Operations | Monitoring | ITSM | DevOps | Cloud

You can use an observability platform that automatically discovers your services and provides ready-to-use dashboards with minimal setup. If you're running a system where microservices come and go, containers shift around, or serverless functions scale up quickly, this kind of experience saves you a lot of time. You gain visibility as soon as something goes live, without requiring any additional steps on your part. In this blog, we talk about the top seven platforms that offer these capabilities.

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.

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.

Non-deterministic UIs are the future and will replace your dashboards, but they’re not here yet. So until then, we’re stuck with conversational interfaces. In an effort to try and describe what I consider the future of UIs to look like, I wrote about how you (and I) have been designing dashboards wrong. The core insight was that we've been designing for static representations of data that sit on a TV in the office, when the actual use case is someone at a desk using them to debug an issue.

Node.js applications power millions of APIs, microservices, and real-time systems. But without proper monitoring, performance issues, memory leaks, and errors can go undetected until they impact users. This guide explains how to monitor Node.js applications in production, what metrics to track, and which tools deliver the best results.