Operations | Monitoring | ITSM | DevOps | Cloud

Monitoring AI systems isn’t business as usual. Monitoring AI isn’t like monitoring traditional systems. You can’t just track uptime or response times and call it a day. AI models evolve, data shifts, and behavior drifts over time, which means your monitoring has to evolve, too. If you’re running AI workloads in production, you already know this. Your models might look healthy according to your infrastructure metrics, but they’re still making bad predictions.

AI workloads break every assumption you have about infrastructure management. AI is everywhere. Machine learning-based tools are answering customer service questions, accelerating incident resolution, catching fraudulent transactions, spotting defects on production lines, and powering late-night searches that delve into the random topic that pops into your head right before bedtime. Behind every prediction, response, or generated sentence is massive computing power doing serious, continuous work.

AI observability closes the gap between “something’s wrong” and “here’s what to fix.” If you run AI in production, you might have felt the whiplash. Yesterday, your LLM answered in 300 milliseconds (ms). Today p99 crawls, costs spike, and nobody’s sure if the culprit is model behavior, data freshness, or GPUs stuck at the ceiling. Dashboards light up, but they don’t tell you which issue puts customers at risk. That’s the gap AI observability closes.

Today, many DevOps and security teams operate in a world of complex, hybrid, or multi-vendor environments. As more teams look to avoid lock-in by adopting open standards, OpenTelemetry (OTel) is quickly gaining adoption as the primary open source method for DevOps and security teams to instrument and aggregate their telemetry data. However, OTel alone may lack the advanced processing functions, native volume control rules, and hybrid environment support that large organizations need.

With the first stable releases out of the gate, we’re happy to announce that Sentry’s Godot SDK is now ready for general use, supporting Windows, Linux, macOS, iOS and Android. We started full-time development a year ago with just a few prototypes, and now it's finally here - built on top of the mature Sentry platform SDKs, it comes as a GDExtension add-on that you can easily add to your Godot projects.

We just launched our Cursor Cloud Agent integration. Now when Seer finds a bug, it can hand it off to Cursor—replete with all the context Sentry has about the issue—to write the fix and create a PR for you.

On November 18th, 2025, a large Cloudflare outage briefly broke big chunks of the internet. For several hours, users around the world were greeted with 500 errors, including platforms like X, ChatGPT, Spotify, and many others that run behind Cloudflare’s network. At UptimeRobot, we sit in a slightly unusual spot during events like this: So when Cloudflare has a bad day, we see it twice: once in the alerts we send to our customers, and again in how it affects parts of our own infrastructure.

InfluxDB 3.7 is now available for both Core and Enterprise, landing alongside version 1.5 of the InfluxDB 3 Explorer UI. This release focuses on giving developers faster visibility into what their system is doing with one-click monitoring, a streamlined installation pathway, and broader updates that simplify day-to-day operations. InfluxDB 3 Core is free and open source, optimized for recent data, and licensed under MIT and Apache 2.

You can cut your log costs by removing repetitive, low-value logs early and keeping only the parts that genuinely help you understand issues. Modern systems generate logs far faster than you expect. Even when your workload stays stable, infrastructure components, retries, and background workers continue producing a steady stream of repeated entries.

Have you ever stood before a critical piece of network infrastructure, knowing it desperately needs an upgrade, yet felt a wave of paralysis wash over you? You’re not alone. It’s a common feeling when facing a project as significant as a data center migration or a move to a modern leaf-spine architecture.