The latest News and Information on Incident Management, On-Call, Incident Response and related technologies.
Companies that underwent accelerated digital transformations during the past 18 months are looking to understand how they can improve their operational maturity to handle the increase in complexity. This is paramount to an organizations’ future success.
Technology companies are at the forefront of innovation, changing the way consumers and the general public interact with their everyday lives. As the late Stan Lee so wisely stated, “with great power comes great responsibility,” and this heightened pressure often leaves little room for error when an issue arises—which happens more often than you’d think.
This is the final blog in our series focusing on CloudOps maturity, where we’ve been looking at the key findings from a recent IDC study, commissioned by PagerDuty. In our previous blogs, we discussed the people-based transformations and the technological changes that organizations must undergo to mature their CloudOps practices.
The link between DevOps and artificial intelligence for operations (AIOps) has only started to become clear within the last few years. Monitoring and alerting has evolved from a "black box approach," where you don't actually know what's happening, into observability, where you have access to data that provides everything you possibly need to know about your IT systems. How does AIOps come into play? AIOps is the practice of applying artificial intelligence, machine learning, and advanced analytics to automate and improve IT operations. Since it entered as a formal discipline with Gartner in 2016, IT teams have been trying to figure out how to employ it to make their lives easier.