Docker is a tool that enables you to package applications in containers to be easily deployed and run on any host machine. Containers provide a way to isolate an application from its surroundings, including the operating system, the filesystem, and other applications. This isolation makes it much easier to deploy and run applications because you don't have to worry about compatibility issues between the different components. All you need to run a container is a Docker engine.
Docker containers can easily be created and run on any host machine, ideal for development, testing, and production environments. You can even run Docker containers inside virtual machines!
Docker also has a powerful Docker Compose tool, which allows you to define and manage multi-container applications. With Compose, you can specify the different components of your application in a YAML file, and then docker-compose will automatically handle the details of creating and connecting the containers.
Easier application deployment and management: With Docker, you can package an application in a container to be easily deployed on any host machine. Containers provide a consistent environment for applications, so you don't have to worry about compatibility issues between different components.
Isolation: Containers isolate an application from its surroundings, making it much easier to deploy and run applications.
multi-container applications: With Docker Compose, you can easily define and manage multi-container applications.
Reduced resource usage: Containers are very efficient in resource usage. They can be easily scaled up or down as needed, so you only use your resources.
Increased Security: Containers help increase Security by isolating applications from each other and the host operating system.
Flexibility: Docker containers can be run on any platform that supports Docker, including Linux, Windows, and macOS.
Portability: Docker containers can be easily moved from one host to another.
Reduced costs: Using containers, you can reduce the cost of infrastructure and operations.
Improved Efficiency: With Docker, you can quickly deploy and run applications with minimal overhead.
Images are used to create containers. A Docker image is a read-only template that contains a set of instructions for creating a Docker container. Images are created using the build command. The build command takes a Dockerfile and creates an image.
A Dockerfile is a text file that contains all the commands necessary to build an image. By default, Docker will build images using the instructions defined in a Dockerfile. However, it is also possible to build images using other methods, such as importing existing files or directories. To create a Dockerfile, one must first have a base image to build from. This can be done by either downloading an existing image from a registry or creating an image from scratch. Once the base image has been created, the Dockerfile can be used to add layers on top of it, such as adding files, installing software, or configuring settings. When building an image from a Dockerfile, it is important to note that each instruction will create a new layer. As a result, it is important to carefully consider the order of instructions to minimize the number of layers and keep the image size as small as possible.
Docker Registry is a service that stores and lets you distribute Docker images. It can be public or private. Public registries are available to anyone without authentication, while private ones require authentication. Docker Hub is a public registry hosted by Docker, Inc. Any user can create an account and push their images to it. You can also pull images from Docker Hub without an account, but you'll be limited to certain rate limits unless you create an account and log in. There are other public registries besides Docker Hub, but most of them are run by third-party organizations. Private registries can be hosted by anyone, including yourself. They just need to have the proper infrastructure in place to support it. Typically, a private registry will be used for storing images for an organization that doesn't want to use a public one. For example, a company may not want its proprietary images to be available to the general public. Or, an organization may want more control over who has access to their images and what they can do with them. You need to have the proper credentials to push or pull images from a private registry. These credentials are typically a username and password, but they can also be an API key or authentication.
Once an image has been created, it can be stored in a registry, such as Docker Hub and used to create containers. When creating a container from an image, you can specify which command should be executed when the container starts up. For example, you could specify that the container should run a web server. By default, containers are created with a random name. However, you can specify a name for your container when you create it. Container names must be unique within a single host. You can use the docker ps command to list all running containers. The docker stop command can be used to stop a running container. And the docker rm command can be used to delete a stopped container.
Docker run is a command used to start, create, and run a container from a Docker image. This command can launch containers either in the background or in the foreground. When run in the background, the container will be created and started but will not be attached to the terminal. This is useful for running long-running processes, such as web servers that do not need to be attached to a terminal. To run a container in the foreground, simply add the -it flags to the docker run command. This will attach the terminal to the container, allowing you to interact with it. Once you are finished with the container, you can use the docker stop command to stop it.
Any computer with a Docker daemon installed can be a host for running containers. The daemon does the heavy lifting of building, running, and distributing your containers. When you use the Docker CLI to run commands related to containers, those commands are sent to the Docker daemon. Then, the daemon runs them on your behalf. The daemon can run on the same machine as your applications or on a remote machine. It doesn't matter where the daemon runs as long as it has network access to all machines running containers. You can even install the Docker daemon inside of a container. This is called "Docker in Docker" and is used for tasks like building containers.
A virtual machine (VM) is a software computer that, like a physical computer, runs an operating system and applications. The major difference between a VM and a physical computer is that a VM runs on a computer that shares hardware resources with other VMs. A VM uses software to emulate hardware, so multiple virtual machines can run on a single physical machine without multiple sets of physical hardware.
Docker is an open-source project that automates the deployment of applications inside software containers by providing an additional layer of abstraction and automation of operating-system-level virtualization on Linux.
Docker containers can run on any operating system that supports the Linux kernel, including Windows and macOS.
Virtual machines can run on any operating system, including Windows, macOS, and Linux.
Lightweight: One of the main advantages of containers is that they are very lightweight. They don't need a full operating system like virtual machines (VMs). Instead, they share the kernel of the host operating system. This makes them much faster to start up and shut down. In addition, it means that you can run many more containers on a single server than you could VMs. This can lead to significant cost savings, as you don't need to purchase as many servers.
Portable: Containers have many advantages over traditional virtual machines (VMs). They are more portable, for one thing. Containers can be easily moved from one host to another, making them ideal for applications that need to be deployed across multiple environments. This portability makes it easy to move containers between different clouds and even between on-premise and cloud-based infrastructures. In addition, containers are more efficient than VMs, making them a good choice for applications that need to run in resource-constrained environments. Finally, containers are more secure than VMs, thanks to their isolation properties. This makes them an attractive option for sensitive applications that need to be run in a highly controlled environment.
Flexible: There's no denying the benefits of virtual machines. They're easy to set up and manage, and they offer a high degree of isolation between different applications. However, VMs can also be inflexible, especially when changing resource requirements. This is where containers can come in handy. Unlike VMs, containers can be easily scaled up or down as needed, making them more flexible for development and production environments. In addition, containers use far fewer resources than VMs, so you can fit more of them on a single server. This makes them ideal for organizations that need to run multiple applications but don't have the budget for a large number of VMs.
Scalable: Containers are a type of virtualization that is becoming increasingly popular due to their many benefits. One of the biggest advantages of containers is that they are highly scalable. Containers can be easily added or removed as needed, making them more flexible than virtual machines (VMs). This makes it easy to scale up or down as needed without providing new VMs. As a result, containers can help save time and money while still providing businesses flexibility and scalability.
Version Control: Container technology has made it easier to version control your applications and dependencies. In the past, developers had to manually keep track of different versions of their code and dependencies, which was often error-prone and time-consuming. This information is automatically tracked with containers and can be easily rolled back if needed. This makes it easy to experiment with new features and quickly revert back to a stable version if something goes wrong. In addition, containers make it easy to share code between developers since all of the dependencies are wrapped up in a self-contained package. As a result, container technology has hugely impacted how software is developed and maintained.
Dependencies: In a traditional application, dependencies are scattered across various components, making it difficult to keep track of them. This can lead to versioning issues and inconsistencies that can cause the application to break. By contrast, containers package all of an application's dependencies together. This makes deploying the application easier, as all dependencies will be satisfied. Additionally, containers make it easy to roll back to a previous version if necessary. As a result, containers can help to reduce the complexity of deployments and make them more reliable.
Security: In computing, Security is a paramount concern. Businesses and individuals alike rely on security systems to protect their data from attack. Virtual machines (VMs) have long been a secure option for running applications. However, containers have emerged as a more secure alternative in recent years. Containers offer a higher level of Security than VMs by isolating applications from each other. This Isolation ensures that if one application is compromised, the others will remain safe. In addition, containers are often run with much fewer privileges than VMs, making it more difficult for an attacker to access sensitive data. As a result, containers offer a more secure way to run applications than VMs.
Efficiency: When it comes to computing resources, Efficiency is key. After all, the more efficient a system is, the less waste there is and the lower the operating costs. That's one of the main reasons containers have become so popular in recent years. Containers are much more efficient than virtual machines because they don't need to boot up a full operating system every time they start. This means they can start up far faster and use far fewer resources overall. As a result, containers can help significantly reduce infrastructure costs. In addition, containers are much easier to scale than VMs, meaning that they can be used to support far more workloads with far less overhead. Consequently, it's no wonder that containers are increasingly seen as the future of compute resource management.
cost: When deciding between containers and virtual machines (VMs), the cost is often a major factor. In general, containers are more cost-effective than VMs because they are lighter weight and more efficient. With VMs, each instance includes a full copy of the operating system, leading to wasted resources. Containers share a common operating system and only include the files necessary for each individual application. This makes them much lighter and more efficient, resulting in lower costs. In addition, containers can be scaled up or down more easily than VMs, which helps keep costs under control. As a result, containers are often the best option when the cost is a major consideration.
ease of use: Containerization can be an extremely helpful tool for developers looking to simplify the process of dependency management. By packaging all of the necessary dependencies into a single container, developers can avoid the hassle of manually managing these dependencies on their own. Additionally, containers can be easily run on any system that supports the required runtime environment, making it easy to deploy application dependencies across multiple machines. As a result, containerization can save developers time and effort in managing application dependencies.
In general, containers are more efficient than virtual machines and can help to reduce infrastructure costs. They are also much easier to scale than VMs, making them a good choice for supporting large numbers of workloads. Additionally, containers offer a higher level of Portability and ease of use thanks to their ability to be run on any system that supports the required runtime environment. As a result, when cost, Efficiency, and convenience are important factors, containers are often the best choice.
Let's make a small web application to run with the Python HTTP Server.
echo "hello docker world\! version 1" > index.html
Now run the following command to run this application,
python -m http.server
This will start a python HTTP server on port 8000, which you can test using curl or by visiting http://localhost:8000 in your web browser.
The output should look like this:
hello, docker world! version 1
Now we have a web application that does the basic operations; let's create our own custom image using a Dockerfile which we will use to run our web application.
In order to create a docker image, we need to write Dockerfile, which contains all the necessary steps to build an image. Let's create our first Dockerfile by writing the following content in it.
FROM python:3-alpine MAINTAINER "email@example.com" COPY index.html index.html CMD ["python", "-m", "http.server"]
In the first line, we are using FROM command, which tells the docker to download the python 3 images from the docker hub, we need to specify the maintainer name, which is optional, but it's a good practice to write it in order to give credit to the developer.
In the third line, we are using the COPY command, which copies our index.html file from your current working directory to the app directory in the container, and in the last line, we are telling docker to run a python HTTP server as soon as the container starts running.
Now that we have written our Dockerfile, let's build a docker image by running the following command.
docker build -t hello-world:1 .
In the above command, we are using the -t option, which stands for the tag in order to give a name and a version to our docker image, and .(dot) at the end tells docker to look for Dockerfile in the current working directory.
After the image is built, we can verify it by running the following command, which will list all the available images on our system.
In order to run a docker container, we need to use the docker run command and specify the name of the image that we want to run.
docker run hello-world:1
Let's test this using the curl command.
The output should look like this.
curl: (7) Failed to connect to localhost port 8000 after 8 ms: Connection refused
Here you see connection refused; the reason behind this is container ports are not exposed to the outside world. To fix this issue, we publish a container's port to the host as follows,
docker run -p 8000:8000 hello-world:1
Now, if you run the curl command again, you will see the following output,
hello docker world! version 1
This means that our container is running properly, and it's responding to the requests.
You can also verify that the container is running by using the docker ps command, which lists all the running containers on your system.
You will see output something similar to this.
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 17d5c3466b11 hello-world:1 "python -m http.serv…" 44 seconds ago Up 44 seconds 0.0.0.0:8000->8000/tcp, :::8000->8000/tcp sleepy_murdock
To stop a container, you can use the docker stop command followed by the container ID or name.
docker stop <container ID or Name>
If you want to remove a stopped container, you can use the docker rm command followed by the container ID or name.
docker rm <container ID or Name>
If you want to remove an image, you can use the docker rmi command followed by the image ID or name.
docker rmi <image id or Name>