zabbix

Let's get back to the roots of this blog for a moment -- to monitor what's happening in our home.

To fully understand what's happening in this blog post, I'll explain the morning routine of our 3+ year girl. 

Over the past few weeks, when she wakes up some time after 06:00 before us, she comes out from her room and turns on our living room ceiling light from the wall switch. That light of course is an IoT light bulb, a Philips Hue, so I get to graph that nicely with Zabbix.

This blog post again belongs to topic I spoke about back in Zabbix Summit 2025 -- how do I monitor my nearby environment with Zabbix and how it can help planning my day.

You probably know how annoying it would be to go to train station, only to find out that your train has been cancelled, badly delayed or that you just missed the train for some reason. Zabbix to the rescue!

Let's monitor if

• my train is on time
• if it is not, how badly it is delayed
• or worse, if the train is cancelled

And more.  But how do we even start?

First of all, huge congratulations for my wife -- she started her own little business this month! That takes some real guts! Her business, SensoSoppi, is not about IT at all but about one's wellbeing. 

But, moving on to our topic. After this blog post I will be able to say that I am also monitoring my wife, or at least her business. Of course, her website is already being monitored by my Zabbix.

This will start my blog series which I spoke about at the Zabbix Summit 2025 -- how and why I monitor my surroundings with Zabbix. The reason is partly conceptual, partly real, to showcase how Zabbix can potentially help you to make figuring out what's going on near you much easier. Let's dive in!

Where to get the price data?

In Finland, we have this community-driven fuel station price tracking site, polttoaine.net. It has been around since forever, but for my kind of Zabbix use purposes, has several downsides: 

Zabbix Summit 2025 is almost here and this is just a quick note about what I am going to do.

Back in part 107 of this blog I went bananas and made a local LLava AI model to recognize what is in the image. But how reliably Llava('s smallest model) does actually recognize what is in the picture? Let's test it with Zabbix!

Methodology

For this test, I am 

I might sound like a monZphere fanboy, but that's because I am a monZphere fanboy. Another super cool module of their is their freshly published Zabbix Problem Analysis module, which is open-source and freely available for us all on Github.

The module adds a new Details button after an each alert on Problems view, giving you an easy way to get insights about that particular alert.

As I will be a speaker at the Zabbix Summit 2025, I've been busy building stuff for it; also had a summer holiday in July. Sorry for the long silence! Anyway, let's move on to today's topic.

MonZphere is cooking something really cool. 

When leaving your home, the traditional background chatterbox in your head can be thinking things like "Did I lock the front door?", "Did I turn off the oven?" and so forth. 

With an IoT hub like Cozify, there's another one. For example, if my parents -- who are not very technological -- will come to our house to entertain and look after the puppy whilst we are somewhere away with my wife and our toddler, without Zabbix my head would think "Did I remember to switch Cozify to such mode that it won't change the Home scene status to Away scene?". 

I stumbled upon something called Nanobrowser. It's a Chrome extension which turns your browser into open source AI web agent. 

What's an AI web agent? It makes your web browsing more exciting, with all the gotchas of LLMs combined with the speed and reliability that resembles a drunk grandpa attempting to use a computer without his glasses. No, jokes aside, it is kind of impressive. You just tell it what you want and it attempts to use your browser instead of you. Check this out: