Operations | Monitoring | ITSM | DevOps | Cloud

The volume and ambiguity of log files makes them impossible for humans to process. The promise of logs is revealed when AIOps is applied to analyze their deep structure.

The hype has gone off the charts for AI and machine learning tools' potential in IT organizations. It’s time to temper expectations and move towards a sensible adoption path. Artificial intelligence is not fairy dust sprinkled on a data center, despite the enthusiastic proclamations of many IT operations vendors today. A couple of years ago, AI was the bride atop the wedding cake. It was perfect, with promises to render obsolete errors and out-of-control performance issues.

My 2nd Gartner IOCS experience ended with a bang, just like my first one, with an amazing presentation by Jason Walker at Blizzard Entertainment (part of the $42B Activision-Blizzard gaming powerhouse) on how they use AIOps to deliver an amazing gaming experience for hundreds of millions of gamers around the world, 24×7. But before I get to that, let me share some more key takeaways from the conference.

Observability without AIOps is just noise.

Ticketing systems have remained largely unchanged for three decades. Teams supporting either legacy or DevOps applications both suffer high costs.