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Overprovisioning won't solve capacity problem but deepen it

There's a 'genuine mismatch' between what businesses really need, and what they spend their money on, in terms of server capacity. Also, there's a 'total mismatch' related to current capacity management tools and processes, and those that are really needed.

The grim revealing was made by the UK predictive IT capacity analytics provider Sumerian.

It says that more than three quarters (76 per cent) of IT pros overprovision IT infrastructure to save themselves capacity-related problems. Capacity-related issues have had more than half (59 per cent) still experiencing downtime and service degradation, and in almost two thirds (61 per cent) of cases, IT staff is blamed for it.

“The frequent reliance, even today, on overprovisioning to avoid capacity problems has a direct impact on IT costs,” said Tony Lock, Distinguished Analyst at Freeform Dynamics.

“Moreover, the heavy dependence on Excel spreadsheets and the judgement calls of over-stretched IT staff in their spare time is probably not the best answer. A well-managed, more robust approach to capacity planning is critical.”

There’s a small minority reporting very effective overall IT capacity management practices (18 per cent), the report said, adding that 30 per cent use the latest techniques, such as predictive analytics and machine learning.

“In an age of complex, multi-platform environments, where even a single component hitting a capacity issue can cause slowdown or failure, the commercial risk and impact can far outlast the technical fix,” said Peter Duffy, CTO of Sumerian.

“The prevailing approach of ‘winging it’ will neither protect brand trust nor control costs. What’s more, the trend to rely more heavily on seemingly cheap cloud-based resources for infinite elasticity is not the answer and will leave many facing unexpected cumulative costs. In order to successfully control risk and costs to the business, there is a clear need for a more advanced, automated and proactive approach to be taken, using techniques such as predictive analytics.”