You've heard of AIOps. You've heard of APM. And at times, you may have wondered what AIOps and APM have to do with each other — how they're similar, how they're different, and whether AIOps is actually just an advanced form of APM.
If these are questions you've found yourself asking as AIOps has grown in popularity, keep reading. This blog explains what AIOps and APM have to do with each other, and why you should think of AIOps as being about more than just APM.
What Is AIOps?
AIOps is a term coined by Gartner that stands (in its current usage, at least) for Artificial Intelligence Operations.
The driving idea behind AIOps is that it empowers IT operations teams to use data and machine learning to inform and automate the work they do.
If you've ever worked in IT Ops, you probably understand why this is useful. IT Ops tasks like troubleshooting an application performance problem or investigating a server crash typically involve a lot of guesswork and manual digging.
With the help of AIOps, IT Ops can significantly reduce the amount of guessing and sleuthing required to reach solutions.
What Is APM?
APM, which is short for Application Performance Management (or Application Performance Monitoring, depending on whom you ask), is also something with which you are likely familiar if you have ever worked in IT Ops.
APM is a category that includes the tools and processes required to ensure that applications perform as expected. It entails monitoring hardware infrastructure as well as software, and responding when performance problems are detected — ideally, in a manner timely enough to prevent disruption to end-users.
Increasingly, APM also encompasses tasks related to efficiency and optimization. You might use APM tools to help determine where you are overspending on cloud infrastructure, for example, or which of your databases are under-provisioned.
AIOps and APM
AIOps and APM, then, are similar in that they are both important areas of concern for IT Ops teams. AIOps and APM tools help to automate the work done by IT Ops to identify problems and respond to them before they become critical.
This does not mean, however, that AIOps and APM are the same thing. There are key differences:
AIOps is newer
AIOps is a new and emerging field. APM, in contrast, has been well-established for years. At this point, you won't find many AIOps tools on the market, but you can find plenty of APM resources.
AIOps is broader
AIOps can help with APM in key ways by using machine learning to help interpret all of the data that APM tools collect. AIOps can also automate responses to application performance events so that action occurs immediately, without a need to wait on humans to intervene.
However, AIOps can provide insights for more than just APM. AIOps can also assist with security operations and monitoring, for example, or with infrastructure provisioning and application deployment. These tasks are related to APM, but they are distinct from it.
AIOps is about more than monitoring
APM tools mostly help IT Ops teams to detect problems. They might provide recommendations about how to fix them, but resolution typically requires a manual response by engineers, who have to make decisions based on the data presented to them.
AIOps can take this process a step further. By using data to determine the cause of an issue and the best solution, then implement it automatically, AIOps significantly reduces the risk of human delay or error. It helps provide a better end-user experience, while also saving time for engineers.
To learn more about AIOps, download The Definitive Guide to AIOps.