If you do not know what Pi-hole is I definitely recommend you look into it. Especially if you want to block ads/telemetry on all your home network devices.

Now there are probably a few ways to do this but for my dashboard I ended up using a script to send pi-hole stats to InfluxDB. I currently have Pi-Hole running on a VM under Ubuntu Server 17.10.

This script can be run remotely but you will need to use the authentication method described in the repo.

First we need to install python-pip. So SSH to your Pi-Hole server and run:

sudo apt-get install python-pip -y

Now create a new directory for the script to live in.

mkdir /opt/pihole-influx

Clone the pi-hole-influx repo.

git clone https://github.com/janw/pi-hole-influx.git /opt/pihole-influx

Once that finishes, cd to /pihole-influx and run:

pip install -r requirements.txt

Now clone the config.example.ini to config.ini.

cp config.example.ini config.ini

Edit the config.ini file to match your environment.

nano config.ini
api_locationaddress of the /admin/api.php of your pi-hole instance

You can scrape multiple pi-hole instances if you run more than 1 by adding a second config block called [pihole_2], etc. I’d recommend using a docker container if you plan to use more then one pi-hole instance.

Save and close the config.ini file.

Lastly, you need to create the InfluxDB database that your pi-hole stats will reside in. Will need to match what you put in the database = databasename section in your config.ini.

curl -XPOST "http://<ip.of.influx.db>:8086/query?u=<admin user>&p=<password>" --data-urlencode "q=CREATE DATABASE "pihole""

curl -i -XPOST "http://<ip.of.influx.db>:8086/query?u=<admin user>&p=<password>" --data-urlencode "q=CREATE USER "pihole" WITH PASSWORD "pihole""

curl -XPOST "http://<ip.of.influx.db>:8086/query?u=<admin user>&p=<password>" --data-urlencode "q=GRANT WRITE ON "pihole" TO "pihole""

curl -XPOST "http://<ip.of.influx.db>:8086/query?u=<admin user>&p=<password>" --data-urlencode "q=GRANT READ ON "pihole" TO "grafana""

Now launch piholeinflux.py.


Running piholeinflux.py as a service.

You can setup piholeinflux.py to run as a systemd service so that it will auto launch at boot time if you ever have to reboot your server.

Create the piholeinflux.service file.

nano piholeinflux.service

Paste the below info into your new .service file.

ExecStart=/usr/bin/python /home/USERNAME/pihole-influx/piholeinflux.py

Save and close the .service file. Then run the following in order:

sudo ln -s /opt/pihole-influx/piholeinflux.service /etc/systemd/system
sudo systemctl enable piholeinflux.service
sudo systemctl daemon-reload
sudo systemctl start piholeinflux.service

If you get an error while running make sure you can A: communicate to InfluxDB and B: the “USER=” in the .service file is set to a user that can run it (i.e. root or you).

Setting up the Grafana Dashboard

Pi-Hole Data Source

  1. Select the cog on the left hand side and click “data sources”
  2. Click “add data source”
  3. Click InfluxDB
  4. Enter the following information and hit “Save & Test”

If you get an error, double check your connection info for typos!


Dashboard Setup

Now you can import a basic dashboard using the ID from the script’s repo. This will give you some basic info from your Pi-hole data source.

Dashboard ID: 6603

HOWEVER, there are a few issues with it. First you will want to edit the Realtime Queries and add: non_negative_derivative or add math(* -1) to each of the queries, under “Metrics”, so the Y-Axis has no negative values.

Docker Container Version

You can deploy this script using the below Dockerfile and config.ini

FROM alpine as builder
RUN apk add --no-cache git
RUN git clone https://github.com/janw/pi-hole-influx.git

FROM python:3-alpine
WORKDIR /usr/src/app

COPY --from=builder /app/pi-hole-influx/requirements.txt /usr/src/app
RUN pip install --no-cache-dir -r requirements.txt
COPY --from=builder /app/pi-hole-influx/piholeinflux.py /usr/src/app
COPY config.ini .

CMD [ "python", "./piholeinflux.py" ]

port = 8086
hostname =
username = pihole
password = allthosesweetstatistics
database = pihole

# Time between reports to InfluxDB (in seconds)
reporting_interval = 10

api_location =
instance_name = pihole
timeout = 10

Copy both of the above blocks into the same folder.

docker build -t your-name/of-image .

Thanks to my co-worker for throwing together this easy, lightweight Docker container version. Also since it doesn’t require a mounting volume, it should work in swarm mode!

Edit 4/29/19: Updated to match new Grafana guide settings.