How does AIOps work?

AIOps has two main components: Big Data and Machine Learning. It requires a move away from siloed IT data in order to aggregate observational data (such as that found in monitoring systems and job logs) alongside engagement data (usually found in ticket, incident, and event recording) inside a Big Data platform. AIOps then implements Analytics and Machine Learning (ML) against the combined IT data. The desired outcome is continuous insights that can yield continuous improvements with the implementation of automation. AIOps can be thought of as Continuous Integration and Deployment (CI/CD) for core IT functions.