Artificial intelligence operations (AIOps) and machine learning operations (MLOps) are new subjects and often used interchangeably. AIOps, as defined by Gartner, which coined the term, is the process of combining big data and ML to automate IT operations, including event correlation, anomaly detection and causality determination.
In a special guest feature with Times of India, Sudeep George, VP of Engineering at iMerit discusses the need for AIOps, its advantages and the several ways that enterprises are using AIOps today.
Here are 3 key takeaways from the article:
- With IT at the core of digital transformation across industries, AIOps helps organizations operate with high efficiency and deliver an enhanced user experience. AIOps models can quickly identify the root causes of IT incidents and provide high-quality analytical information that enables technology teams to resolve complex problems.
- AIOps can help realize increased efficiency across a wide range of processes in IT operations by automating most mundane and repetitive tasks. A good AIOps architecture also helps improve problem detection and remedying 4X faster than conventional tools. The combination of the two frees up IT teams who can then contribute more of their time to innovation, resulting in cost savings of 15%-35%.
- More and more enterprises are keen to take advantage of AIOps and are carefully planning their implementation strategies. Drawing from the advantages that AIOps offers, where it can help automate root cause analysis, incident management and problem resolution processes, businesses are using AIOps for a variety of tasks, including performance monitoring, system availability monitoring, event correlation and analysis, and identifying potential outages.
Read the complete article here: Why now is the right time to adopt AIOps for business
