AIOps is the use of machine learning, Big Data and automated decision-making to complete IT tasks. AIOps makes it possible to automate processes that would traditionally require significant manual intervention by humans.
As 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 micro services 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 ever increasing 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. However, because traditional automation tools require humans to configure, deploy and manage them, the ability to simplify increasingly complex IT environments is also limited.
AIOps as the Answer to Complexity
In recent years, Artificial Intelligence for IT Operations has emerged as a better solution to the challenge of ever increasing complexity in IT. It 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, it holds tremendous value. Going forward, it 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.
This guide defines AIOps and assesses it’s current state within the IT industry. It also identifies and explains the core components that drive AIOps, as well as the main use cases for AIOps-powered tools.
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