Difference between revisions of "Docker"
Adelo Vieira (talk | contribs) (→Docker basics) |
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docker --version | docker --version | ||
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docker logs <container_id/container_name> | docker logs <container_id/container_name> | ||
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| + | '''Execute a command inside a running container:''' | ||
| + | : <syntaxhighlight lang="bash"> | ||
| + | docker exec <container_id/container_name> ls | ||
| + | </syntaxhighlight> | ||
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| + | : The following runs an interactive shell session within a running Docker container: | ||
| + | : <syntaxhighlight lang="bash"> | ||
| + | docker exec -it <container_id/container_name> /bin/bash | ||
| + | </syntaxhighlight> | ||
| + | : <code>-it</code>: enables an interactive terminal session. <code>-i</code> allows you to interact with the container, and <code>-t</code> allocates a pseudo-TTY terminal. | ||
<br /> | <br /> | ||
Revision as of 18:07, 2 June 2023
Docker hub: https://hub.docker.com/
Docker is a popular open-source platform for building, shipping, and running applications in containers. Containers are lightweight and portable environments that allow you to run applications and services with their dependencies isolated from the underlying host system.
Docker images are static snapshots or templates of a specific environment that are used to create and run Docker containers. A Docker image is a lightweight, standalone, and read-only package that contains everything needed to run a piece of software, including the code, runtime, libraries, environment variables, and system tools. It is a snapshot or template of a specific environment that can be used to create and run containers. A Docker container is a running instance of an image.
Using Docker, developers can create containerized applications, package them with all the necessary dependencies, and ship them as a single unit that can be deployed on any system that supports Docker. Docker also provides a way to manage containerized applications at scale, with features such as container orchestration, automated builds, and version control.
Some of the benefits of using Docker include improved application portability, faster development cycles, and better resource utilization. With Docker, developers can focus on building and testing applications, while operations teams can easily deploy and manage them across different environments and infrastructure. [ChatGPT]
Installation
Last time I installed Docker and Docker Compose, I follwed ChatGPT and everything was perfect!
The official documentation to install it in Ubuntu is here: https://docs.docker.com/engine/install/ubuntu/
Why use Docker
- Capture all dependencies as code:
- Python requerements
- OS dependencies.
- Consistent dev and prod environment: You can use the same image for development and production. So you eliminate all the issues that can arrive when changing to another environment in production.
- Easier collaboration: When you share your code with other developers you can be sure it will work. You eliminate all dependencies issues in another developer's machines.
- Different version of Python / Different version of databases / Different version of SDK.
Docker basics
docker --version
docker-compose --version
Download Docker images from https://hub.docker.com/
docker pull postgres docker pull mongo
Create a new Docker container:
- In the case of the official images already built and available on Docker Hub, we you can directly pull and run the image:
docker run mongo docker run -d mongo docker run --name my-mongo-container -d -p 27017:27017 mongo
- The docker build command is used when you want to build a custom Docker image based on specific requirements, using a Dockerfile. So it is used to add customizations or extend the functionality of the image.
Dockerfile# Use the official MongoDB image as the base FROM mongo # Add a custom configuration file COPY my-custom-config.conf /etc/mongodb.conf # Expose a custom port (optional) EXPOSE 27018 # Set an environment variable (optional) ENV MY_VAR=my_value # Run a custom command (optional) CMD ["mongod", "--config", "/etc/mongodb.conf"]
docker build -t my-custom-mongo-image .
docker run --name my-custom-mongo-container -d -p 27018:27018 my-custom-mongo-image
Show all images in our machine:
docker images
Show all containers in our machine:
docker ps # running containers docker ps -a # all
- We should be able to see the Postgres container running.
Start a container:
docker start <container_id/container_name>
- Please note that the
runcommand is used to create a new Docker container while thestartcommand is used to start/run an existing container.
Stop a container:
docker stop <container_id/container_name>
- This command is used to gracefully stop a running container by sending a termination signal (SIGTERM) to the main process inside the container. The container is given a chance to perform any necessary cleanup tasks before it stops.
docker kill <container_id/container_name>- This command is used to forcefully stop a running container by sending a kill signal (SIGKILL) to the main process inside the container. Unlike docker stop, there is no graceful shutdown period or cleanup process. The container is immediately terminated, and any running processes inside the container are abruptly stopped.
Remove a container:
docker rm <container_id/container_name>
- Please note that before you can remove a Docker container, you must stop it.
Remove a Docker image:
docker rmi <image_id>
- Please note that before you can remove a Docker image, you must stop and remove all its associated containers.
Show logs of a container:
docker logs <container_id/container_name>
Execute a command inside a running container:
docker exec <container_id/container_name> ls
- The following runs an interactive shell session within a running Docker container:
docker exec -it <container_id/container_name> /bin/bash-it: enables an interactive terminal session.-iallows you to interact with the container, and-tallocates a pseudo-TTY terminal.
