AIOps brings artificial intelligence, machine learning, and data science to go from reactive to predictive IT Operations. AIOps automate processes with significantly reduced human intervention and manual efforts. As per recent research by TechValidate found that 97% of surveyed IT organizations agreed that AIOps-enabled solutions that deliver actionable insights will help automate and enhance overall IT Operations functions.
Key Drivers for AIOps
Proactively managing and improving the experience of modern applications, cloud or traditional infrastructures and networks is a must requirement for enterprises to achieve competitive edge. And, it’s not easy with traditional ITOps tools and technologies. IT teams work under tremendous pressure to meet SLAs while managing increasingly dynamic, hybrid, and distributed nature of their computing environments. Additionally, the shift in recent years toward microservices and containers similarly increased the number of components that go into a single application, as well as the challenge of orchestrating all of them.
Today, 80% of the enterprises use automation tools to handle added complexity. However, these traditional automation tools require humans to configure, deploy and manage them. With the adoption of advanced AIOps tools and platforms such as Splunk, Moogsoft, Broadcom and few others offers a better solution to the meet ever increasing complexity in ITSM.