Operations | Monitoring | ITSM | DevOps | Cloud

Modern data centers generate enormous volumes of telemetry from servers, switches, cooling systems, power infrastructure, and environmental sensors. Operations engineers must capture, store, and analyze this data in real-time to monitor uptime, maintain energy efficiency, and perform predictive maintenance using AI. Legacy monitoring systems struggle to meet today’s volume, cardinality, and latency demands.

It’s 2 AM. Your phone buzzes. A critical server’s CPU is maxing out again. But this time, the issue isn’t just high usage. It’s heat. As a network admin, you’re trained to monitor traffic patterns, patch vulnerabilities, and respond to performance slowdowns. But high CPU temperature? That’s the silent system killer many still underestimate. Without a proactive plan, it can knock out performance, rack up hardware costs, and shorten the lifespan of your infrastructure.

You write code. Open a PR. CI runs. PR merges. Prod’s on fire by 5pm. Maybe you skipped writing some tests. (It's tedious, sometimes unclear, and easy to ignore when you're racing to ship—until something breaks and you realize a test could’ve saved your Friday night.) Maybe the PR review was more of a drive-by from a teammate who barely had time to skim the diff. But reviews and tests matter.

Kentik CEO and co-founder Avi Freedman explains why observability is not enough in the age of AI.