No-Code Internet QoS (Quality of Service) Monitoring

Monitoring the Internet Bandwidth Quality of Service is essential to gain confidence in the service provider. 

There are several solutions available for enterprise-scale bandwidth monitoring.  This article is focused on a solution for home users. It is quick and straightforward. No coding is required. 

In 2018, I worked on a pet project that involved setting up a monitoring system for my internet bandwidth. I used a Raspberry Pi and installed all the necessary software. However, one of my biggest challenges was accessing the dashboard outside my home network. It was complex, and I had to rely on local/on-prem environments. After thinking, I realized that leveraging cloud services could help me overcome this bottleneck. I'm excited to explore this idea further and see how it can improve my project.

• Needs the ability to access the monitoring dashboard from anywhere, so it should be hosted on a cloud service. 
• Needs the ability to run an agent on the network to monitor 24x7, so a lightweight computer like Rasberry Pi will work. 

Software components 

• Docker standalone/local/on-prem runtime: To run the Telegraf agent container that collects the stats like download, upload, etc., and pushes them to a time-series database. 
• InfluxDB Cloud instance: Cloud-based time series database to collect and store the internet speed stats 
• Grafana Cloud instance: Cloud-based visualization instance to plot beautiful graphs of the internet speed. 

Hardware components 

• Raspberry Pi is connected to the home network and set up to run forever. Don't worry; its power consumption is very minimal. 

Setup

• Login to the Influx DB Cloud portal with your Google account https://cloud2.influxdata.com/signup 
• Setup "Company" and "Organization" You can give any name 
• Create a "Bucket" - Imagin this to be a store 
• We would use the Telegraf agent, so move to the Telegraf tab and create a configuration.
• Select the bucket you created earlier, and from the filter type "Internet Speed" select the tile. 
• The above steps are going to create a Telegraf config file and provide instructions that are important to note down. 
• INFLUX_TOKEN is required for the Telegraf agent to successfully write data into the cloud Influx DB 
• The start command of Telegraf provides the reference path for the config file. 
• Download Telegraf agent https://portal.influxdata.com/downloads/. There are several types, but we would be using the docker image. 
• On the Raspberry Pi, install Docker and open a terminal. 
• run the commands provided in the above link 

# Debian-based image

docker pull telegraf

•  Start the container 

• docker run -e INFLUX_TOKEN=<Token> -p 8086:8086 -d -it --name telegraf telegraf --config https://<URL>

• The above command is going to start the container with the config file location provided as https URL and start pushing the internet speed stats to the influx bucket 

• Verify data in the Influx bucket 
• Navigate to the influx Buckets tab and click on the bucket you created 
• Select the measurement drop-down and select the internet_speed that you already created 
• Select the fields and write a simple query to inspect the data that is collected
• This data is pushed from the Raspberry Pi on your home network 
• Configure Grafana visualization 
• Log into the Grafana Cloud portal https://grafana.com/auth/sign-in and launch the Grafana Cloud instance. 
• We need to pull the data from Influx Cloud Bucket and plot the visualization to create the Influx data source. 
• In the URL, use the influx cloud server URL, select Basic Authentication, and provide your login credentials. 
• Provide the influx organization you created earlier and select the bucket you created earlier. 
• This setup needs an Influx token to access the data from Grafana. So open the Influx Cloud instance and configure an API token with full access. 
• Copy the token and use that in the Grafana Data Source config 
• Now test the connection, and you should see that all is good
• Configre Grafana Dashboard 
• Click Grafana >> Dashboard and New 
• Select a pane and open the configuration 
• Make sure the Time series is selected on the top-right 
• Select the Data Source that you just created 
• Now the challenge here is to write a Flux Language Query. It took some learning for me so I am providing a basic query that you can use and modify (refer: https://docs.influxdata.com/influxdb/v2.7/query-data/get-started/query-influxdb/) 
• from(bucket: "Internet_mon")

  |> range(start: -30d)

  |> drop(columns: ["tag", "host", "server_id", "source"])

  |> filter(fn: (r) => r._measurement == "internet_speed" )

  |> filter(fn: (r) => r._field == "download")

  |> yield(name: "DownloadSpeed")
• The visualization starts showing the data 

That's it. You can now start playing around to create more widgets like the following. Observe your Internet Bandwidth Quality of Service in real time to understand current and past behaviors. 

Share the link and monitor your home network from anywhere. Note that the cloud instances used are on free plans. 

Enjoy!!

More interesting ideas 

• Set alerts using the "Threshold" concept in Grafana - Whenever the internet download speed drops or disconnects, you would like to get an email/tweet. 
• If the downtime continues for more than a threshold amount of time, say, 10 minutes or more, you should send an email to your service provided with detailed logs. 

Understanding application Observability and the difference with Application Process Monitoring is very important for a software/systems developer. Check this out https://youtu.be/dXohgVATzDc 

Please comment with your inputs/concerns/more ideas and how you could solve some complex problems with observability.