AIOps (artificial intelligence in IT operations) in monitoring refers to the convergence of artificial intelligence, machine learning, and data analytics to make IT monitoring a responsive, intelligent, and agile business function. AIOps is not an alternative to DevOps but a great partner to it that provides intelligent insights when integrated with every stage of the cycle.

Waste is never a good thing. And rumblings of an economic downturn, alongside dire warnings of climate change, are making it increasingly necessary to address waste. As a society, we need to reduce consumption, data included. First, we all must acknowledge the high cost of data. Despite the prevailing opinion of the 2010s, data isn’t free. There’s a monetary and carbon cost to keeping data alive.

ITOps and DevOps are technology management practices that have been around long enough that anyone in IT should have a good grasp of what they mean. Here’s our experts’ take on ITOps vs. DevOps.

Episode 5, Mooving to… Practical Postmortems covers how to leverage postmortems to effectively learn from failure. Postmortems are a commonplace reference and are now considered a best practice in most modern engineering teams. However, there’s still a lot of confusion on what postmortems should be – and more importantly, what they should NOT be. Thom Duran, Senior Manager of Productivity from Panther walks us through all that and more in the latest Mooving To.. episode!

In this video, I explain what topology is and why it’s critical for the success of AIOps projects. Simply adding machine learning to event correlation has proven an ineffective approach for root causing IT issues in environments of any size or complexity. If you’re considering different approaches to AIOps, there are two questions you need to ask about topology. This brief video will arm you with those questions and will help make your AIOps project(s) successful.