AIOps aims to streamline IT workflows, predict potential issues, automate incident response, and ultimately improve the performance and efficiency of enterprise IT environments.
[1] The term refers to the multi-layered complex technology platforms which enhance and automate IT operations by using machine learning and analytics to analyze the large amounts of data collected from various ITOps devices and tools, automatically identifying and responding to issues in real-time.
This new approach in modern, accelerated, and hyperscaled IT environments leverages advances in machine learning and big data to overcome previous limitations.
This automation reduces the burden on IT teams, allowing them to focus on strategic tasks rather than routine operational issues.
While both disciplines rely on AI and data-driven methods, AIOps primarily targets IT operations, whereas MLOps is concerned with the deployment, monitoring, and maintenance of ML models.