As engineers, we are constantly bombarded with complex machine data. In order to better monitor and troubleshoot our environments, we must analyze and gain an accurate understanding of this data to best evaluate how our systems are performing and combat any issues that may occur. Yet, sifting through this data while managing the added intricacies of serverless architecture, microservices, containers, and other technologies make our jobs increasingly difficult to navigate.

Access Gartner’s exclusive research report to find out how AIOps—when used together with APM—plays a pivotal role in driving better business outcomes.

In a previous post, I talked about the potential of AIOps and why true AI (Artificial Intelligence) hasn’t had much impact in the monitoring space yet. However, I believe Algorithmic IT Operations can help and will share the path LogicMonitor is taking to get there in this post.

AIOps is the application of analytics and machine learning to automate some aspects of DevOps and IT operations management. Like all new technologies, it may take time to discover the best ways to get practical results. However, AIOps is already showing a lot of promise in three key uses cases.