Operations | Monitoring | ITSM | DevOps | Cloud

Custom dashboards in Netdata have always let you pull charts together on-the-fly into a single view. That’s useful, but it’s also limited. In practice, when you’re running an incident or reviewing a service, you don’t just want charts. You want to see the output of top alongside your CPU metrics. You want slow query logs next to your database latency charts.

If you’ve ever opened the alerts tab during a busy period, you know the problem. There are alerts you’ve already looked at, alerts someone on your team is handling, and alerts that fired on a known issue that’s being worked on. They all sit together in the same list alongside the new ones you haven’t seen yet.

Charts in Netdata have always been interactive. You can zoom, pan, select time ranges, and see per-second granularity across thousands of metrics. But when you spotted something interesting, the next steps usually meant leaving the chart: opening another tab to check a related metric, navigating to the correlation tool, or pulling up a different time range for comparison. The investigation workflow lived outside the chart, even though the chart was where the investigation started.

Netdata AI can already troubleshoot your alerts and generate Insights reports. What it couldn’t do, until now, was have a back-and-forth conversation. You could get a one-shot analysis, but you couldn’t ask follow-up questions, pull in additional context, or go from a quick question to a full investigation without starting over. We’ve added a conversational layer to Netdata AI.

When you’re managing a handful of nodes, the flat list in the nodes tab works fine. When you’re managing hundreds or thousands, it becomes a wall of hostnames. You end up applying the same filters repeatedly: all the production database servers, all the nodes in eu-west, all the Kubernetes workers in the staging cluster. The filters work, but they don’t persist, and there’s no way to share them with the rest of your team. Node groups solve this.

The Netdata Cloud MCP Server is now available — giving AI agents and assistants direct access to your Netdata through a single endpoint at app.netdata.cloud/api/v1/mcp.

Over the past few months, we’ve seen incredible adoption of our AI Investigations and Insights reports. Teams are using them to automate the deep, thoughtful analysis required for complex post-mortems, capacity planning, and performance optimization. These comprehensive reports are fantastic when you need a well-researched, shareable document. But what about the moments during an investigation?

Netdata has an incredibly powerful alerting engine. But this can sometimes be a double-edged sword: the flexibility to build incredibly specific, intelligent alerts is immense, but mastering its syntax can feel like learning a new language. We’ve heard this from so many of you. You tell us that configuring alerts is often the steepest part of the learning curve, a task that falls to the one “Netdata expert” on the team who has spent the time digging through the documentation.

Bullshit and nonsense. But let’s take it from the beginning. The industry’s story goes something like this: Then, in the same breath: You see the contradiction already, right? The same industry that tells you “collect less, simplify, trust the experts” is also the industry where: This isn’t an observability strategy. It’s observability by hindsight. Right. Good. Now we’re having fun.

When a critical alert fires at 2 AM, the last thing your on-call engineer should be doing is manual administrative work. Yet, for many teams, that’s exactly what happens. You see the alert in your monitoring tool, then you have to switch contexts, open a new browser tab, log into your ITSM platform, and manually create an incident—all while your systems are failing.