget to solve the immediate problem.

How AI is Transforming Capacity Planning

There is light at the end of the capacity planning tunnel, in the form of Artificial Intelligence (AI). Leading the charge is Nimble Storage, a HPE acquisition that is making waves in the infrastructure space. A tool called InfoSight is challenging traditional storage thinking, using predictive analytics to assess massive amounts of data to identify patterns of behaviour. From here, it predicts where extra capacity will be needed, when, and how much. This takes the guesswork out of planning, and, better yet, employs an automated ‘self-healing’ capability to save you time.

AI Beyond the Storage Environment

What’s particularly neat about the way AI is being employed is that the insights go way beyond just storage. From their position in the infrastructure eco-system, Nimble Storage devices have a view of user and data behaviour. They can spot performance issues and predict hardware failure.

Between AI-driven smart storage and instantly scalable cloud, the potential is there to grab back a handy amount of IT spending. There is one obstacle, though, before you get carried away. Both on-premise and cloud success depend on the right starting point, which means careful assessment from someone without a vested interest in either direction.

From On-Premise to Cloud – and Back Again

Our hybrid specialists at mcr often find themselves helping unravel cloud transitions that haven’t gone to plan, re-assessing which workloads should reside where and in some cases aiding transitions back to on-premise or private cloud environments. Even where transitions have been largely successful, our team recommends regular re-assessments as different cloud offerings emerge and new technologies become available. After all, the better you know your environment, the less guesswork involved in planning your next move.

To learn more about Nimble Storage and other intelligent infrastructure possibilities, contact mcr’s friendly experts.

2018-05-02T04:56:07+00:00 January 13th, 2018|Categories: Blog|0 Comments