---
description: >-
  If you wish to deploy Grafana for alternative graphs, follow the steps below.
---

# Using Ultrafeeder with Grafana and Prometheus

[`Grafana`](https://grafana.com/) is an analytics platform that can provide alternative graphs for `readsb`.

In this guide we will be using [`Prometheus`](https://prometheus.io/) as the data repository.

Using Grafana and Prometheus in this configuration does not require a plan, account, or credentials for their respective cloud offerings.

## Hardware requirements

Prometheus will store a lot of data, and Grafana will do a lot of data queries. As a result, it would be better if you run these containers on a different system than your feeder Raspberry Pi. This will leave your Pi focused on data collection and processing, and unbothered by the CPU and Disk IO load that Prometheus/Grafana will cause.

You *can* do it on a single system. We're assuming below that you are not. If you do it on a single system, then you can combine the `docker-compose.yml` components in a single file

## Step 1: Make Prometheus data available for the Ultrafeeder

- Edit your Ultrafeeder's `docker-compose.yml` file and ensure that the following is set for the `ultrafeeder` service:

```yaml
    environment:
      - PROMETHEUS_ENABLE=true
    ports:
      - 9273-9274:9273-9274
```

Now recreate the ultrafeeder container (`docker-compose up -d ultrafeeder`) and it will generate Prometheus data.

## Step 2: create a container stack for `prometheus` and `grafana`

On the machine where you will run Prometheus and Grafana, create a docker-compose file in the `/opt/grafana` directory:

```bash
mkdir -p -m777 /opt/grafana && cd /opt/grafana
cat > docker-compose.yml
```

Now paste in the following text:

<details>
  <summary>&lt;&dash;&dash; Click the arrow to see the <code>docker-compose.yml</code> text</summary>

```yaml
version: '3.9'
services:
  grafana:
    image: grafana/grafana-oss:latest
    restart: unless-stopped
    container_name: grafana
    hostname: grafana
    tty: true
    # uncomment the following section and set the variables if you are exposing Grafana to the internet behind a rev web proxy:
    # environment:
    #   - GF_SERVER_ROOT_URL=https://mywebsite.com/grafana
    #   - GF_SERVER_SERVE_FROM_SUB_PATH=true
    ports:
      - 3000:3000
    volumes:
      - /opt/grafana/grafana/appdata:/var/lib/grafana

  prometheus:
    image: prom/prometheus
    container_name: prometheus
    hostname: prometheus
    restart: unless-stopped
    tmpfs:
      - /tmp
    volumes:
      - /opt/grafana/prometheus/config:/etc/prometheus
      - /opt/grafana/prometheus/data:/prometheus
    ports:
      - 9090:9090
```

</details>

Once you have created and saved this `docker-compose.yml` file, give these commands to create the mapped volumes:

```bash
docker compose up -d
docker compose stop prometheus
docker compose stop grafana
```

Now, you should be able to see the following directories:
- `/opt/grafana/grafana/appdata`
- `/opt/grafana/prometheus/config`
- `/opt/grafana/prometheus/data`

## Step 3: Configuring Prometheus

Prometheus needs to be told where to look for the data from the ultrafeeder. We will create a target prometheus configuration file that does this, please copy and paste the following:

<details>
  <summary>&lt;&dash;&dash; Click the arrow to see the shell script</summary>


```bash
sudo touch /opt/grafana/prometheus/config/prometheus.yml
sudo chmod a+rwx /opt/grafana/prometheus/config/prometheus.yml
cat > /opt/grafana/prometheus/config/prometheus.yml <<EOF
global:
  scrape_interval: 15s # Set the scrape interval to every 15 seconds. Default is every 1 minute.
  evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute.

alerting:
  alertmanagers:
    - static_configs:
        - targets:

rule_files:

scrape_configs:
  # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
  - job_name: "prometheus"
    static_configs:
      - targets: ["localhost:9090"]
  - job_name: 'readsb'
    static_configs:
      - targets: ['ip_of_ultrafeeder_machine:9273', 'ip_of_ultrafeeder_machine:9274']
EOF
```

</details>

Make sure to change `ip_of_ultrafeeder_machine` to the IP address or hostname of your ultrafeeder machine.

Once the file has been updated, issue the command `docker compose up -d` in the application directory to apply the changes and bring up the `prometheus` and `grafana` containers.

At this point we will need to add a collector definition to `prometheus` and restart with the new configuration.

1. Issue the command `docker exec -it prometheus sh -c "echo -e \"  - job_name: 'readsb'\n    static_configs:\n      - targets: ['readsb:9273']\" >> /etc/prometheus/prometheus.yml"`
2. Issue the command `docker stop prometheus`
3. Issue the command `docker compose up -d`

You should also be able to point your web browser at:

* `http://docker.host.ip.addr:9090/` to access the `prometheus` console.
* `http://docker.host.ip.addr:3000/` to access the `grafana` console, use admin/admin as initial credentials, you should be prompted to change the password on first login.

Remember to change `docker.host.ip.addr` to the IP address of your docker host.

## Configuring data source and dashboard in Grafana

After you have logged into the `grafana` console the following manual steps are required to connect to `prometheus` as the data source

1. Click `Add your first data source` in the main panel
2. Click `Prometheus` from the list of options provided
3. Input or select the following options, if the option is not listed, do not input anything for that option:

Option | Input
------------- | -------------
Name | readsb
URL | http://prometheus:9090/

Clicking `Save & Test` should return a green message indicating success. The dashboard can now be imported with the following steps

1. Hover over the `four squares` icon in the sidebar, click `+ Import`
2. Enter `18398` into the `Import via grafana.com` section and click `Load`
3. Select `readsb` from the bottom drop down list
4. Click `Import` on the subsequent dialogue box

At this point you should see a very nice dashboard, you can find it under `General` in the `Dashboards` section.
<img src="https://user-images.githubusercontent.com/15090643/228942953-ed8b64aa-3a38-4c6f-bd42-e929b72399b2.png">
<img src="https://user-images.githubusercontent.com/15090643/228943041-7e135856-543a-416a-9331-50853d2e0929.png">
<img src="https://user-images.githubusercontent.com/15090643/228943083-c017c5a0-f5aa-4d03-b241-8e58f2c8a5f6.png">