5 posts tagged with "netdata-monitoring"

Businesses are increasingly reliant on monitoring tools to ensure the seamless performance and reliability of their systems. However, the true cost of implementing and maintaining these tools is often obscured by hidden expenses. Our previous blog delved into the concealed costs associated with various monitoring solutions, such as Prometheus & Grafana (Open Source Monitoring) and commercial platforms like Datadog, Dynatrace, and NewRelic. These costs can manifest in various forms - from complex setups and maintenance to additional charges for advanced features.

Unlike its counterparts, Netdata is engineered with transparency and efficiency at its core, ensuring that organizations can monitor their systems effectively without incurring unexpected expenses. This blog will explore how Netdata stands out in the crowded field of monitoring tools by eliminating hidden costs, providing a detailed analysis of its unique features and advantages.

Let us explore how Netdata’s user-friendly approach, unlimited metrics collection, decentralized architecture, and comprehensive capabilities make it a holistic solution for cost-effective monitoring.

When it comes to monitoring IT infrastructure, the costs you see on the price tag of the tool are often just the tip of the iceberg. Below the waterline, a mass of hidden costs can lurk, which can significantly affect the total cost of ownership.

What are they and why do we need them?​

A “Parent” is a Netdata Agent, like the ones we install on all our systems, but is configured as a central node that receives, stores and processes metrics data from other Netdata “Child” nodes in our infrastructure.

Netdata Parents are flexible. You can have one big active-active cluster of Netdata Parents, or you can spread a lot of independent Parents across the infrastructure.

This “distributed still centralized” setup provides a lot of benefits. Let’s go through them one by one in this blog post.

We have been busy at work under the hood of the Netdata agent to introduce new capabilities that let you extend the "training window" used by Netdata's native anomaly detection capabilities.

This blog post will discuss one of these improvements to help you reduce "false positives" by essentially extending the training window by using the new (beautifully named) number of models per dimension configuration parameter.

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.