DevOps and AIOps are both popular operational terms of the last 10 years, as organizations try to adjust to rapidly changing roles of computers and the humans that run them. While AIOps and DevOps sound similar and are two popular tech buzzwords, they serve distinct purposes within the tech organizational ecosystem. Both are designed to optimize for the ultimate goal: providing the best user experience in the most efficient and effective way possible.
First, let’s start by looking at the difference between DevOps and AIOps. AIOps is a class of tools designed to help get better analysis out of monitoring tools. Observability tools are great for displaying data and slicing and dicing, but which data points matter? Which do you need to take action on? That’s where AIOps comes in. AIOps makes sense out of the data input, and tells you what you need to pay attention to. This facilitates quicker analysis and actionable insights for teams to execute ops.
Unlike AIOps, DevOps is not a class of tools. Rather, DevOps is an organizational concept that has become popular as the roles of developers and operations managers have evolved. DevOps extends the responsibility of the developer beyond just shipping the product. Since the developer wrote the code, they are the best equipped to fix encountered issues even after the product has gone to market. This, of course, shifts additional responsibilities onto the developer, and thus the entire developer organization.
So while these two terms are different, they work well together to deliver the best end product and user experience. AIOps enables developers to understand and detect problems because it automatically surfaces key issues. While traditional ITOps managers spend a significant amount of time combing through disparate information, AIOps automatically analyzes the data and detects anomalous patterns. This gives DevOps engineers time to focus on what they do best – creating and building. Read more about using AIOps to optimize for DevOps here.