Question: How do you configure postgresql.conf when using PostgreSQL in Docker?

Answer

When running PostgreSQL in a Docker container, configuring the postgresql.conf file can be approached in several ways. Here are some effective methods:

1. Mounting a Custom Configuration File

The simplest way to use a custom postgresql.conf is by mounting it into the Docker container. You prepare your configuration file on your host machine and then mount this file to the appropriate location inside the Docker container.

docker run -d \ -v /my/custom/postgresql.conf:/etc/postgresql/postgresql.conf \ postgres

In this example, /my/custom/postgresql.conf is the path on your host machine, and /etc/postgresql/postgresql.conf is the path where PostgreSQL expects its configuration file inside the container (this path can vary depending on how the PostgreSQL image is set up).

2. Using Environment Variables

For common configuration tweaks, many PostgreSQL Docker images support environment variables. For example, setting the environment variable POSTGRES_MAX_CONNECTIONS could correspond to the max_connections setting in postgresql.conf.

docker run -d \ -e POSTGRES_MAX_CONNECTIONS=200 \ postgres

Check the documentation of the specific PostgreSQL Docker image you are using, as available environment variables and their effects can vary.

3. Extending the Official Image

If your configuration needs are complex, you might consider creating a custom Dockerfile that extends the official PostgreSQL image. In your Dockerfile, you can COPY your custom configuration files into the image and adjust ownership or permissions as necessary.

FROM postgres:latest COPY custom_postgresql.conf /etc/postgresql/postgresql.conf RUN chown postgres:postgres /etc/postgresql/postgresql.conf

After building your image, you can run your container with this new image.

Conclusion

Choosing the right method depends on your specific needs, such as whether you need to change just a few parameters or overhaul the entire configuration. The mounting method provides flexibility and ease of updates without rebuilding images, whereas using a custom Dockerfile is suited for environments that require image immutability and strict version control.

Was this content helpful?

White Paper

Free System Design on AWS E-Book

Download this early release of O'Reilly's latest cloud infrastructure e-book: System Design on AWS.

Free System Design on AWS E-Book
Start building today

Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.