Operations | Monitoring | ITSM | DevOps | Cloud

How to configure Netdata's all-new Anomaly Advisor, powered by ML, for real-time troubleshooting

Netdata's Lead Machine Learning Engineer, Andrew Maguire, walks through how to configure the all-new Anomaly Advisor. This new feature lets you troubleshoot in real-time, at scale, by identifying periods of time with raised anomaly rates across your entire infrastructure. In this guided video, Andrew will explain how to enable Netdata's ML functionality then, how to set up unsupervised anomaly detection with minimal configuration, and lastly how the Anomaly Advisor works to speed up troubleshooting when an incident occurs.

Introducing Anomaly Advisor for troubleshooting at scale

Troubleshoot at scale with our all-new, lightweight Anomaly Advisor, powered by machine learning. The Anomaly Advisor finds periods of time with elevated anomaly rates across your entire infrastructure faster than ever before. This new feature works along with our ML unsupervised models on the edge, making your troubleshooting trouble-free! Even better, the Anomaly Advisor requires minimal configuration and is extremely lightweight. No need to worry about exhausting your CPU usage.

Introducing Anomaly Advisor - Unsupervised Anomaly Detection in Netdata

Today we are excited to launch one of our flagship ML assisted troubleshooting features in Netdata – the Anomaly Advisor. The Anomaly Advisor builds on earlier work to introduce unsupervised anomaly detection capabilities into the Netdata Agent from v1.32.0 onwards.

Kubernetes throttling? It doesn't have to suck!

Kubernetes has a bad habit of throttling CPU resources—with the result that you can suffer severely degraded performance or find yourself paying a fortune for extra, unnecessary infrastructure. Watch this video to learn how K8s clusters protect themselves from what they see as heavy CPU usage, and how you can monitor and troubleshoot the problem. We demonstrate how you can:– Use Netdata to reduce API response times by a factor of 7– Expect to reduce infrastructure resource requirements by 60-75%

Kubernetes Throttling Doesn't Have To Suck. Let Us Help!

In the Kubernetes (K8s) community, there is a huge misconception about CPU allocation and utilization. Even highly experienced SREs find themselves struggling with the way Kubernetes allocates CPU resources, leading to misconfigured CPU allocations and extremely negative outcomes. For starters, this results in significant quality degradation on important service components, introduced by behind-the-scenes CPU limiting (or throttling).

Troubleshooting Alerts the Right Way: As a Team

At Netdata, we love two things more than anything else: Our goal is to make troubleshooting and monitoring as seamless as possible with the open-source Agent. This includes giving you pre-configured alerts so that you get notified immediately when a disruption occurs. The Netdata Agent comes with over 250 pre-configured and optimized alerts.