AIOps is an emerging system that combines big data and AI or machine learning functionality to enhance and partially replace a broad range of IT operations processes and tasks. These tasks include availability and performance monitoring, event correlation and analysis, IT service management, and automation. By adopting and levering AIOps, IT organizations can automate and enhance IT operational practices and access continuous insight into the performance of their business services. The primary objective of AIOps is to provide insights from the IT infrastructure using machine learning and reinforcement learning, and they can act upon these insights using cognitive automation.
AI and AIOps technology bring business KPIs and IT SLAs closer to the desired level, thus significantly transforming enterprise IT operations to make them more business driven. Finally, the promise of AIOps to IT operations is to operate in a better, faster, and scalable fashion. AIOps adoption will enable the IT organization to be the first citizen in the enterprise digital transformation journey. The adequately planned AIOps adoption enables the IT team to be the critical partner of the business.
This is the starting stage of AIOps in any organization. Organizations having traditional monitoring tools usually that are working on a reactive mode. The IT team receives thousands of events every day from the chatty monitoring tools and struggle to figure out where to focus.
In this level, AIOps tools and processes can quickly determine the root cause and notify the IT operations team. This will help the IT operations team to take quick action before the problem is noticed by the end-users. Also, it reduces the impact on business operations.
This is the third level with more analytics to foresee future events like service outage or infrastructure capacity exhaustion with a high degree of probability. An AIOps platform provides predictive recommendations to the IT operations team to minimize or eliminate business impacts.
IT organizations at this prescriptive level can get prescriptive recommendations from the AIOps systems and can make better and faster-informed decisions. This will enable them to be a better agile organization to deal with the fast-moving business requirements with the highest level of efficiency.
The automated IT organization can leverage an advanced AIOps platform that can provide resource optimization and auto-remediation recommendations to the automation platform based on AI- based analytics and keep the system up and running without much human intervention.