AIOps and the New IT Skill Set It Requires
If you’ve been in IT Ops for more than a few months, then you don’t need a blog post to tell you what your job is. But, with so much ongoing change in the world of IT Ops, and especially given the fact that very major developments to the role of IT Ops are on the horizon, a close look at how significant shifts in the role will cause the need for the development of new skills is more than a little warranted. AIOps will impact the role of IT Ops in many profound ways; there simply is no way around it. And with a sizable change in the role of IT Ops will come to the need for a new IT skill set – one that integrates with emerging technology while taking advantage of the benefits of machine learning and its impact on general workloads in the IT department and across the organization. In this post, we’ll take an in-depth look at how AIOps will impact the IT Ops role, and what new skills that change will necessitate.What Is AIOps
AIOps, simply put, is the application of machine learning and artificial intelligence to the operation of IT. By employing artificial intelligence in the examination and manipulation of big data, including both IT data and business data, AIOps strives to provide better service levels and more efficient operation of processes. It does this by applying machine learning to the understanding and management of optimal operation, and through the detection of anything hampering optimal operation. AIOps can also provide a suggested response, or it can automatically execute an appropriate response. It does all of this at speeds that put traditional IT Ops, with its reliance on human analysis and expertise, to shame while dealing with the ever-increasing issue of data overload. As you might expect, this frees up human capital to focus on the aspects of IT Ops that cannot be managed automatically by AI — empowering IT teams to spend their time on more complex, value-driven projects.The Traditional IT Skill Set Vs the New IT Skill Set
The traditional IT Ops skill set, because of the demands of traditional IT operations, is necessarily concentrated in the area of data analysis for the design, production, and management of various environments utilized to deliver services and applications that attempt to meet internal and/or external stakeholder expectations. In order to fully realize the potential benefits of AIOps, IT professionals will need to enhance their skill sets so that they can manage the work of AI, rather than doing the work directly. In addition to many traditional IT Ops skills, the following enhanced skills will also need to be learned in order to facilitate the transition.- Auditing and Management of Machine Learning Processes
- IT Ops professionals will need to augment their skill set with the ability to audit and manage machine learning processes, helping AI to anticipate and learn to accommodate the seasonal, one-time, and industry-specific issues that AI will not be prepared to deal with otherwise.
- Playing Outside the Sandbox
- The ongoing trend of integrating IT best practices through ESM efforts across organizations will deepen with the advent of AIOps, and IT Ops professionals will need to get even more involved beyond the IT sandbox, working with other departments to help ensure the successful integration of AIOps across the organization.
- Management of APIs and Their Impact
- With much of the responsibility for management of applications migrating from developers to IT Ops, understanding the impact of applications on the IT environment and anticipating and proactively managing AI to deal with issues will be key to IT operations success.
The Generalist Approach to AIOps Management
Where once IT Ops professionals could (or almost needed to) take a myopic approach to the management of operations and processes, a more generalist approach will be needed going forward. Managing AIOps, anticipating needs and issues within IT and across organizations, and driving innovation are not only possible but also becoming increasingly mandatory. Learn more about the ways data can improve IT service management.
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