We completely reworked our custom-made, time series database (dbengine), resulting in stunning improvements to performance, scalability, and stability, while at the same time significantly reducing the agent memory requirements. On production-grade hardware (e.g. 48 threads, 32GB ram) Netdata Agent Parents can easily collect 2 million points/second while servicing data queries for 10 million points / second, and running ML training and Health querying 1 million points / second each!

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.

Understand what makes a storage device S.M.A.R.T and how to monitor a self monitoring component using Netdata.

Find out how to effectively and easily monitor and troubleshoot BIND 9 using Netdata.

Find out how to effectively and easily monitor and troubleshoot Memcached using Netdata.

Find out how to effectively and easily monitor and troubleshoot NTPdaemon using Netdata.

Find out how to effectively and easily monitor and troubleshoot MongoDB using Netdata.

As a continuation of our series for monitoring web servers with NGINX and APACHE, let us find out how to effectively and easily monitor and troubleshoot NGINXPlus using Netdata!

Find out how to effectively and easily monitor and troubleshoot Dovecot using Netdata.

Find out how to effectively and easily monitor and troubleshoot CoreDNS using Netdata.