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By Gary Thome
According to a recent report, the hybrid cloud market is exploding. It is expected to grow from $44.60 billion in 2018 to $97.64 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 17.0% during the forecast period.
As hybrid cloud deployments enfold, organizations can expect to encounter some long-term challenges. In a recent podcast, Dana Gardner, Principal Analyst at Interarbor Solutions and John Abbott, Vice President of Infrastructure and Co-Founder of The 451 Group, discuss the growth of hybrid cloud and what challenges the enterprise is facing. I found the interview insightful, especially their thoughts on increased complexity, uncontrolled costs, and an ever-widening skills gap.
Solving the complexity problem
As organizations seek a mix of hybrid and multi-cloud infrastructure, they are implementing cloud in a way that wasn’t anticipated years ago. “CAPEX to OPEX, operational agility, complexity, and costs have all been big factors,” explains Abbott. “Also, on-premises deployments continue to remain a critical function. You can’t just get rid of your existing infrastructure investments that you have made over many, many years.”
Gardner suggests that technologies such as artificial intelligence (AI) and machine learning (ML) could help solve the hybrid cloud complexity issue. Abbott agrees both present a huge potential. “IT tools are in a great position to gather a huge amount of data from sensors and from usage data [and] logs, and pull that together. We can then more clearly see patterns and optimize in the future.”
I think a combination of AI and automation is critical to simplify the complexity of hybrid and multi-cloud. Newer applications are incredibility complex with lots of moving parts; sometimes developers can make hundreds of changes a day to a single application. With this type of complexity, traditional governance models just won’t work, which is why HPE InfoSight is so important. HPE InfoSight is an industry-leading predictive analytics platform that brings software-defined intelligence to the data center with the ability to predict and prevent infrastructure problems before they happen.
Control costs, or they will control you
Gardner and Abbott discuss at length the growing challenge of controlling cloud costs. “Cloud models can significantly reduce cost, but only if you control it. Sizes of instances, time slices, time increments, and things like that all have a huge effect on the total cost of cloud services,” Abbott explains.
Abbot gives the example of the large number of people who may have authority to order services. “If you have multiple people in an organization ordering particular services from their credit cards, that gets out of control. I think Amazon Web Services (AWS) alone has hundreds of price points — things are really hard to keep a track of.”
To gain control over your spending on cloud, Abbot believes IT admins need better management tools. “They need a single pane of glass — or at least a single control point — for these multiple services, both on-premises and in the cloud.”
Organizations do indeed need better multi-cloud management tools. Yet, in many organizations, IT needs to play a stronger role in managing governance of applications, because they understand it better than anyone else. The enterprise still needs someone to pay attention to what is going on and proactively make decisions. IT needs to periodically look at where everything is deployed and make appropriate decisions such as removing zombie machines that aren’t being used, or move an application from one cloud to another. When IT takes responsibility, they will naturally select the tools they need to become more efficient.
What about the skills gap?
Both analysts mention the current skills gap as a concern for today’s enterprise. Gardner wonders who in the enterprise has the knowledge and expertise to oversee all of the financial functions involved with multi- and hybrid cloud deployments. This person needs to understand the technology, and also the economic implications, such as forecasting and budgets. Gardner doesn’t believe the typical IT director or admin has those skills right now.
Abbot thinks this role is evolving with a new generation of IT admins. “There are skill shortages, obviously, for managing specialist equipment, and organizations can’t replace some of those older admin types. So they are building up a new level of expertise that is more generalist.” He goes on to say that developers and the systems architects will also need the help of new automation tools, management consoles, and control planes.
Abbot believes that organizations should look to a more experienced partner to help them in this rapidly changing and complex environment. Abbot references the recent acquisition of BlueData by Hewlett Packard Enterprise (HPE). “The experts in data analysis and in artificial intelligence (AI) and the data scientists coming up are the people that will drive this. And they need partners with expertise in vertical sectors to help them pull it together,” concludes Abbot.
Gary Thome is the Vice President and Chief Technologist for the Software-Defined and Cloud Group at Hewlett Packard Enterprise (HPE). He is responsible for the technical and architectural directions of converged datacenter products and technologies.
To read more articles from Gary, check out the HPE Shifting to Software-Defined blog.