The Grafana server is running, also in Docker, on the same machine. If you want, I’ll make another post with my docker-compose.yaml file.

I did this, as is my wont these days, using Docker. I spun up the InfluxDB server, plus Telegraf and Chronograf, on one of the Raspberry Pi machines. And, to be honest, there wasn’t a lot to it. This is not going to be a tutorial on InfluxDB or Grafana. Grafana is a web server that can take data from various sources, including an InfluxDB server, and present it as various charts, graphs and widgets. And writing to the database couldn’t be easier, with no mucking about with SQL queries and whatnot. For one thing, if the data you supply does not include a field called ‘time’, InfluxDB will automatically append a timestamp field to each record. It’s specifically designed for storing regular data points and so is ideal for IoT and network monitoring applications. I thought it would be complicated.įor those not familiar with it, InfluxDB is a ‘time series’ database. Having procrastinated for ages, I finally decided I’d get to grips with InfluxDB and Grafana as a way of capturing and displaying this data in a more thorough and meaingful way. Nothing that could show me fluctuations over time. But while it certainly did work, all I got was a figure on the intranet web page for the most recent reading. This was intercepted and logged by a Python script running on a server, which wrote the data to text files in a place where the intranet server could see them. My previous method of logging the CPU temperatures of machines on the network involved a Bash script sending out a message via MQTT.

Linux get cpu temperature