Update docker roadmap content (#7440)

* rework docker roadmap content

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Containers are lightweight, portable, and isolated software environments that allow developers to run and package applications with their dependencies, consistently across different platforms. They help to streamline application development, deployment, and management processes while ensuring that applications run consistently, regardless of the underlying infrastructure. Containers are lightweight, portable, and isolated software environments that allow developers to run and package applications with their dependencies, consistently across different platforms. They help to streamline application development, deployment, and management processes while ensuring that applications run consistently, regardless of the underlying infrastructure.
## Containers and Docker
Docker is a platform that simplifies the process of creating, deploying, and managing containers. It provides developers and administrators with a set of tools and APIs to manage containerized applications. With Docker, you can build and package application code, libraries, and dependencies into a container image, which can be distributed and run consistently in any environment that supports Docker.
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@What is a Container?](https://www.docker.com/resources/what-container/) - [@official@What is a Container?](https://www.docker.com/resources/what-container/)
- [@article@Introduction to Containers - AWS Skill Builder](https://explore.skillbuilder.aws/learn/course/106/introduction-to-containers) - [@course@Introduction to Containers - AWS Skill Builder](https://explore.skillbuilder.aws/learn/course/106/introduction-to-containers)
- [@feed@Explore top posts about Containers](https://app.daily.dev/tags/containers?ref=roadmapsh) - [@feed@Explore top posts about Containers](https://app.daily.dev/tags/containers?ref=roadmapsh)

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# Need for Containers # Need for Containers
In the world of software development and deployment, consistency and efficiency are crucial. Before containers came into the picture, developers often faced challenges when deploying applications across different environments including: Containers solve the issue around inconsistent environments when working in large teams. Before containers or virtual environments, a lot of issues and time loss was caused by having to install and configure local environments to build projects shared by co-workers or freinds.
- **Inconsistent environments:** Developers often work in different environments which might have different configurations and libraries compared to production servers. This leads to compatibility issues in deploying applications.
- **Inefficient resource utilization:** Virtual Machines (VMs) were widely used to overcome environment inconsistency. However, VMs require an entire OS to be running for each application, making the resource utilization inefficient.
- **Slow processes and scalability issues:** Traditional deployment methods have a slower time to market and scaling difficulties, which hinders fast delivery of software updates.
Visit the following resources to learn more: Visit the following resources to learn more:

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# Bare Metal vs VM vs Containers # Bare Metal vs VM vs Containers
## Bare Metal Bare metal is a term used to describe a computer that is running directly on the hardware without any virtualization. This is the most performant way to run an application, but it is also the least flexible. You can only run one application per server, and you cannot easily move the application to another server. Virtual machines (VMs) are a way to run multiple applications on a single server. Each VM runs on top of a hypervisor, which is a piece of software that emulates the hardware of a computer. The hypervisor allows you to run multiple operating systems on a single server, and it also provides isolation between applications running on different VMs. Containers are a way to run multiple applications on a single server without the overhead of a hypervisor. Each container runs on top of a container engine, which is a piece of software that emulates the operating system of a computer.
Bare metal is a term used to describe a computer that is running directly on the hardware without any virtualization. This is the most performant way to run an application, but it is also the least flexible. You can only run one application per server, and you cannot easily move the application to another server.
## Virtual Machines
Virtual machines (VMs) are a way to run multiple applications on a single server. Each VM runs on top of a hypervisor, which is a piece of software that emulates the hardware of a computer. The hypervisor allows you to run multiple operating systems on a single server, and it also provides isolation between applications running on different VMs.
## Containers
Containers are a way to run multiple applications on a single server without the overhead of a hypervisor. Each container runs on top of a container engine, which is a piece of software that emulates the operating system of a computer.
You can learn more from the following resources: You can learn more from the following resources:
- [@article@History of Virtualization](https://courses.devopsdirective.com/docker-beginner-to-pro/lessons/01-history-and-motivation/03-history-of-virtualization) - [@article@History of Virtualization](https://courses.devopsdirective.com/docker-beginner-to-pro/lessons/01-history-and-motivation/03-history-of-virtualization)
- [@article@Bare Metal Machine](https://glossary.cncf.io/bare-metal-machine/)
- [@article@What is a Virtual Machine?](https://azure.microsoft.com/en-au/resources/cloud-computing-dictionary/what-is-a-virtual-machine)

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The Open Container Initiative (OCI) is a Linux Foundation project which aims at creating industry standards for container formats and runtimes. Its primary goal is to ensure the compatibility and interoperability of container environments through defined technical specifications. The Open Container Initiative (OCI) is a Linux Foundation project which aims at creating industry standards for container formats and runtimes. Its primary goal is to ensure the compatibility and interoperability of container environments through defined technical specifications.
## OCI Specifications
OCI has three main specifications:
- **Runtime Specification (runtime-spec):** It defines the specification for executing a container via an isolation technology, like a container engine. The container runtime built by Docker, called 'containerd', has guided the development of the OCI runtime-spec.
- **Image Specification (image-spec):** It defines the container image format, which describes the contents of a container and can be run by a compliant runtime. Docker's initial image format has led to the creation of the OCI image-spec.
- **Distribution Specification (distribution-spec):** It defines an API protocol to facilitate and standardize the distribution of content. Docker's existing registry API served as a starting point and heavily influenced the design of the OCI Distro Spec.
You can learn more from the following resources: You can learn more from the following resources:
- [@official@Open Container Initiative](https://opencontainers.org/) - [@official@Open Container Initiative](https://opencontainers.org/)

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# What are Namespaces? # What are Namespaces?
In the Linux kernel, namespaces are a feature that allows the isolation of various system resources, making it possible for a process and its children to have a view of a subset of the system that is separate from other processes. Namespaces help to create an abstraction layer to keep containerized processes separate from one another and from the host system. Docker namespaces are a fundamental feature of Linux that Docker uses to create isolated environments for containers. They provide a layer of isolation by creating separate instances of global system resources, making each container believe it has its own unique set of resources. Docker utilizes several types of namespaces, including PID (Process ID), NET (Network), MNT (Mount), UTS (Unix Timesharing System), IPC (InterProcess Communication), and USER namespaces and by leveraging these namespaces, Docker can create lightweight, portable, and secure containers that run consistently across different environments.
There are several types of namespaces in Linux, including:
- **PID (Process IDs)**: Isolates the process ID number space, which means that processes within a container only see their own processes, not those on the host or in other containers.
- **Network (NET)**: Provides each container with a separate view of the network stack, including its own network interfaces, routing tables, and firewall rules.
- **Mount (MNT)**: Isolates the file system mount points in such a way that each container has its own root file system, and mounted resources appear only within that container.
- **UTS (UNIX Time Sharing System)**: Allows each container to have its own hostname and domain name, separate from other containers and the host system.
- **User (USER)**: Maps user and group identifiers between the container and the host, so different permissions can be set for resources within the container.
- **IPC (Inter-Process Communication)**: Allows or restricts the communication between processes in different containers.
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Docker Namespaces](https://docs.docker.com/engine/security/userns-remap/) - [@official@Docker Namespaces](https://docs.docker.com/engine/security/userns-remap/)
- [@article@Linux Namespaces](https://man7.org/linux/man-pages/man7/namespaces.7.html)

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# cgroups # cgroups
**cgroups** or **control groups** is a Linux kernel feature that allows you to allocate and manage resources, such as CPU, memory, network bandwidth, and I/O, among groups of processes running on a system. It plays a crucial role in providing resource isolation and limiting the resources that a running container can use. cgroups or "control groups" are a Linux kernel feature that allows you to allocate and manage resources, such as CPU, memory, network bandwidth, and I/O, among groups of processes running on a system. It plays a crucial role in providing resource isolation and limiting the resources that a running container can use. Docker utilizes cgroups to enforce resource constraints on containers, allowing them to have a consistent and predictable behavior. Below are some of the key features and benefits of cgroups in the context of Docker containers:
Docker utilizes cgroups to enforce resource constraints on containers, allowing them to have a consistent and predictable behavior. Below are some of the key features and benefits of cgroups in the context of Docker containers:
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Control Groups](https://www.docker.com/resources/what-container/#control-groups) - [@official@Control Groups](https://www.docker.com/resources/what-container/#control-groups)
- [@article@Control Groups - Medium](https://medium.com/@furkan.turkal/how-does-docker-actually-work-the-hard-way-a-technical-deep-diving-c5b8ea2f0422) - [@article@Control Groups - Medium](https://medium.com/@furkan.turkal/how-does-docker-actually-work-the-hard-way-a-technical-deep-diving-c5b8ea2f0422)
- [@video@An introduction to cgroups, runc & containerD](https://www.youtube.com/watch?v=u1LeMndEk70)

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Docker Desktop is an easy-to-install application that enables developers to quickly set up a Docker environment on their desktop machines. It is available for both Windows and macOS operating systems. Docker Desktop is designed to simplify the process of managing and running Docker containers, providing a user-friendly interface and seamless integration with the host operating system. Docker Desktop is an easy-to-install application that enables developers to quickly set up a Docker environment on their desktop machines. It is available for both Windows and macOS operating systems. Docker Desktop is designed to simplify the process of managing and running Docker containers, providing a user-friendly interface and seamless integration with the host operating system.
## Installation
To install Docker Desktop on your machine, follow these steps:
- **Download the installer**: You can download the installer for your operating system from the Docker Desktop website. Make sure to choose the appropriate version (Windows or Mac).
- **Run the installer**: Double-click on the downloaded installer file and follow the setup wizard to complete the installation process.
- **Launch Docker Desktop**: Once the installation is complete, start Docker Desktop and sign in with your Docker Hub account. If you don't have an account, you can sign up for a free account on the Docker Hub website.
Learn more from the following resources: Learn more from the following resources:
- [@official@Docker Desktop Documentation](https://docs.docker.com/desktop/) - [@official@Docker Desktop Documentation](https://docs.docker.com/desktop/)

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There is often confusion between "Docker Desktop" and "Docker Engine". Docker Engine refers specifically to a subset of the Docker Desktop components which are free and open source and can be installed only on Linux. Docker Engine can build container images, run containers from them, and generally do most things that Docker Desktop can, but it is Linux only and doesn't provide all of the developer experience polish that Docker Desktop provides. There is often confusion between "Docker Desktop" and "Docker Engine". Docker Engine refers specifically to a subset of the Docker Desktop components which are free and open source and can be installed only on Linux. Docker Engine can build container images, run containers from them, and generally do most things that Docker Desktop can, but it is Linux only and doesn't provide all of the developer experience polish that Docker Desktop provides.
Docker Engine includes:
- Docker Command Line Interface (CLI)
- Docker daemon (dockerd), exposing the Docker Application Programming Interface (API)
For more information about docker engine see: For more information about docker engine see:
- [@official@Docker Engine - Docker Documentation](https://docs.docker.com/engine/) - [@official@Docker Engine - Docker Documentation](https://docs.docker.com/engine/)
- [@video@Docker Engine for Linux Servers Setup and Tips](https://www.youtube.com/watch?v=YeF7ObTnDwc)
- [@feed@Explore top posts about Docker](https://app.daily.dev/tags/docker?ref=roadmapsh) - [@feed@Explore top posts about Docker](https://app.daily.dev/tags/docker?ref=roadmapsh)

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# Installation Setup # Installation Setup
Docker provides a desktop application called **Docker Desktop** that simplifies the installation and setup process. There is also another option to install using the **Docker Engine**. Docker provides a desktop application called*Docker Desktop that simplifies the installation and setup process. There is also another option to install using the Docker Engine but be aware that installing just the Docker Engine will not provide you with any GUI capabilites.
- [@official@Docker Desktop website](https://www.docker.com/products/docker-desktop) - [@official@Docker Desktop website](https://www.docker.com/products/docker-desktop)
- [@official@Docker Engine](https://docs.docker.com/engine/install/) - [@official@Docker Engine](https://docs.docker.com/engine/install/)

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# Ephemeral FS # Ephemeral FS
By default, the storage within a Docker container is ephemeral, meaning that any data changes or modifications made inside a container will only persist as long as the container is running. Once the container is stopped and removed, all the associated data will be lost. This is because Docker containers are designed to be stateless by nature. By default, the storage within a Docker container is ephemeral, meaning that any data changes or modifications made inside a container will only persist as long as the container is running. Once the container is stopped and removed, all the associated data will be lost. This is because Docker containers are designed to be stateless by nature. This temporary or short-lived storage is called the "ephemeral container file system". It is an essential feature of Docker, as it enables fast and consistent deployment of applications across different environments without worrying about the state of a container.
This temporary or short-lived storage is called the "ephemeral container file system". It is an essential feature of Docker, as it enables fast and consistent deployment of applications across different environments without worrying about the state of a container.
## Ephemeral FS and Data Persistence
As any data stored within the container's ephemeral FS is lost when the container is stopped and removed, it poses a challenge to data persistence in applications. This is especially problematic for applications like databases, which require data to be persisted across multiple container life cycles.
To overcome these challenges, Docker provides several methods for data persistence, such as:
- **Volumes**: A Docker managed storage option, stored outside the container's FS, allowing data to be persisted across container restarts and removals.
- **Bind mounts**: Mapping a host machine's directory or file into a container, effectively sharing host's storage with the container.
- **tmpfs mounts**: In-memory storage, useful for cases where just the persistence of data within the life-cycle of the container is required.
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Data Persistence - Docker Documentation](https://docs.docker.com/get-started/docker-concepts/running-containers/persisting-container-data/) - [@official@Data Persistence - Docker Documentation](https://docs.docker.com/get-started/docker-concepts/running-containers/persisting-container-data/)
- [@video@Docker Concepts - Persisting container data](https://www.youtube.com/watch?v=10_2BjqB_Ls)

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Volume mounts are a way to map a folder or file on the host system to a folder or file inside a container. This allows the data to persist outside the container even when the container is removed. Additionally, multiple containers can share the same volume, making data sharing between containers easy. Volume mounts are a way to map a folder or file on the host system to a folder or file inside a container. This allows the data to persist outside the container even when the container is removed. Additionally, multiple containers can share the same volume, making data sharing between containers easy.
## Creating a Volume
To create a volume in Docker, you need to run the following command:
```bash
docker volume create my-volume
```
This command will create a volume named `my-volume`. You can inspect the details of the created volume using the command:
```bash
docker volume inspect my-volume
```
## Mounting a Volume in a Container
To mount a volume to a container, you need to use the `-v` or `--mount` flag while running the container. Here's an example:
Using `-v` flag:
```bash
docker run -d -v my-volume:/data your-image
```
Using `--mount` flag:
```bash
docker run -d --mount source=my-volume,destination=/data your-image
```
In both examples above, `my-volume` is the name of the volume we created earlier, and `/data` is the path inside the container where the volume will be mounted.
## Sharing Volumes Between Containers
To share a volume between multiple containers, simply mount the same volume on multiple containers. Here's how to share `my-volume` between two containers running different images:
```bash
docker run -d -v my-volume:/data1 image1
docker run -d -v my-volume:/data2 image2
```
In this example, `image1` and `image2` would have access to the same data stored in `my-volume`.
## Removing a Volume
To remove a volume, you can use the `docker volume rm` command followed by the volume name:
```bash
docker volume rm my-volume
```
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Docker Volumes](https://docs.docker.com/storage/volumes/). - [@official@Docker Volumes](https://docs.docker.com/storage/volumes/).
- [@official@Docker Volume Flags](https://docs.docker.com/storage/bind-mounts/#choose-the--v-or---mount-flag) - [@official@Docker Volume Flags](https://docs.docker.com/storage/bind-mounts/#choose-the--v-or---mount-flag)
- [@video@Docker Volumes explained in 6 minutes](https://www.youtube.com/watch?v=p2PH_YPCsis)

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Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Docker Bind Mounts](https://docs.docker.com/storage/bind-mounts/) - [@official@Docker Bind Mounts](https://docs.docker.com/storage/bind-mounts/)
- [@article@How to Use Bind Mount in Docker?](https://www.geeksforgeeks.org/how-to-use-bind-mount-in-docker/)

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Running your database in a Docker container can help streamline your development process and ease deployment. Docker Hub provides numerous pre-made images for popular databases such as MySQL, PostgreSQL, and MongoDB. Running your database in a Docker container can help streamline your development process and ease deployment. Docker Hub provides numerous pre-made images for popular databases such as MySQL, PostgreSQL, and MongoDB.
## Example: Using PostgreSQL Image
For PostgreSQL, follow similar steps to those outlined above. First, search for the official image:
```bash
docker search postgres
```
Pull the image:
```bash
docker pull postgres
```
Run a PostgreSQL container, specifying environment variables such as `POSTGRES_PASSWORD`:
```bash
docker run --name some-postgres -e POSTGRES_PASSWORD=my-secret-pw -p 5432:5432 -d postgres
```
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Containerized Databases](https://docs.docker.com/guides/use-case/databases/) - [@official@Containerized Databases](https://docs.docker.com/guides/use-case/databases/)
- [@video@How to Setup MySQL Database with Docker](https://www.youtube.com/watch?v=igc2zsOKPJs)

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Docker allows you to create isolated, disposable environments that can be deleted once you're done with testing. This makes it much easier to work with third party software, test different dependencies or versions, and quickly experiment without the risk of damaging your local setup. Docker allows you to create isolated, disposable environments that can be deleted once you're done with testing. This makes it much easier to work with third party software, test different dependencies or versions, and quickly experiment without the risk of damaging your local setup.
## Creating an Interactive Test Environment with Docker
To demonstrate how to setup an interactive test environment, let's use the Python programming language as an example. We will use a public Python image available on Docker Hub.
- To start an interactive test environment using the Python image, simply run the following command:
```bash
docker run -it --rm python
```
Here, `-it` flag ensures that you're running the container in interactive mode with a tty, and `--rm` flag will remove the container once it is stopped.
- You should now be inside an interactive Python shell within the container. You can execute any Python command or install additional packages using `pip` as you normally would.
```python
print("Hello, Docker!")
```
- Once you are done with your interactive session, you can simply type `exit()` or press `CTRL+D` to exit the container. The container will be automatically removed as specified by the `--rm` flag.
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Launch a Dev Environment](https://docs.docker.com/desktop/dev-environments/create-dev-env/)
- [@article@Test Environments - Medium](https://manishsaini74.medium.com/containerized-testing-orchestrating-test-environments-with-docker-5201bfadfdf2) - [@article@Test Environments - Medium](https://manishsaini74.medium.com/containerized-testing-orchestrating-test-environments-with-docker-5201bfadfdf2)

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Docker images can include command line utilities or standalone applications that we can run inside containers. Docker images can include command line utilities or standalone applications that we can run inside containers.
## BusyBox
BusyBox is a small (1-2 Mb) and simple command line application that provides a large number of the commonly used Unix utilities, such as `awk`, `grep`, `vi`, etc. To run BusyBox inside a Docker container, you simply need to pull the image and run it with Docker:
```bash
docker pull busybox
docker run -it busybox /bin/sh
```
### cURL
cURL is a well-known command line tool that can be used to transfer data using various network protocols. It is often used for testing APIs or downloading files from the internet. To use cURL inside a Docker container, you can use the official cURL image available on Docker Hub:
```bash
docker pull curlimages/curl
docker run --rm curlimages/curl https://example.com
```
In this example, the `--rm` flag is used to remove the container after the command has finished running.
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Docker Images](https://docs.docker.com/engine/reference/commandline/images/) - [@official@Docker Images](https://docs.docker.com/engine/reference/commandline/images/)

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# Using Third Party Images # Using Third Party Images
Third-party images are pre-built Docker container images that are available on [Docker Hub](https://hub.docker.com) or other container registries. These images are created and maintained by individuals or organizations and can be used as a starting point for your containerized applications. Third-party images are pre-built Docker container images that are available on Docker Hub or other container registries. These images are created and maintained by individuals or organizations and can be used as a starting point for your containerized applications.
## Using an Image in Your Dockerfile
For example: If you're looking for a `Node.js` image, you can search for "node" on Docker Hub and you'll find the official Node.js image along with many other community-maintained images.
To use a third-party image in your Dockerfile, simply set the image name as the base image using the `FROM` directive. Here's an example using the official Node.js image:
```dockerfile
FROM node:20
# The rest of your Dockerfile...
```
Visit the following resources to learn more: Visit the following resources to learn more:

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A Dockerfile is a text document that contains a list of instructions used by the Docker engine to build an image. Each instruction in the Dockerfile adds a new layer to the image. Docker will build the image based on these instructions, and then you can run containers from the image. A Dockerfile is a text document that contains a list of instructions used by the Docker engine to build an image. Each instruction in the Dockerfile adds a new layer to the image. Docker will build the image based on these instructions, and then you can run containers from the image.
## Structure of a Dockerfile
A Dockerfile is organized in a series of instructions, one per line. Each instruction has a specific format.
```bash
INSTRUCTION arguments
```
The following is an example of a simple Dockerfile:
```bash
# Use an official Python runtime as a parent image
FROM python:3.7-slim
# Set the working directory to /app
WORKDIR /app
# Copy the current directory contents into the container at /app
COPY . /app
# Install any needed packages specified in requirements.txt
RUN pip install --trusted-host pypi.python.org -r requirements.txt
# Make port 80 available to the world outside this container
EXPOSE 80
# Define environment variable
ENV NAME World
# Run app.py when the container launches
CMD ["python", "app.py"]
```
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Dockerfile Reference](https://docs.docker.com/engine/reference/builder/) - [@official@Dockerfile Reference](https://docs.docker.com/engine/reference/builder/)

@ -1,27 +1,8 @@
# Efficient Layer Caching # Efficient Layer Caching
When building container images, Docker caches the newly created layers. These layers can then be used later on when building other images, reducing the build time and minimizing bandwidth usage. However, to make the most of this caching mechanism, you should be aware of how to efficiently use layer caching. When building container images, Docker caches the newly created layers. These layers can then be used later on when building other images, reducing the build time and minimizing bandwidth usage. However, to make the most of this caching mechanism, you should be aware of how to efficiently use layer caching. Docker creates a new layer for each instruction (e.g., `RUN`, `COPY`, `ADD`, etc.) in the Dockerfile. If the instruction hasn't changed since the last build, Docker will reuse the existing layer.
## How Docker Layer Caching Works
Docker creates a new layer for each instruction (e.g., `RUN`, `COPY`, `ADD`, etc.) in the Dockerfile. If the instruction hasn't changed since the last build, Docker will reuse the existing layer.
For example, consider the following Dockerfile:
```dockerfile
FROM node:14
WORKDIR /app
COPY package.json /app/
RUN npm install
COPY . /app/
CMD ["npm", "start"]
```
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Docker Layer Caching](https://docs.docker.com/build/cache/) - [@official@Docker Layer Caching](https://docs.docker.com/build/cache/)
- [@video@Layer Caching](https://www.youtube.com/watch?v=_nMpndIyaBU)

@ -1,35 +1,6 @@
# Reducing Image Size # Reducing Image Size
- **Use an appropriate base image:** Choose a smaller, more lightweight base image that includes only the necessary components for your application. For example, consider using the `alpine` variant of an official image, if available, as it's typically much smaller in size. Reducing Docker image size is crucial for optimizing storage, transfer speeds, and deployment times. Key strategies include using minimal base images like Alpine Linux, leveraging multi-stage builds to exclude unnecessary build tools, removing unnecessary files and packages, and minimizing the number of layers by combining commands.
```dockerfile
FROM node:14-alpine
```
- **Run multiple commands in a single `RUN` statement:** Each `RUN` statement creates a new layer in the image, which contributes to the image size. Combine multiple commands into a single `RUN` statement using `&&` to minimize the number of layers and reduce the final image size.
```dockerfile
RUN apt-get update && \
apt-get install -y some-required-package
```
- **Remove unnecessary files in the same layer:** When you install packages or add files during the image build process, remove temporary or unused files in the same layer to reduce the final image size.
```dockerfile
RUN apt-get update && \
apt-get install -y some-required-package && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
```
- **Use multi-stage builds:** Use multi-stage builds to create smaller images. Multi-stage builds allow you to use multiple `FROM` statements in your Dockerfile. Each `FROM` statement creates a new stage in the build process. You can copy files from one stage to another using the `COPY --from` statement.
- **Use `.dockerignore` file:** Use a `.dockerignore` file to exclude unnecessary files from the build context that might cause cache invalidation and increase the final image size.
```dockerfile
node_modules
npm-debug.log
```
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,33 +1,6 @@
# Building Container Images # Building Container Images
Container images are executable packages that include everything required to run an application: code, runtime, system tools, libraries, and settings. By building custom images, you can deploy applications seamlessly with all their dependencies on any Docker-supported platform. Container images are executable packages that include everything required to run an application: code, runtime, system tools, libraries, and settings. By building custom images, you can deploy applications seamlessly with all their dependencies on any Docker-supported platform. The key component in building a container image is the `Dockerfile`. It is essentially a script containing instructions on how to assemble a Docker image. Each instruction in the Dockerfile creates a new layer in the image, making it easier to track changes and minimize the image size. Here's a simple example of a Dockerfile:
## Dockerfile
The key component in building a container image is the `Dockerfile`. It is essentially a script containing instructions on how to assemble a Docker image. Each instruction in the Dockerfile creates a new layer in the image, making it easier to track changes and minimize the image size. Here's a simple example of a Dockerfile:
```dockerfile
# Use an official Python runtime as a parent image
FROM python:3.7-slim
# Set the working directory to /app
WORKDIR /app
# Copy the current directory contents into the container at /app
COPY . /app
# Install any needed packages specified in requirements.txt
RUN pip install --trusted-host pypi.python.org -r requirements.txt
# Make port 80 available to the world outside this container
EXPOSE 80
# Define environment variable
ENV NAME World
# Run app.py when the container launches
CMD ["python", "app.py"]
```
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,31 +1,6 @@
# DockerHub # DockerHub
DockerHub is a cloud-based registry service provided by Docker Inc. It is the default public container registry where you can store, manage, and distribute your Docker images. Docker Hub is a cloud-based registry service that serves as the primary public repository for Docker container images. It allows users to store, share, and distribute Docker images, offering both free public repositories and paid private ones and integrates seamlessly with Docker CLI, enabling easy pushing and pulling of images. It features official images maintained by software vendors, automated builds linked to source code repositories, and webhooks for triggering actions based on repository events.
## Features of DockerHub
- **Public and private repositories:** Store your images in public repositories that are accessible to everyone, or opt for private repositories with access limited to your team or organization.
- **Automated Builds:** DockerHub integrates with popular code repositories such as GitHub and Bitbucket, allowing you to set up automated builds for your Docker images
- **Webhooks:** DockerHub allows you to configure webhooks to notify other applications or services when an image has been built or updated.
- **Organizations and Teams:** Make collaboration easy by creating organizations and teams to manage access to your images and repositories.
- **Official Images:** DockerHub provides a curated set of official images for popular software like MongoDB, Node.js, Redis, etc. These images are maintained by Docker Inc.
To push an image to DockerHub, you need to log in to the registry using your DockerHub credentials:
```bash
docker tag your-image your-username/your-repository:your-tag
docker push your-username/your-repository:your-tag
```
To pull images from DockerHub, you can use the `docker pull` command:
```bash
docker pull your-username/your-repository:your-tag
```
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,22 +1,6 @@
# DockerHub Alternatives # DockerHub Alternatives
These alternatives provide a different set of features and functionalities that may suit your container registry needs. Container images can be stored in many different registries, not just Dockerhub. Most major cloud platforms now provide container registries such as "Artifact Registry" on Google Cloud Platform, Elastic Container Registry on AWS and Azure Container Registry on Microsoft Azure. GitHub also provides it's own resistry which is useful when container builds are included in your GitHub Actions workflow.
## Artifact Registry
Artifact Registry is a container registry service provided by Google Cloud Platform (GCP). It offers a fully managed, private Docker container registry that integrates with other GCP services like Cloud Build, Cloud Run, and Kubernetes Engine.
### Amazon Elastic Container Registry (ECR)
Amazon Elastic Container Registry (ECR) is a fully-managed Docker container registry by Amazon Web Services (AWS) that simplifies the process of storing, managing, and deploying Docker images.
### Azure Container Registry (ACR)
Azure Container Registry (ACR) is Microsoft Azure's container registry offering. It provides a wide range of functionalities, including geo-replication for high availability.
### GitHub Container Registry (GHCR)
GitHub Container Registry (GHCR) is the container registry service provided by GitHub. It enhances the support for Docker in GitHub Packages by providing a more streamlined experience for managing and deploying Docker images.
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,22 +1,6 @@
# Image Tagging Best Practices # Image Tagging Best Practices
Properly tagging your Docker images is crucial for efficient container management and deployment. In this section, we will discuss some best practices for image tagging. Docker image tagging best practices center on creating clear, consistent, and informative labels. Adopt semantic versioning for releases, avoid the ambiguous "latest" tag in production, and include relevant metadata like build dates or Git commit hashes. Implement a strategy distinguishing between environments, use descriptive tags for variants, and automate tagging in CI/CD pipelines. Regularly clean up old tags and document your conventions to maintain clarity and facilitate team-wide adoption. These practices ensure efficient image management and improve collaboration across your organization.
## Use Semantic Versioning
When tagging your image, it is recommended to follow Semantic Versioning guidelines. Semantic versioning is a widely recognized method that can help better maintain your application. Docker image tags should have the following structure `<major_version>.<minor_version>.<patch>`. Example: `3.2.1`.
## Tag the Latest Version
Docker allows you to tag an image as 'latest' in addition to a version number. It is a common practice to tag the most recent stable version of your image as 'latest' so that users can quickly access it without having to specify a version number. However, it is important to keep this tag updated as the new versions are released.
```sh
docker build -t your-username/app-name:latest .
```
## Use Automated Build and Tagging Tools
Consider using CI/CD tools (Jenkins, GitLab CI, Travis-CI) to automate image builds and tagging based on commits, branches, or other rules. This ensures consistency and reduces the likelihood of errors caused by manual intervention.
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,14 +1,6 @@
# Container Registries # Container Registries
A **Container Registry** is a centralized storage and distribution system for Docker container images. It allows developers to easily share and deploy applications in the form of these images. Container registries play a crucial role in the deployment of containerized applications, as they provide a fast, reliable, and secure way to distribute container images across various production environments. A Container Registry is a centralized storage and distribution system for Docker container images. It allows developers to easily share and deploy applications in the form of these images. Container registries play a crucial role in the deployment of containerized applications, as they provide a fast, reliable, and secure way to distribute container images across various production environments.
Below is a list of popular container registries available today:
- **Docker Hub**: Docker Hub is the default registry for public Docker images and serves as a platform for sharing and distributing images among developers.
- **Artifact Registry**: Artifact Registry is a managed container registry provided by Google Cloud Platform (GCP), offering private storage and distribution of container images.
- **Amazon Elastic Container Registry (ECR)**: Amazon ECR is a fully-managed Docker container registry provided by Amazon Web Services, offering high scalability and performance for storing, managing, and deploying container images.
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,33 +1,6 @@
# Running Containers # Running Containers
The `docker run` command creates a new container from the specified image and starts it. The `docker run` command creates and starts a new container from a specified image. It combines `docker create` and `docker start` operations, offering a range of options to customize the container's runtime environment. Users can set environment variables, map ports and volumes, define network connections, and specify resource limits. The command supports detached mode for background execution, interactive mode for shell access, and the ability to override the default command defined in the image. Common flags include `-d` for detached mode, `-p` for port mapping, `-v` for volume mounting, and `--name` for assigning a custom container name. Understanding `docker run` is fundamental to effectively deploying and managing Docker containers.
The basic syntax for the `docker run` command is as follows:
```bash
docker run [OPTIONS] IMAGE [COMMAND] [ARG...]
```
- `OPTIONS`: These are command-line flags that can be used to adjust the container's settings, like memory constraints, ports, environment variables, etc.
- `IMAGE`: The Docker image that the container will run. This can be an image from Docker Hub or your own image that is stored locally.
- `COMMAND`: This is the command that will be executed inside the container when it starts. If not specified, the default entrypoint of the image will be used.
- `ARG...`: These are optional arguments that can be passed to the command being executed.
## Examples
Here are some sample commands to help you understand how to use `docker run`:
- Run an interactive session of an Ubuntu container:
```bash
docker run -it --name=my-ubuntu ubuntu
```
- Run an Nginx web server and publish the port 80 on the host:
```bash
docker run -d --name=my-nginx -p 80:80 nginx
```
Visit the following resources to learn more: Visit the following resources to learn more:

@ -2,37 +2,7 @@
Docker Compose is a tool for defining and running multi-container Docker applications. It allows you to create, manage, and run your applications using a simple YAML file called `docker-compose.yml`. This file describes your application's services, networks, and volumes, allowing you to easily run and manage your containers using just a single command. Docker Compose is a tool for defining and running multi-container Docker applications. It allows you to create, manage, and run your applications using a simple YAML file called `docker-compose.yml`. This file describes your application's services, networks, and volumes, allowing you to easily run and manage your containers using just a single command.
## Creating a Docker Compose File
To create a `docker-compose.yml` file, start by specifying the version of Docker Compose you want to use, followed by the services you want to define. Here's an example of a basic `docker-compose.yml` file:
```yaml
version: "3.9"
services:
web:
image: nginx:latest
ports:
- "80:80"
depends_on:
- db
db:
image: mysql:latest
environment:
MYSQL_ROOT_PASSWORD: mysecretpassword
```
The web server exposes its port 80 to the host machine and depends on the launch of the database (`db`).
## Running Docker Compose
To run your Docker Compose application, simply navigate to the directory containing your `docker-compose.yml` file and run the following command:
```bash
docker-compose up
```
Docker Compose will read the file and start the defined services in the specified order.
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Docker Compose documentation](https://docs.docker.com/compose/). - [@official@Docker Compose documentation](https://docs.docker.com/compose/)
- [@video@Docker Compose Tutorial](https://www.youtube.com/watch?v=DM65_JyGxCo)

@ -1,45 +1,8 @@
# Runtime Configuration Options # Runtime Configuration Options
Runtime configuration options allow you to customize the behavior and resources of your Docker containers when you run them. These options can be helpful in managing container resources, security, and networking. Docker runtime configuration options give you powerful control over your containers' environments. By tweaking resource limits, network settings, security profiles, and logging drivers, you can optimize performance and enhance security. You'll also find options for setting environment variables, mounting volumes, and overriding default behaviors – all crucial for tailoring containers to your specific needs. For more advanced users, there are tools to adjust kernel capabilities and set restart policies. Whether you're using command-line flags or Docker Compose files, these options help ensure your containers run smoothly and consistently, no matter where they're deployed.
Here's a brief summary of some commonly used runtime configuration options:
- **CPU:** You can limit the CPU usage of a container with the `--cpus` and `--cpu-shares` options. `--cpus` limits the number of CPU cores a container can use, while `--cpu-shares` assigns relative share of CPU time for the container.
```bash
docker run --cpus=2 --cpu-shares=512 your-image
```
- **Memory:** You can limit and reserve memory for a container using the `--memory` and `--memory-reservation` options. This can help prevent a container from consuming too many system resources.
```bash
docker run --memory=1G --memory-reservation=500M your-image
```
- **User:** By default, containers run as the `root` user. To increase security, you can use the `--user` option to run a container as another user or UID.
```bash
docker run --user 1000 your-image
```
- **Read-only root file system:** To prevent unwanted changes to the container file system, you can use the `--read-only` option to mount the root file system as read-only.
```bash
docker run --read-only your-image
```
- **Publish Ports:** You can use the `--publish` (or `-p`) option to publish a container's ports to the host system. This allows external systems to access the containerized service.
```bash
docker run -p 80:80 your-image
```
- **Hostname and DNS:** You can customize the hostname and DNS settings of a container using the `--hostname` and `--dns` options.
```bash
docker run --hostname=my-container --dns=8.8.8.8 your-image
```
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Docker Documentation](https://docs.docker.com/engine/reference/run/) - [@official@Docker Documentation](https://docs.docker.com/engine/reference/run/)
- [@article@Docker Runtime Arguments](https://galea.medium.com/docker-runtime-arguments-604593479f45)

@ -1,38 +1,6 @@
# Running Containers # Running Containers
To start a new container, we use the `docker run` command followed by the image name. The basic syntax is as follows: Running docker containers is typically done with a simple `docker run` command, which is a combination of the `docker create` and `docker start` commands.
```bash
docker run [options] IMAGE [COMMAND] [ARG...]
```
For example, to run the official Nginx image, we would use:
```bash
docker run -d -p 8080:80 nginx
```
To list all running containers, use the `docker container ls` command.
```bash
docker container ls -a
```
To access a running container's shell, use the `docker exec` command:
```bash
docker exec -it CONTAINER_ID bash
```
To stop a running container, use the `docker stop` command followed by the container ID or name:
```bash
docker container stop CONTAINER_ID
```
```bash
docker container rm CONTAINER_ID
```
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,18 +1,6 @@
# Image Security # Image Security
Image security is a crucial aspect of deploying Docker containers in your environment. Ensuring the images you use are secure, up to date, and free of vulnerabilities is essential. In this section, we will review best practices and tools for securing and managing your Docker images. Image security is a crucial aspect of deploying Docker containers in your environment. Ensuring the images you use are secure, up to date, and free of vulnerabilities is essential. In this section, we will review best practices and tools for securing and managing your Docker images. When pulling images from public repositories, always use trusted, official images as a starting point for your containerized applications. Official images are vetted by Docker and are regularly updated with security fixes. You can find these images on the Docker Hub or other trusted registries.
## Use Trusted Image Sources
When pulling images from public repositories, always use trusted, official images as a starting point for your containerized applications. Official images are vetted by Docker and are regularly updated with security fixes. You can find these images on the Docker Hub or other trusted registries.
## Scan Images for Vulnerabilities
Regularly scan your images for known vulnerabilities using tools like Clair or Anchore. These tools can detect potential risks in your images and container configurations, allowing you to address them before pushing images to a registry or deploying them in production.
## Sign and Verify Images
To ensure the integrity and authenticity of your images, always sign them using Docker Content Trust (DCT). DCT uses digital signatures to guarantee that the images you pull or push are the ones you expect and haven't been tampered with in transit.
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,21 +1,6 @@
# Runtime Security # Runtime Security
Runtime security focuses on ensuring the security of Docker containers while they are running in production. This is a critical aspect of container security, as threats may arrive or be discovered after your containers have been deployed. Runtime security in Docker focuses on ensuring the safety and integrity of containers during their execution, safeguarding against vulnerabilities and malicious activities that could arise while the containerized application is running. This involves monitoring container behavior for anomalies, implementing access controls to limit permissions, and employing tools to detect and respond to suspicious activity in real time. Effective runtime security also ensures that only verified images are deployed and continuously audits the system to maintain compliance, thereby providing a robust defense layer to prevent exploits and maintain the desired security posture throughout the container lifecycle.
- Ensure that your containers are regularly scanned for vulnerabilities, both in the images themselves and in the runtime environment.
- Isolate your containers' resources, such as CPU, memory, and network, to prevent a single compromised container from affecting other containers or the host system.
- Maintain audit logs of container activity to help with incident response, troubleshooting, and compliance.
## Least Privilege Principle
- Run your containers as a non-root user whenever possible.
- Avoid running privileged containers, which have access to all of the host's resources.
- Use Linux capabilities to strip away unnecessary permissions from your containers.
## Read-only Filesystems
- Use the `--read-only` flag when starting your containers to make their filesystems read-only.
- Implement volume mounts or `tmpfs` mounts for locations that require write access.
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,14 +1,6 @@
# Container Security # Container Security
- Container security is a critical aspect of implementing and managing container technologies like Docker. It encompasses a set of practices, tools, and technologies designed to protect containerized applications and the infrastructure they run on. Container security encompasses a broad set of practices and tools aimed at protecting containerized applications from development through deployment and runtime. It involves securing the container image, ensuring that only trusted and non-vulnerable code is used, implementing strong access controls for container environments, and configuring containers to follow the principle of least privilege. Additionally, it includes monitoring for unexpected behavior, protecting communication between containers, and maintaining the host environment’s security. Effective container security integrates seamlessly into DevSecOps workflows to provide continuous visibility and protection across the container lifecycle without disrupting development speed or agility.
- Isolation is crucial for ensuring the robustness and security of containerized environments. Containers should be isolated from each other and the host system, to prevent unauthorized access and mitigate the potential damage in case an attacker manages to compromise one container.
- Implementing best practices and specific security patterns during the development, deployment, and operation of containers is essential to maintaining a secure environment.
- Access controls should be applied to both container management and container data, in order to protect sensitive information and maintain the overall security posture.
- Containers can be vulnerable to attacks, as their images depend on a variety of packages and libraries. To mitigate these risks, vulnerability management should be included in the container lifecycle.
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,23 +1,8 @@
# Docker Images # Docker Images
Docker images are lightweight, standalone, and executable packages that include everything needed to run an application. These images contain all necessary dependencies, libraries, runtime, system tools, and code to enable the application to run consistently across different environments. Docker images are lightweight, standalone, and executable software packages that include everything needed to run a piece of software, such as the application code, runtime, libraries, and system tools. They serve as the blueprint for creating containers and are built in layers, where each layer represents a file system change, allowing for efficient storage and distribution. Docker images can be stored in and pulled from container registries like Docker Hub, enabling developers to share, deploy, and version their applications consistently across different environments, ensuring reproducibility and simplifying the process of managing dependencies.
## Working with Docker Images Learn more from the following resources:
Docker CLI provides several commands to manage and work with Docker images. Some essential commands include: - [@article@What’s the Difference Between Docker Images and Containers?](https://aws.amazon.com/compare/the-difference-between-docker-images-and-containers/)
- [@video@What is an image?](https://www.youtube.com/watch?v=NyvT9REqLe4)
- `docker image ls`: List all available images on your local system.
- `docker build`: Build an image from a Dockerfile.
- `docker image rm`: Remove one or more images.
- `docker pull`: Pull an image from a registry (e.g., Docker Hub) to your local system.
- `docker push`: Push an image to a repository.
For example, to pull the official Ubuntu image from Docker Hub, you can run the following command:
```bash
docker pull ubuntu:latest
```
## Sharing Images
Docker images can be shared and distributed using container registries, such as Docker Hub, Google Container Registry, or Amazon Elastic Container Registry (ECR). Once your images are pushed to a registry, others can easily access and utilize them.

@ -1,22 +1,6 @@
# Containers # Containers
Containers can be thought of as lightweight, stand-alone, and executable software packages that include everything needed to run a piece of software, including the code, runtime, libraries, environment variables, and config files. Containers isolate software from its surroundings, ensuring that it works uniformly across different environments. Containers are isolated, lightweight environments that run applications using a shared operating system kernel, ensuring consistency and portability across different computing environments. They encapsulate everything needed to run an application, such as code, dependencies, and configurations, making it easy to move and run the containerized application anywhere. Using the Docker CLI, you can create, start, stop, and manage containers with commands like `docker run`, `docker ps` to list running containers, `docker stop` to halt them, and `docker exec` to interact with them in real time. The CLI provides a powerful interface for developers to build, control, and debug containers effortlessly, allowing for streamlined development and operational workflows.
## Working with Containers using Docker CLI
Docker CLI offers several commands to help you create, manage, and interact with containers. Some common commands include:
- `docker run`: Used to create and start a new container.
- `docker container ls`: Lists running containers.
- `docker container stop`: Stops a running container.
- `docker container rm`: Removes a stopped container.
- `docker exec`: Executes a command inside a running container.
- `docker logs`: Fetches the logs of a container, useful for debugging issues.
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,19 +1,9 @@
# Docker Networks # Docker Networks
Docker networks provide an essential way of managing container communication. It allows containers to talk to each other and to the host machine using various network drivers. By understanding and utilizing different types of network drivers, you can design container networks to accommodate specific scenarios or application requirements. Docker networks enable containers to communicate with each other and with external systems, providing the necessary connectivity for microservices architectures. By default, Docker offers several network types such as bridge, host, and overlay, each suited for different use cases like isolated environments, high-performance scenarios, or multi-host communication. Using the Docker CLI, you can create, inspect, and manage networks with commands like `docker network create` to define custom networks, `docker network ls` to list existing networks, and `docker network connect` to attach a container to a network. This flexibility allows developers to control how containers interact, ensuring secure and efficient communication across distributed applications.
## Managing Docker Networks
Docker CLI provides various commands to manage the networks. Here are a few useful commands:
- List all networks: `docker network ls`
- Inspect a network: `docker network inspect <network_name>`
- Create a new network: `docker network create --driver <driver_type> <network_name>`
- Connect containers to a network: `docker network connect <network_name> <container_name>`
- Disconnect containers from a network: `docker network disconnect <network_name> <container_name>`
- Remove a network: `docker network rm <network_name>`
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Docker Networks](https://docs.docker.com/network/) - [@official@Docker Networks](https://docs.docker.com/network/)
- [@official@Docker Network Commands](https://docs.docker.com/engine/reference/commandline/network/) - [@official@Docker Network Commands](https://docs.docker.com/engine/reference/commandline/network/)
- [@video@Docker Networking](https://www.youtube.com/watch?v=bKFMS5C4CG0)

@ -1,30 +1,6 @@
# Docker Volumes # Docker Volumes
Docker volumes are a mechanism for persisting data generated by and used by Docker containers. They allow you to separate the data from the container itself, making it easy to backup, migrate, and manage your persistent data. Docker volumes are persistent storage solutions used to manage and store data outside the container’s filesystem, ensuring data remains intact even if the container is deleted or recreated. They are ideal for storing application data, logs, and configuration files that need to persist across container restarts and updates. With the Docker CLI, you can create and manage volumes using commands like `docker volume create` to define a new volume, `docker volume ls` to list all volumes, and `docker run -v` to mount a volume to a specific container. This approach helps maintain data integrity, simplifies backup processes, and supports data sharing between containers, making volumes a core part of stateful containerized applications.
## Types of Volumes
There are three types of volumes in Docker:
- **Host Volumes**
- **Anonymous Volumes**
- **Named Volumes**
## Volume Management with Docker CLI
Docker CLI provides various commands to manage volumes:
- `docker volume create`: Creates a new volume with a given name.
- `docker volume ls`: Lists all volumes on the system.
- `docker volume inspect`: Provides detailed information about a specific volume.
- `docker volume rm`: Removes a volume.
- `docker volume prune`: Removes all unused volumes.
To use a volume in a container, you can use the `-v` or `--volume` flag during the `docker run` command. For example:
```bash
docker run -d --name my-container -v my-named-volume:/var/lib/data my-image
```
Visit the following resources to learn more: Visit the following resources to learn more:

@ -1,45 +1,6 @@
# Docker CLI # Docker CLI
The Docker CLI (Command Line Interface) is a powerful tool that allows you to interact with and manage Docker containers, images, volumes, and networks. It provides a wide range of commands for users to create, run, and manage Docker containers and other Docker resources in their development and production workflows. The Docker Command Line Interface (CLI) is a powerful tool used to interact with the Docker engine, enabling developers and operators to build, manage, and troubleshoot containers and related resources. With a wide range of commands, the Docker CLI provides control over all aspects of Docker, including creating and managing containers (`docker run`, `docker stop`), building images (`docker build`), managing networks (`docker network`), handling storage (`docker volume`), and inspecting system status (`docker ps`, `docker info`). Its intuitive syntax and flexibility allow users to automate complex workflows, streamline development processes, and maintain containerized applications with ease, making it a foundational utility for Docker management and orchestration.
In this topic, we'll dive into some key aspects of Docker CLI, covering the following:
## 1. Installation
To get started with Docker CLI, you need to have Docker installed on your machine. You can follow the official installation guide for your respective operating system from the [Docker documentation](https://docs.docker.com/get-docker/).
## 2. Basic Commands
Here are some essential Docker CLI commands to familiarize yourself with:
- `docker run`: Create and start a container from a Docker image
- `docker container ls`: List running containers
- `docker image ls`: List all available images on your system
- `docker pull`: Pull an image from Docker Hub or another registry
- `docker push`: Push an image to Docker Hub or another registry
- `docker build`: Build an image from a Dockerfile
- `docker exec`: Run a command in a running container
- `docker logs`: Show logs of a container
## 3. Docker Run Options
`docker run` is one of the most important commands in the Docker CLI. You can customize the behavior of a container using various options, such as:
- `-d, --detach`: Run the container in the background
- `-e, --env`: Set environment variables for the container
- `-v, --volume`: Bind-mount a volume
- `-p, --publish`: Publish the container's port to the host
- `--name`: Assign a name to the container
- `--restart`: Specify the container's restart policy
- `--rm`: Automatically remove the container when it exits
## 4. Dockerfile
A Dockerfile is a script containing instructions to build a Docker image. You can use the Docker CLI to build, update, and manage Docker images using a Dockerfile.
## 5. Docker Compose
Docker Compose is a CLI tool for defining and managing multi-container Docker applications using YAML files. It works together with the Docker CLI, offering a consistent way to manage multiple containers and their dependencies.
Visit the following resources to learn more: Visit the following resources to learn more:

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# Tests # Tests
We want to run tests in an environment as similar as possible to production, so it only makes sense to do so inside of our containers! We want to run tests in an environment as similar as possible to production, so it only makes sense to do so inside of our containers! This can include unit tests, integration tests, and end-to-end tests, all run within Docker containers to simulate real-world scenarios while avoiding interference from external dependencies. Using Docker CLI and tools like Docker Compose, you can create isolated testing environments, run tests in parallel, and spin up and tear down the necessary infrastructure automatically.
Visit the following resources to learn more: Visit the following resources to learn more:

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# Developer Experience # Developer Experience
So far we have only discussed using docker for deploying applications. However, docker is also a great tool for developing applications. There are a few different recommendations that you can adopt to improve your development experience. Docker significantly enhances the developer experience by providing a consistent, isolated environment for building, testing, and running applications, eliminating the “it works on my machine” problem. With Docker, developers can package their applications and dependencies into portable containers, ensuring consistency across different environments, from local development to staging and production. The simplified setup and reproducibility of environments accelerate onboarding, minimize conflicts, and allow developers to focus on coding rather than troubleshooting configurations. Moreover, tools like Docker Compose enable quick orchestration of complex multi-container applications, making it easier to prototype, iterate, and collaborate, ultimately streamlining the entire development lifecycle.
- Use `docker-compose` in your application for ease of development.
- Use bind mounts to mount the code from your local into the container filesystem to avoid having to rebuild the container image with every single change.
- For auto-reloading, you can use tools like [vite](https://vitejs.dev/) for client side, [nodemon](https://nodemon.io/) for nodejs or [air](https://github.com/cosmtrek/air) for golang.
- You should also provide a way to debug your applications. For example, look into [delve](https://github.com/go-delve/delve) for Go, enable debugging in node.js using --inspect flag etc. It doesn't matter what you use, but the point is that you should have a way to debug your application running inside the container.
- You should have a way to run tests inside the container. For example, you could have a separate docker-compose file for running tests.
- You should have a CI pipeline for production images.
- Ephemeral environment for each pull request
For more details and practical examples: For more details and practical examples:

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# PaaS Options for Deploying Containers # PaaS Options for Deploying Containers
Platform as a Service (PaaS) is a cloud computing model that simplifies the deployment and management of containers. It abstracts away the underlying infrastructure allowing developers to focus on creating and running their applications. Given below are some of the popular PaaS options for deploying containers: Platform-as-a-Service (PaaS) options for deploying containers provide a simplified and managed environment where developers can build, deploy, and scale containerized applications without worrying about the underlying infrastructure. Popular PaaS offerings include Google Cloud Run, Azure App Service, AWS Elastic Beanstalk, and Heroku, which abstract away container orchestration complexities while offering automated scaling, easy integration with CI/CD pipelines, and monitoring capabilities. These platforms support rapid development and deployment by allowing teams to focus on application logic rather than server management, providing a seamless way to run containers in production with minimal operational overhead.
## Amazon Elastic Container Service
is a fully managed container orchestration service offered by Amazon Web Services. It allows you to run containers without having to manage servers or clusters.
## Google Cloud Run
Google Cloud Run is a fully-managed compute platform by Google that allows you to run stateless containers. It is designed for running applications that can scale automatically, enabling you to pay only for the resources you actually use.
## IBM Cloud Code Engine
IBM Cloud Code Engine is a fully managed, serverless platform by IBM that runs your containerized applications and source code. It supports deploying, running, and auto-scaling applications on Kubernetes.
## Microsoft Azure Container Instances
Microsoft Azure Container Instances is a service offered by Microsoft Azure that simplifies the deployment of containers using a serverless model. You can run containers without managing the underlying hosting infrastructure or container orchestration.
Visit the following resources to learn more: Visit the following resources to learn more:

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# Kubernetes # Kubernetes
Kubernetes (K8s) is an open-source orchestration platform used for automating the deployment, scaling, and management of containerized applications. While Docker provides the container runtime environment, Kubernetes extends that functionality with a powerful and flexible management framework. Kubernetes is an open-source container orchestration platform designed to automate the deployment, scaling, and management of containerized applications. It provides a robust framework for handling complex container workloads by organizing containers into logical units called pods, managing service discovery, load balancing, and scaling through declarative configurations. Kubernetes enables teams to deploy containers across clusters of machines, ensuring high availability and fault tolerance through self-healing capabilities like automatic restarts, replacements, and rollback mechanisms. With its extensive ecosystem and flexibility, Kubernetes has become the de facto standard for running large-scale, distributed applications, simplifying operations and improving the reliability of containerized workloads.
## Key Concepts
- **Cluster**: A set of machines, called nodes, that run containerized applications in Kubernetes. A cluster can have multiple nodes for load balancing and fault tolerance.
- **Node**: A worker machine (physical, virtual, or cloud-based) that runs containers as part of the Kubernetes cluster. Each node is managed by the Kubernetes master.
- **Pod**: The smallest and simplest unit in the Kubernetes object model. A pod represents a single instance of a running process and typically wraps one or more containers (e.g., a Docker container).
- **Service**: An abstraction that defines a logical set of pods and a policy for accessing them. Services provide load balancing, monitoring, and networking capabilities for the underlying pods.
- **Deployment**: A high-level object that describes the desired state of a containerized application. Deployments manage the process of creating, updating, and scaling pods based on a specified container image.
## Kubernetes vs. Docker Swarm
While both Kubernetes and Docker Swarm are orchestration platforms, they differ in terms of complexity, scalability, and ease of use. Kubernetes provides more advanced features, better scalability, and higher fault tolerance, but has a steeper learning curve. Docker Swarm, on the other hand, is simpler and more straightforward but lacks some advanced functionality.
Visit the following resources to learn more: Visit the following resources to learn more:

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# Docker Swarm # Docker Swarm
Docker Swarm is a container orchestration tool that enables users to manage multiple Docker nodes and deploy services across them. It is a native clustering and orchestration feature built into the Docker Engine, which allows you to create and manage a swarm of Docker nodes, referred to as a _Swarm_. Docker Swarm is Docker’s native container orchestration tool that allows users to deploy, manage, and scale containers across a cluster of Docker hosts. By transforming a group of Docker nodes into a single, unified cluster, Swarm provides high availability, load balancing, and automated container scheduling using simple declarative commands. With features like service discovery, rolling updates, and integrated security through TLS encryption, Docker Swarm offers an approachable alternative to more complex orchestrators like Kubernetes. Its tight integration with the Docker CLI and ease of setup make it a suitable choice for small to medium-sized deployments where simplicity and straightforward management are priorities.
## Advantages
- **Scalability**: Docker Swarm allows you to scale services horizontally by easily increasing or decreasing the number of replicas.
- **Load balancing**: Swarm ensures that the nodes within the swarm evenly handle container workloads by providing internal load balancing.
- **Service discovery**: Docker Swarm allows you to automatically discover other services in the swarm by assigning a unique DNS entry to each service.
- **Rolling updates**: Swarm enables you to perform rolling updates with near-zero downtime, easing the process of deploying new versions of your applications.
Visit the following resources to learn more: Visit the following resources to learn more:

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Deploying containers is a crucial step in using Docker and containerization to manage applications more efficiently, easily scale, and ensure consistent performance across environments. This topic will give you an overview of how to deploy Docker containers to create and run your applications. Deploying containers is a crucial step in using Docker and containerization to manage applications more efficiently, easily scale, and ensure consistent performance across environments. This topic will give you an overview of how to deploy Docker containers to create and run your applications.
## Benefits of Container Deployment
- **Consistency**: Containers ensure your application runs the same way across different environments, solving the "it works on my machine" issue.
- **Isolation**: Each container operates independently, avoiding conflicts and allowing better service management.
- **Scalability**: Easily scale applications by running multiple instances and distributing the workload.
- **Version Control**: Manage different versions and roll back to previous versions if needed.
## Steps to Deploy Containers
- **Create a Dockerfile**: Script that defines the image with base image, code, dependencies, and configurations.
- **Build the Docker Image**: Use `docker build` to create an image from the Dockerfile.
- **Push the Docker Image**: Push the image to a registry using `docker push`.
- **Deploy the Container**: Use `docker run` to start a container from the image.
- **Manage the Container**: Use commands like `docker ps`, `docker stop`, and `docker rm` for container management.
- **Monitor and Log**: Use `docker logs` for log viewing and `docker stats` for performance monitoring.
Visit the following resources to learn more: Visit the following resources to learn more:
- [@official@Docker Deployment](https://docs.docker.com/get-started/deployment/) - [@official@Docker Deployment](https://docs.docker.com/get-started/deployment/)

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