Operations | Monitoring | ITSM | DevOps | Cloud

We often hear the term "load" used to describe the state of a server or a device. But what does it really mean? System load is a measure of the amount of computational work that a system performs. An overloaded system, by definition, isn't able to complete all its tasks per schedule - this affects the performance and productivity of the system. And while "load" often gets conflated with CPU usage there's a lot more to it.

When Netdata's metric collection meets Grafana's visualization capabilities, you get powerful and dazzling dashboards to strengthen your monitoring infrastructure. Hugo Valente, Senior Product Manager, walks through the new plug-in to be sure that you're making the most of this unbeatable combination.

Netdata for Redis monitoring just got a nice upgrade! Metrics were reorganized for an easier monitoring experience, and it now displays ~40 dimensions across 25 different charts. 🚀 �� Make sure to share your feedback and enjoy! Happy monitoring!

This demonstration sees Andy Maguire performing manual development on a Python collector, extending its functionality by defining alerts to exclude, and then opening a PR for the change.

Netdata for PostgreSQL monitoring just got a huge upgrade, collecting 100+ PostgreSQL metrics and displaying these across 60+ different composite charts. You can check the reference documentation for the full list of metrics, and see them running live in the demo space. If you are using PostgreSQL in production, it is crucial that you monitor it for potential issues. And the more comprehensive the monitoring the better!

In this video we will walk though the Netdata Anomaly Advisor deepdive python notebook. The aim of this notebook is to explain, in detail, how the unsupervised anomaly detection in the Netdata agent actually works under the hood. No buzzwords, no magic, no mystery :) Try it for yourself, get started by signing in to Netdata and connecting a node. Once initial models have been trained (usually after the agent has about one hour of data, zero configuration needed), you'll be able to start exploring in the Anomaly Advisor tab of Netdata.

The latest Netdata Agent release v1.36 introduces anomaly rates on every chart, a centralized admin interface, metric correlation improvements, and a new tiering mechanism that allows almost unlimited metrics for your nodes. Want to know more? Hit "Subscribe" and post a comment or ask your question below.

Anomaly rate information is now available embedded in every Netdata chart! Now you are always just a click away from finding out if the metric you are interested in is exhibiting anomalous behavior or not. In this video we walk through some real world usage of the new anomaly rate embedded chart.

The latest Netdata Agent release v1.35 introduces massive improvements for the machine learning-powered Anomaly Advisor, Metric Correlations, Kubernetes monitoring, and much more. Anomaly Advisor & on-device Machine Learning This release features a launch of the flagship machine learning (ML) assisted troubleshooting Anomaly Advisor. Unsupervised ML models are trained for every metric, at the edge, on your devices, enabling real-time anomaly detection across all your systems and applications.

OK, it took our video guy exactly 42 seconds, but we're allowing for some leeway here. Basically, if you want to monitor a Linux node, whether physical, virtual, container, or IoT, all you need to do is.