Hardware and software systems become more efficient, sophisticated and useful, they also tend to grow more complex. For example, when virtual machines replaced bare-metal software environments, virtualization created a new layer of complexity that IT teams had to plan for and manage. The shift in recent years toward microservices and containers similarly increased the number of components that go into a single application, as well as the challenge of orchestrating all of them.
Traditionally, the ability of IT Ops teams to handle everincreasing complexity has been limited. Hiring more staff is the most obvious response, but that is not a cost-effective solution,
or one that can scale well. Automation tools can also help handle added complexity.
In recent years, Artificial Intelligence for IT Operations (AIOps) has emerged as a better solution to the challenge of everincreasing complexity in IT. AIOps leverages Big Data, data analytics and machine learning to provide insight and enable a higher level of automation (one that does not depend extensively on human operators) for the management tasks that modern infrastructure and software require.
For this reason, AIOps holds tremendous value. Going forward, AIOps will play a key role in enabling new efficiencies for IT teams.
It will also make practical the adoption of complex next-generation technologies that cannot be managed successfully using traditional solutions. In short, businesses of the future won’t survive without the assistance of AIOps. If your business has not yet begun adopting AIOps-powered solutions, now is the time for assessing, planning and implementing AIOps tools that can drive business value.