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Do you have the right tools for hybrid IT?

Chris Purcell

 

istock-610855316-100742085-large.jpgIn the move to hybrid IT, enterprises are experiencing the familiar challenge of technology management needing to catch up with new compute innovation. Cloud adoption (public and private) is occurring at a rapid pace with cloud and big data on the rise, and IT teams do not have the management tools necessary to extract value from data in a way that is operationally or economically efficient.

Dana Gardner, Principal Analyst at Interarbor Solutions, tackles this issue in his podcast BriefingsDirect Voice of the Analyst podcast series, where he sits down with leading IT industry analysts to discuss the mounting complexities businesses face as they transform their IT strategy. Recently, Gardner met with Paul Teich, Principal Analyst at TIRIAS Research in Austin, Texas, to examine the need for management solutions in a successful digital transformation.

Big data on a small screen

Despite having an overload of information on a single pane of glass, IT managers still don’t have a full picture. Big data is flowing at a rate that humans can’t comprehend in real time, meaning IT needs a big data tool to perform analysis.

Right now, there are so many moving parts in a hybrid IT environment that IT managers are unable to keep track of inefficiencies. At mid-sized and large corporations, for example, developers often use multiple credit cards to purchase multiple cloud services, leaving IT with no visibility to track stranded instances. Mismanaged data can result in a big waste of money.

To combat the mounting complexity of hybrid IT, Gardner suggests that enterprises should consider looking to a data-driven approach. Analytics will provide measurable benchmarks to gauge efficiency across the right mix of infrastructures. Even with this approach, however, gaining value from data is still a challenge.

“I think we have to get past having a screen full of data, a screen full of information, and to a point where we have insight. And that is going to require a new generation of tools, probably borrowing from some of the machine learning evolution that’s happening now in pattern analytics,” said Teich.

A data-driven approach powered by machine-learning

To track efficiency, management needs to focus more on where data is stored and how to move it. Since internal IT departments no longer run all IT for an enterprise, management needs a tool to segue data into visible workflows to gain insight.

Teich advocates for machine learning, which can look at a bigger picture, manage more variables, and learn across more data points than any human can. Most important, machine learning helps enterprises get better economies of scale, which will help IT teams keep a handle on costs. With the ability to aggregate the purchases of storage and compute instances, IT managers can understand what jobs are running where and how much capacity is needed across a hybrid IT environment.

“It also comes at an auspicious time as IT is trying to re-factor its value to the organization. If in fact they are no longer running servers and networks and keeping the trains running on time, they have to start being more in the business of defining what trains should be running and then how to make them the best business engines, if you will,” said Teich. This transition for IT, from an architecture function to a procurement function, will be just as powerful a role in business’s digital transformation.

“…Getting that machine-learning capability attuned to your specific hybrid IT panoply of resources and assets is going to be a gift that keeps giving,” said Gardner. Having insight into a business’s global infrastructure will enable IT teams to be better prepared for risk and unexpected changes to the business environment.

Gardner and Teich agree that enterprises that take advantage of machine learning now will have a head start over competitors. Enterprises ability to differentiate themselves from other cloud service providers doing the same will depend on how well they optimize their services by utilizing a customized management approach.

 “If the baseline technologies are becoming commoditized, then optimization — that algorithm-like approach to smartly move workloads and data and providing consumption models that are efficiency-driven — that’s going to be the difference between a 1 percent margin and a 5 percent margin over time,” said Teich.

A need for third-party management vendors

Currently, public cloud giants have little incentive to work together, so third party providers need to step in to help manage hybrid IT environments.  Teich points to Hewlett Packard Enterprise (HPE) as the only vendor actively trying to fulfill this position.

At the recent Discover event in Madrid, HPE announced the industry’s first multi-cloud management solution, HPE OneSphere. Through its software-as-a-service (SaaS) portal, HPE OneSphere gives customers access to a pool of IT resources that spans the public cloud services they subscribe to, as well as their on-premises environments. Using this new tool, organizations are able to seamlessly compose, operate, and optimize all workloads across on-premises, private, hosted, and public clouds. HPE OneSphere also provides dashboards based on different user roles that offer business analytics. HPE OneSphere is designed for IT operations, developers, and business executives seeking to build clouds, deploy applications, and gain insights faster.

New management capabilities such as HPE OneSphere will be crucial to the success of IT enterprises. With these tools, IT will help to eliminate inefficiencies and leverage new technologies better as they move toward a business-driven digital transformation.

HPE has assembled an array of resources that are helping businesses succeed in a hybrid IT world. Learn about HPE’s approach to managing hybrid IT by checking out the HPE website for HPE OneSphere. And to find out how HPE can help you determine a workload placement strategy that meets your service level agreements, visit HPE Pointnext.

Chris

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About the Author

Chris Purcell

Composable Infrastructure, Integrated and Multi-Cloud management, Hyperconverged Infrastructure and Cloud

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