Zabbix Summit 2023 is just around the corner, and with that in mind we’ve decided to whet your appetite by providing a sneak peek at just a few of the distinguished speakers who have graciously agreed to present at this year’s Summit in the form of a short and direct interview. Read on to hear […]

Zabbix Summit 2023 will take place on October 5–7 in Riga, Latvia. And while Summit veterans will feel right at home at our venue – the Radisson Blu Hotel Latvija – everything else this year promises to be a new and unique experience. Let’s take a look at what Summit attendees can expect to see, […]

In the third article about Zabbix and exploratory data analysis, we will understand how theories about asymmetry and kurtosis work.

As my home monitoring experiment has become such a celebrity and as it has so much going on, I’m trying to make sure I won’t ever lose its configuration and data, no matter what would happen. Here are some tips and reminders for you, too.

In the previous blog post, we just explored some of the basic statistic concepts to estimate KPIs for a web application response time: in that case, average, median and percentile. Now we must continue our work but this time, analyzing some variances of the collected metrics, considering a certain period.

Can you verify if your phone battery drains faster during summer compared to other seasons with Zabbix? Of course, you can!