Industry executives and experts share their predictions for 2018.  Read them in this 10th annual VMblog.com series exclusive.

Contributed by Mike Lunt, VP Engineering, Zenoss

Cloud, Data Centers and More: 4 IT Predictions You Won't See Elsewhere

While containers and machine learning are all but foregone conclusions in today's publications, several trends are forming amongst IT insiders around the world. What's old will become new again, and a couple of dark horses will leap forward in the following predictions for 2018.

Public Cloud Meets Its Match

Current wisdom is, "everything will eventually be in the cloud," but that thinking is naively unsound. Hardware sales are poised for a roaring comeback, and IT professionals, who are completely consumed with public cloud migrations, will soon be flanked by a wave of edge computing needed to drive IoT and other real-time compute scenarios. Edge computing of the intelligent sort requires instantaneous responses, often with direct human interaction, and the round-trip delay back to the cloud won't suffice. Cloud computing will eventually be relegated to host the analytics across millions of edge devices (gateways, sensors, etc.) while the pertinent decisions happen in real time within hardware at the edge.

Google Cloud Platform (GCP) Makes a Stand

At this point, even our grandparents have heard of Amazon's cloud Amazon Web Services (AWS), and Microsoft's Azure is frequently touted as a distant contender in the public cloud space where it seems everyone else has been written off. AWS's impressive rise was initially focused on relieving the burden on IT to manage infrastructure; however, Google has been quietly developing a next-generation cloud platform focused on the world of serverless computing with containerization, data stream processing and machine learning as first-order items. GCP's focus on the enterprise will give Google a head start as public cloud transforms into the collection and learning center for IoT edge computing.

Software Defined Takes the Next Step

Software-defined data centers and the virtualized compute, network and storage that comprise them are now in their second and third generations. While all of this virtualization made the data center more malleable and easier to deploy, the side effect was an explosion in complexity. Bluntly said, the human capacity to manage this monstrosity is quickly dwindling, and reliance on machine learning has moved away from being a productivity nicety to becoming a survival tactic for IT operations teams. Software-defined IT operations is the next progressive step in using machine-based learnings to maintain the health of critical business services scattered across multiple public clouds, on-premises facilities and soon-to-be edge devices.

Enterprise IT Comes to Its Senses

Contrary to cloud mythology, IT infrastructure is literally everywhere and expanding at a mind-bending pace -  and trying to manage it with a relatively static on-premises solution is no longer viable. Reliability, scalability and even security are pillars where today's on-premises management systems cannot compete with an elastic, DevOps-driven system in the cloud. Combine the machine-based learnings across multiple environments to generate adaptive algorithms in real time, and no single operations team running a static solution has a chance at parity. Enterprise IT operations teams will finally let go of the control reins and relish the power of the cloud for managing the entire IT ecosystem from deep infrastructure all the way to the intelligent edge.

2018 will be the year when all IT teams are forced to consider how and where IT infrastructure is managed as well as address the systems that manage it efficiently and effectively. Agree or disagree? Tweet @zenoss with your 2018 IT predictions for the cloud, software-defined trends and more.     

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About the Author

Mike Lunt is Zenoss's vice president of Engineering. Mike oversees Zenoss's global engineering teams, which are responsible for both the open source and commercial products at the heart of Zenoss's offerings. Mike joined Zenoss in 2008 and has over 20 years of experience delivering enterprise on-prem and SaaS based solutions to the Fortune 500. Prior to Zenoss, Mike served as a director of R&D at BMC Software, responsible for delivering various ITOM solutions, and he was a key change agent in BMC's transformation to Agile development techniques. Mike joined BMC through the successful acquisition of Evity, providing Web transaction monitoring solutions, where he lead the Operations and QA teams. Prior to Evity, Mike was a founding engineer of Onebox.com, which was acquired by Phone.com, and a part of other early stage companies such as Aquity. Mike holds a Bachelor of Science in Mechanical Engineering from Oklahoma State University.