screenly / balena-prometheus-exporter

Development Environment Setup Using Docker

The following steps outline the configuration of Docker for the development environment of the screenly/balena-prometheus-exporter project. This will help maintain a clean separation between development and production requirements.

Step 1: Create the Dockerfile

The Dockerfile is essential for containerizing the application. Below is the code for the Dockerfile used in the development environment:

FROM python:3.10-alpine

WORKDIR /usr/src/app

COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt

COPY main.py .

USER nobody

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

Explanation:

  • FROM python:3.10-alpine: The image is based on Alpine Linux with Python 3.10 installed to keep the image lightweight.
  • WORKDIR /usr/src/app: Sets the working directory in the container.
  • COPY requirements.txt ./: Copies the requirements.txt file into the container for dependency installation.
  • RUN pip install –no-cache-dir -r requirements.txt: Installs the required Python packages without caching.
  • COPY main.py .: Copies the main application script into the container.
  • USER nobody: Runs the application as a non-privileged user for security reasons.
  • CMD [ “python”, “./main.py” ]: Specifies the command to run when the container starts, executing the main script.

Step 2: Define Dependencies

The requirements.txt file should contain all necessary packages for the exporter to function. Below is the content of the requirements.txt file:

certifi==2024.7.4
charset-normalizer==3.1.0
idna==3.4
prometheus-client==0.16.0
requests==2.31.0
urllib3==1.26.18

Step 3: Building the Docker Image

To build the Docker image, navigate to the directory containing the Dockerfile and execute the following command:

$ docker build -t balena-exporter .

Explanation:

  • docker build: Command to build the Docker image.
  • -t balena-exporter: Tags the image with the name balena-exporter.
  • .: Indicates the current directory as the context for the Docker build.

Step 4: Running the Docker Container

Once the image is built, the application can be run in a container with the following command:

$ docker run -d \
--name balena-exporter \
-p 8000:8000 \
-e BALENA_TOKEN= \
balena-exporter

Explanation:

  • docker run -d: Runs the container in detached mode.
  • –name balena-exporter: Assigns a name to the container for easier management.
  • -p 8000:8000: Maps port 8000 of the container to port 8000 of the host, allowing access to the application.
  • -e BALENA_TOKEN=: Sets the BALENA_TOKEN environment variable necessary for the application’s authentication. This token must be set appropriately.
  • balena-exporter: Specifies which image to run.

Step 5: Verifying the Exporter

To ensure the exporter is functioning correctly, perform a curl command to the mapped port:

curl http://localhost:8000

This should return the metrics exposed by the exporter.

Optional Environment Variables

The application has an optional CRAWL_INTERVAL environment variable that controls how frequently the application queries the Balena API. By default, this is set to 60 seconds. To set this variable, include it in the docker run command as shown below:

-e CRAWL_INTERVAL=30

This example sets the crawl interval to 30 seconds instead of the default.

Source

  • Dockerfile, main.py, requirements.txt from screenly/balena-prometheus-exporter.