The latest News and Information on AIOps, alerting in complex systems and related technologies.
Based on our interactions with buyers evaluating vendors in the AIOps market, much of what we’re hearing chimes with this quote - “What will AI allow us to automate? We'll be able to automate everything that we can describe. The problem is: it's not clear what we can describe.” Stephen Wolfram, computer scientist and physicist.
Alert management is no longer a manageable task, given the growth in applications, cloud environments and point monitoring tools. Too much time is spent filtering and making sense of alert data and determining where to route incidents. All of these steps slow down critical issue identification and resolution. In this article, I want to discuss a more sensible, modern way to deal with IT alerts, through machine learning intelligence and automation.
Logging is an essential method to understanding what’s happening in your environment. Logs help developers and system administrators understand where and when things have gone wrong. Ideally, logs on their own would suffice as indicators of what’s happening. However, there’s far too many log messages being produced in today’s world and most don’t contain the information we actually need.