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AIOps which is described as “artificial intelligence for IT operations.” AIOps is the practice of applying AI to automate and optimize IT processes. Leveraging both machine learning and advanced analytics techniques, AIOps proactively identifies, isolates and resolves IT issues.
The ultimate goal of AIOps is to build autonomous IT operations. The key difference between AIOps and conventional IT analytics tools is the automation component. AIOps platforms work by, first, ingesting, consolidating and analysing all IT data into one, centralized platform. This means aggregating both historical and real-time data from dozens of sources including helpdesk systems, multi-cloud environments,containerized applications, storage, databases, events and logs, APIs and SDKs, APM, monitoring, and data streams. The system then applies a series of advanced analytics to this data, ranging from statistical and probabilistic analysis to automated pattern discovery and prediction, unsupervised learning for anomaly detection and topological analysis to any combination of these techniques.
Every enterprise has different needs and accordingly implements AIOps solutions. The focus of AI solutions is to identify and act on real-time issues efficiently. Some core elements of AIOps can help an enterprise to implement AI solutions in IT operations.The four stages of AIOps involves Collect raw data, aggregate it for alerts, analyse the data, then execute an action plan. AIOps or IT Analytics is about finding patterns. With the help of machine learning, we can...