Intelligent Data Centres Issue 35 | Page 32

efore the rise of cloud computing and the

B consequent proliferation of remote compute and storage assets , data centres were relatively straightforward systems that could be staffed by just a handful of qualified welltrained and experienced professionals .

However , the emergence of new – and generally more complex – offerings in the cloud computing space ( SaaS , PaaS , IaaS , etc .) has transformed the typical data centre into a high-tech mission critical clearinghouse for a variety of critical corporate workloads .
The challenge of servicing this new demand is not only being felt by the hyperscalers such as Amazon AWS , Microsoft Azure , Google GCP etc ., but is having an impact right across the hosting / provider community .
As the entire sector scrambles to keep up , the demand for IT professionals with the requisite skillsets needed to manage these increasingly complex and mission critical environments has skyrocketed .
Unfortunately , the number of qualified candidates for these positions still seems to be decreasing rather than increasing . As such , data centre management teams are facing a severe staffing shortage that , if unaddressed , may well one day threaten a company ’ s ability to adequately maintain either its own digital assets or a provider ’ s ability to maintain its service offering .
Given that as a society we are being driven towards what appears to be a fully automated and digitally dependant world , this is not great news .
Most corporate stakeholders are fighting tooth and nail to hang on to the talent they still have , in what has become a very competitive marketplace , however , this will only work for so long before the cracks become too big to paper over .
Maybe in order to keep pace with the growing demand being placed on data centres , we need to let go of the past and start looking to the future with a more hybrid approach , which not only works collectively to attract new talent into the sector but also invests in solutions that allow data centres to thrive in the absence of extensive human oversight .
Thankfully , Machine Learning ( ML ) technology offers a solution , assisting with a range of server functions without automating IT management entirely . ML platforms combined with advanced heuristics can autonomously perform routine tasks like systems updating , security patching and file backups while leaving more nuanced , qualitative tasks to the IT personnel .
Without the burden of handling each and every user request or incident alert , IT professionals can assume oversight roles for tasks that previously required their painstaking attention , which in turn will free up more time to focus on the more holistic management challenges .
For both individual companies and third-party data centre providers , this partnership-based approach may well provide a happy medium between outright automation and helping to elevate , rather than solving the chronic understaffing issues the sector is soon to face . If fully embraced , this ‘ hybrid ’ management model could well become the norm throughout the data centre industry .
Machines are not going to replace human workers – well at least not anytime soon – but what ML can do is help overworked IT teams do everything required to keep a data centre running smoothly . ◊
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