python-colorlog VS Docker Compose

[supervisord]http\_port=/var/tmp/supervisor.sock ; (default is to run a UNIX domain socket server)stdout\_logfile=/dev/stdoutstdout\_logfile\_maxbytes=0stderr\_logfile=/dev/stderrstderr\_logfile\_maxbytes=0[program:gunicorn\_core\_service]#environment=myapp\_VENV=/opt/myapp/venv/environment=PYTHONPATH=/opt/myapp/myappServer/myappServercommand = /opt/myapp/venv/bin/gunicorn wsgi -b 0.0.0.0:8000 --timeout 90 --access-logfile /dev/stdout --error-logfile /dev/stderrdirectory = /opt/myapp/myappServeruser = rootautostart=trueautorestart=trueredirect\_stderr=truestdout\_logfile=/dev/stdoutstdout\_logfile\_maxbytes=0stderr\_logfile=/dev/stderrstderr\_logfile\_maxbytes=0[program:django-celery]command=/opt/myapp/venv/bin/python ./manage.py celery --app=myappServer.celeryapp:app worker -B --loglevel=INFOdirectory=/opt/myapp/myappServernumprocs=1stdout\_logfile=/dev/stdoutstdout\_logfile\_maxbytes=0stderr\_logfile=/dev/stderrstderr\_logfile\_maxbytes=0redirect\_stderr=trueautostart=trueautorestart=truestartsecs=10[program:nginx]command=nginx -g "daemon off;"#user = rootautostart=trueautorestart=trueredirect\_stderr=truestdout\_logfile=/dev/stdoutstdout\_logfile\_maxbytes=0stderr\_logfile=/dev/stderrstderr\_logfile\_maxbytes=0 5. Since docker can only log once process, the logs of all the process of my container are forwarded to /dev/stdout and /dev/stderr 6. And I use colorlog as color formatter to colorize Django logs:

How is it different from python-colorlog?

sudo curl -L https://github.com/docker/compose/releases/latest/download/docker-compose-$(uname -s)-$(uname -m) -o /usr/local/bin/docker-compose sudo chmod +x /usr/local/bin/docker-compose

Solutions are many, and could include Docker Compose, VS Code dev containers, Telepresence, Localstack or setting up temporary AWS accounts as a development environment for serverless applications.

Using Docker Compose to run Postgres and any third-party services locally provides a streamlined and consistent development environment. Developers can define services in a docker-compose.yml file, which enables them to configure and launch an entire stack with a single command. In this case, Postgres is encapsulated within a container with predefined configurations. Docker Compose also facilitates easy scaling, updates, and isolation of services, enhancing development efficiency and reducing the setup time for new team members or transitioning between projects. It encapsulates complex configurations, such as Postgres' performance monitoring and logging settings, in a manageable, version-controlled file, simplifying and replicating the service setup across different environments.

“Compose simplifies the control of your entire application stack, making it easy to manage services, networks, and volumes in a single, comprehensible YAML configuration file. Then, with a single command, you create and start all the services from your configuration file.” - Docker documentation

curl -fsSL https://get.docker.com -o get-docker.sh sudo sh get-docker.sh # Install docker compose sudo curl -L "https://github.com/docker/compose/releases/download/1.29.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose # Apply executable permissions to the binary sudo chmod +x /usr/local/bin/docker-compose # Run Project docker-compose up -d

Docker,

This foundation now opens the door to even more powerful concepts. You can explore more advanced concepts such as container networking, streamlining the management of complex applications with Docker Compose, and how to make your application data persistent using volumes.

In many projects that are containerized, especially in cases where development is also done locally with docker-compose, teams often have two Dockerfiles, 1 for Development, the other for Production. If you happen to have multiple environments like pre-prod, staging and so on, some teams could have different Dockerfiles for these environments.