If I were to tell you that you could run autonomous IT operations that self-optimize and remediate, you will probably tell me “I have heard that before.” Well now it’s actually possible and your peers have begun their journey to building IT infrastructures and operations that self-heal and improve themselves to support today’s digital businesses. Why? Well here are the three core reasons:
1. PRESSURE FROM TODAY’S DIGITAL BUSINESSES
First of all let’s talk about the need. Today’s digital businesses demand support for new technologies or delivery models and at same time they are unforgiving on the experience that IT Ops teams enable. With the ever-increasing volume, velocity and variety of data, alongside the presence of multiple point tools, it’s getting increasingly difficult for IT teams to ensure a reliable experience and run efficiently at the same time.
In order to better support the development and deployment of new innovative models or applications, IT teams need to free up time from mandated IT tasks. They need to augment themselves with AI driven IT operations management solutions (aka AIOps) and use them to drive auto-remediation and self-optimization. This is no longer a nice to have, but a must have to thrive in today’s highly competitive digital world.
2. MATURITY OF IT ORGANIZATIONS
Pretty much all IT organizations, especially in the enterprise, have monitoring and management tools in place. These tools might be a bit reactive in nature but they make sure that services don’t go down for days and domain users can perform their everyday task efficiently. In order to adopt an AI-driven approach, it’s essential that you have monitoring tools for all aspects including application, networks, infrastructure and user experience in place, in addition to other IT operations management tools like ticketing, CMDB and automation.
AIOps solutions will enable you to aggerate data from these sources and gain actionable, timely insights required to run self-driving operations. If you don’t have any of the tools covered above, you need to fill in those gaps first before you deploy AIOps.
3. MATURITY OF TECHNOLOGIES
Machine learning algorithms and big data technologies have started to become mainstream and more widely accessible. These are the basic ingredients to the development of AIOps tools that drive self-healing and self-optimization. Most of these technologies are tried and tested and designed to aggerate and process large volumes of data. Now vendors with domain expertise in IT operations management like CA Technologies are able to leverage these technologies and algorithms in order to build AIOps solutions that significantly expedite the journey of an enterprise to AI-driven autonomous operations.