Docker: Difference between revisions

Latest revision as of 17:43, 6 July 2025

Docker is an open-source platform designed to automate the deployment, scaling, and management of applications using containerization technology. It enables developers to package applications and their dependencies into a standardized unit called a container, which can then be run consistently across different computing environments. The primary advantage of Docker is its ability to facilitate the creation of lightweight, portable, and reproducible software environments, thereby streamlining the development lifecycle and enhancing operational efficiency.

History

Docker was initially released in March 2013 by Solomon Hykes as an internal project for a company called DotCloud, which later became known as Docker, Inc. The platform drew upon several existing technologies, most notably Linux Containers (LXC), which provided the foundational capabilities for container management. Docker’s introduction coincided with the rise of cloud computing, which highlighted the need for new approaches to application deployment and resource management.

By 2014, Docker gained significant traction in the developer community and the tech industry at large. The platform's popularity surged due to its simplicity, robust functionality, and the ability to integrate seamlessly with existing tools and workflows. The open-source nature of Docker allowed developers to contribute to its ecosystem, leading to rapid advancements and the introduction of features such as Docker Compose and Docker Swarm for orchestration and clustering.

In 2016, Docker launched the Docker Enterprise Edition (EE), a commercially supported version of the platform that included enhanced security features and management capabilities geared towards enterprise deployment. This release reflected Docker’s commitment to scaling its technology for larger organizations and integrating it with existing enterprise software infrastructures.

In recent years, Docker has become a core component of DevOps and cloud-native architectures, paving the way for microservices-based application designs and shifting how organizations approach application development and deployment across environments.

Architecture

Docker's architecture is comprised of several key components that work together to provide a comprehensive platform for container management.

Core Components

At the heart of Docker’s architecture is the Docker Engine, a client-server application that contains a server daemon, REST API, and a command-line interface (CLI):

The Docker daemon, or dockerd, is responsible for managing Docker containers, images, networks, and volumes. It handles commands received from the Docker CLI or REST API, performing the necessary actions to create, run, and manage containers.
The Docker client provides a user interface for developers to command the Docker daemon. This component allows for direct communication using commands such as `docker run`, `docker build`, and `docker pull`.
The REST API serves as an intermediary that enables programs and tools to interact with Docker. It allows other applications to automate Docker-related tasks programmatically.

Containerization

The principle of containerization lies at the core of Docker’s functionality, enabling applications to run in isolated environments. Containers share the same operating system kernel but are packaged with their own libraries, configuration files, and dependencies. This approach offers numerous advantages over traditional virtual machines, including reduced overhead, increased start-up speed, and greater resource efficiency.

Each container operates independently, which allows developers to test and deploy software in environments that closely mirror production settings without the risk of interference from other applications or processes running on the host system.

Docker Images

Docker images are the standalone, executable packages that include everything required to run a piece of software—including the code, runtime, system tools, libraries, and settings. Images serve as the blueprint for containers. They are built using a layered filesystem approach, where each instruction in the Dockerfile creates a new layer, making the images lightweight and efficient. When a container is created from an image, only the changes made to that container are saved as a new layer. This layering mechanism facilitates faster downloads, storage efficiency, and easier updates.

Docker Hub is the default registry where users can find and share container images. It contains a vast library of official images maintained by Docker, as well as private repositories for custom images.

Implementation

Docker can be implemented across various environments, from local development machines to large-scale production setups in cloud services. The process is generally straightforward, involving the installation of the Docker Engine, the configuration of container images, and orchestration for managing multiple containers.

Local Development

For local development, Docker enables developers to create isolated environments for testing code without polluting their development setups. By running applications in containers, developers can ensure consistent behavior across different environments. This is particularly beneficial when working on systems that have differing dependencies or configurations.

Developers can utilize Docker Compose, a tool for defining and running multi-container applications. By specifying configurations in a docker-compose.yml file, teams can automate the building and provisioning of entire application stacks, making it easier to manage complex application architectures.

Continuous Integration and Continuous Deployment (CI/CD)

Docker plays a critical role in modern CI/CD workflows. Many CI/CD tools, such as Jenkins, GitLab CI, and CircleCI, support Docker natively, allowing developers to build, test, and deploy applications in an automated fashion. This integration allows for consistent testing environments, thereby reducing the likelihood of issues arising from discrepancies between testing and production environments.

Additionally, containers can be used to run integration tests, ensuring that software components function as expected before deployment. As a result, organizations that use Docker as part of their CI/CD pipelines benefit from faster feedback loops and higher software quality.

Orchestration

As applications grow in complexity and scale, managing multiple containers becomes a necessity. Container orchestration platforms, such as Kubernetes, Docker Swarm, and Apache Mesos, provide the tools required for deploying and managing clusters of containers across a distributed environment. These platforms enable automated load balancing, service discovery, scaling, and self-healing features, which are essential for maintaining high availability and optimal performance in production systems.

Docker Swarm is integrated into Docker and provides native orchestration capabilities, allowing users to create and manage a swarm of Docker nodes easily. Kubernetes, on the other hand, has become the de facto standard for container orchestration, offering extensions and robust community support for more complex deployments.

Applications

Docker's versatility lends itself to a wide variety of applications across diverse industries, transforming traditional software development and deployment methodologies.

Microservices Architecture

One of the most significant applications of Docker is in the implementation of microservices architectures. In a microservices framework, applications are decomposed into smaller, independent services, each responsible for a specific function. Docker containers provide an ideal environment for deploying these services, facilitating rapid iteration and deployment of individual components without affecting the entire application. This modularity results in improved scalability, maintainability, and ease of updates.

DevOps Practices

Docker is a cornerstone of the DevOps movement, which seeks to unify software development and IT operations. By leveraging Docker, organizations can increase collaboration between development and operations teams, enable better communication, and streamline processes. Automated container deployments simplify the management of production environments and allow for continuous monitoring and feedback, improving the reliability and speed of software delivery.

Cloud Computing

The rise of cloud computing has further propelled Docker's adoption, as organizations migrate their operations to cloud-based platforms. Solutions offered by major cloud providers, such as AWS, Microsoft Azure, and Google Cloud Platform, facilitate the deployment and management of Docker containers at scale. These platforms provide services that simplify container orchestration, storage, and networking, making it easier for organizations to integrate Docker into their cloud environments.

Docker's lightweight nature and portability ensure that applications can be run in any cloud environment, offering valuable flexibility for organizations to choose their infrastructure without vendor lock-in.

Criticism

Despite its popularity and numerous advantages, Docker has faced criticism and limitations that organizations must consider when integrating container technology into their workflows.

Security Concerns

One of the primary concerns with Docker containers is their security implications. As containers share the host operating system kernel, vulnerabilities in that kernel can expose all containers to potential threats. Additionally, containers often run with elevated privileges, which can increase the risk of unauthorized access or abuse.

To mitigate these concerns, best practices must be followed, including using minimal base images, regularly updating containers with security patches, and implementing strict access controls. Organizations must also consider employing specialized tools for container security, such as image scanning and runtime protection solutions.

Performance Overhead

Although containers generally offer better performance than traditional virtualization solutions, there can still be performance overhead associated with running multiple containerized applications. Resource contention can occur when multiple containers compete for limited CPU, memory, and I/O resources, potentially leading to degraded application performance. Proper monitoring and resource management strategies are essential to address these issues and ensure optimal operation of containerized environments.

Complexity in Management

While Docker provides substantial benefits in terms of agility and scalability, the management of containerized environments—especially at scale—can become complex. The introduction of orchestration tools can add layers of complexity, requiring organizations to invest time and resources in learning and maintaining these systems. Inadequate knowledge and experience can hinder effective implementation, and organizations may need to seek dedicated training for their staff to maximize the value of Docker technologies.

Conclusion

Docker has transformed the landscape of application development and deployment by providing powerful tools for containerization and orchestration. Its advantages, including portability, consistency, and efficiency, have made it a vital component of modern software practices. Although challenges remain, particularly in areas such as security and management, the continued evolution of the Docker ecosystem reflects the growing importance of container technologies in an increasingly cloud-centric and DevOps-oriented world.

References

@@ Line 1: / Line 1: @@
-'''Docker''' is an open-source platform that automates the deployment, scaling, and management of applications within lightweight, portable containers. It leverages containerization technology to allow developers to package applications and their dependencies into a standardized unit called a container. This encapsulation provides numerous benefits, including consistency across different computing environments, ease of deployment, and improved resource utilization.
+'''Docker''' is an open-source platform designed to automate the deployment, scaling, and management of applications using containerization technology. It enables developers to package applications and their dependencies into a standardized unit called a container, which can then be run consistently across different computing environments. The primary advantage of Docker is its ability to facilitate the creation of lightweight, portable, and reproducible software environments, thereby streamlining the development lifecycle and enhancing operational efficiency.
 == History ==
-Docker was initially developed by Solomon Hykes as an internal project at dotCloud, a platform-as-a-service company, in 2010. The first release of Docker was in March 2013, with the core idea revolving around simplifying the deployment process and creating standardized environments for applications. The project quickly gained immense popularity due to its ability to solve many problems associated with traditional virtualization, such as resource overhead and deployment complexity.
+Docker was initially released in March 2013 by Solomon Hykes as an internal project for a company called DotCloud, which later became known as Docker, Inc. The platform drew upon several existing technologies, most notably Linux Containers (LXC), which provided the foundational capabilities for container management. Docker’s introduction coincided with the rise of cloud computing, which highlighted the need for new approaches to application deployment and resource management.
-By 2014, Docker had transitioned into a standalone company, with Hykes serving as its CTO. The expansion of Docker's functionality continued, leading to the introduction of Docker Compose for defining multi-container applications in a declarative manner, and Docker Swarm for orchestrating clusters of Docker containers. As the community grew, Docker began to adopt and promote standards for container images, and in 2015, the Open Container Initiative (OCI) was formed to establish common standards for container formats and runtimes.
+By 2014, Docker gained significant traction in the developer community and the tech industry at large. The platform's popularity surged due to its simplicity, robust functionality, and the ability to integrate seamlessly with existing tools and workflows. The open-source nature of Docker allowed developers to contribute to its ecosystem, leading to rapid advancements and the introduction of features such as Docker Compose and Docker Swarm for orchestration and clustering.
-As of 2023, Docker has established itself as a cornerstone of modern software development practices, particularly in the realms of DevOps and microservices architecture. It has been instrumental in the adoption of Continuous Integration and Continuous Deployment (CI/CD) pipelines across various industries.
+In 2016, Docker launched the Docker Enterprise Edition (EE), a commercially supported version of the platform that included enhanced security features and management capabilities geared towards enterprise deployment. This release reflected Docker’s commitment to scaling its technology for larger organizations and integrating it with existing enterprise software infrastructures.
+In recent years, Docker has become a core component of DevOps and cloud-native architectures, paving the way for microservices-based application designs and shifting how organizations approach application development and deployment across environments.
 == Architecture ==
-Docker’s architecture is typically composed of three primary components: the Docker daemon, Docker client, and Docker registry. Each of these plays a crucial role in the overall functioning of the platform.
+Docker's architecture is comprised of several key components that work together to provide a comprehensive platform for container management.
+=== Core Components ===
+At the heart of Docker’s architecture is the Docker Engine, a client-server application that contains a server daemon, REST API, and a command-line interface (CLI):
+* The Docker daemon, or ''dockerd'', is responsible for managing Docker containers, images, networks, and volumes. It handles commands received from the Docker CLI or REST API, performing the necessary actions to create, run, and manage containers.
+* The Docker client provides a user interface for developers to command the Docker daemon. This component allows for direct communication using commands such as `docker run`, `docker build`, and `docker pull`.
+* The REST API serves as an intermediary that enables programs and tools to interact with Docker. It allows other applications to automate Docker-related tasks programmatically.
-=== Docker Daemon ===
+=== Containerization ===
-The Docker daemon, also referred to as `dockerd`, is responsible for managing Docker containers. It handles all interactions with containers, images, networks, and volumes. The daemon listens for API requests from the Docker client and runs as a background process on the host operating system. It is critical for handling the lifecycle of containers, which includes creating, starting, stopping, and deleting them. The daemon can also communicate with other Docker daemons to manage multi-host container deployment and orchestration.
+The principle of containerization lies at the core of Docker’s functionality, enabling applications to run in isolated environments. Containers share the same operating system kernel but are packaged with their own libraries, configuration files, and dependencies. This approach offers numerous advantages over traditional virtual machines, including reduced overhead, increased start-up speed, and greater resource efficiency.
-=== Docker Client ===
+Each container operates independently, which allows developers to test and deploy software in environments that closely mirror production settings without the risk of interference from other applications or processes running on the host system.
-The Docker client is the primary interface through which users interact with Docker. It can be run from a command-line interface or via graphical interfaces provided by third-party tools. The client communicates with the Docker daemon using the Docker API, allowing users to execute commands such as `docker run`, `docker pull`, and `docker build`. The client can be run on the same host as the daemon or on remote systems, facilitating remote management of Docker containers.
+=== Docker Images ===
-=== Docker Registry ===
+Docker images are the standalone, executable packages that include everything required to run a piece of software—including the code, runtime, system tools, libraries, and settings. Images serve as the blueprint for containers. They are built using a layered filesystem approach, where each instruction in the Dockerfile creates a new layer, making the images lightweight and efficient. When a container is created from an image, only the changes made to that container are saved as a new layer. This layering mechanism facilitates faster downloads, storage efficiency, and easier updates.
-Docker Registry is a storage and distribution system for Docker images. When a user builds an image, they can push it to a registry for storage and later retrieval. The most widely used public registry is Docker Hub, which hosts a vast collection of pre-built images available for use. Organizations can also set up private registries to store proprietary images securely. Docker registries enable version control and sharing of container images efficiently across teams and environments.
+Docker Hub is the default registry where users can find and share container images. It contains a vast library of official images maintained by Docker, as well as private repositories for custom images.
 == Implementation ==
-The implementation of Docker is made simple through its command-line interface and various APIs, allowing for straightforward integration into existing workflows. The combination of Docker Engine, CLI tools, and various orchestration frameworks allows developers to create, manage, and scale containerized applications easily.
+Docker can be implemented across various environments, from local development machines to large-scale production setups in cloud services. The process is generally straightforward, involving the installation of the Docker Engine, the configuration of container images, and orchestration for managing multiple containers.
-=== Installing Docker ===
-Docker can be installed on various operating systems, including Linux, macOS, and Windows. The installation process may differ slightly depending on the host OS. Typically, users download the Docker Desktop application or install the Docker Engine using package management systems available for their operating systems. Following installation, users can verify the setup by running the `docker --version` command to confirm that Docker is functioning as expected.
+=== Local Development ===
-=== Creating Container Images ===
+For local development, Docker enables developers to create isolated environments for testing code without polluting their development setups. By running applications in containers, developers can ensure consistent behavior across different environments. This is particularly beneficial when working on systems that have differing dependencies or configurations.
-Creating container images involves writing a `Dockerfile`, which contains a set of instructions for building an image. Instructions typically specify a base image, required files, environment variables, and command execution. Once the `Dockerfile` is defined, users can build images using the `docker build` command, specifying the Docker context from which the image will be built. The resulting images can then be run as containers.
+Developers can utilize Docker Compose, a tool for defining and running multi-container applications. By specifying configurations in a ''docker-compose.yml'' file, teams can automate the building and provisioning of entire application stacks, making it easier to manage complex application architectures.
-=== Running Containers ===
+=== Continuous Integration and Continuous Deployment (CI/CD) ===
-Running containers is achieved with the `docker run` command, which allows users to execute a container from a specified image. The command supports various options to manage the container's behavior, such as mapping ports, mounting volumes, and assigning environment variables. Once a container is launched, it can be accessed through specified ports or integrated with other services.
+Docker plays a critical role in modern CI/CD workflows. Many CI/CD tools, such as Jenkins, GitLab CI, and CircleCI, support Docker natively, allowing developers to build, test, and deploy applications in an automated fashion. This integration allows for consistent testing environments, thereby reducing the likelihood of issues arising from discrepancies between testing and production environments.
-=== Orchestration and Scaling ===
+Additionally, containers can be used to run integration tests, ensuring that software components function as expected before deployment. As a result, organizations that use Docker as part of their CI/CD pipelines benefit from faster feedback loops and higher software quality.
-While Docker makes it easy to create and run containers, managing a large number of containers across different hosts can be challenging. To address this, Docker Swarm and Kubernetes emerged as popular orchestration tools.
+=== Orchestration ===
-Docker Swarm is integrated directly into the Docker Engine, allowing users to set up a cluster of Docker nodes and deploy scaled applications across them. Swarm mode introduces concepts such as services, replicas, and load balancing, making distributed applications easier to manage.
+As applications grow in complexity and scale, managing multiple containers becomes a necessity. Container orchestration platforms, such as Kubernetes, Docker Swarm, and Apache Mesos, provide the tools required for deploying and managing clusters of containers across a distributed environment. These platforms enable automated load balancing, service discovery, scaling, and self-healing features, which are essential for maintaining high availability and optimal performance in production systems.
-Kubernetes, on the other hand, is an open-source container orchestration platform that provides a more extensive set of features. Although initially developed by Google, it has become a widely adopted standard for orchestrating containerized applications. Kubernetes supports scaling, self-healing, service discovery, and rolling updates, making it a popular choice for managing container workloads in production environments.
+Docker Swarm is integrated into Docker and provides native orchestration capabilities, allowing users to create and manage a swarm of Docker nodes easily. Kubernetes, on the other hand, has become the de facto standard for container orchestration, offering extensions and robust community support for more complex deployments.
 == Applications ==
-Docker has found widespread applications across various sectors and in numerous development strategies. Organizations leverage Docker to simplify and accelerate their software development processes. Some of the most common applications include:
+Docker's versatility lends itself to a wide variety of applications across diverse industries, transforming traditional software development and deployment methodologies.
 === Microservices Architecture ===
-In a microservices architecture, applications are broken down into smaller, independent services that can be developed, deployed, and scaled independently. Docker is particularly well-suited to this approach, as it allows developers to encapsulate each microservice in its own container, ensuring that dependencies and configurations are isolated. This practice enhances the agility of development teams, enabling faster iterations and more manageable deployments.
+One of the most significant applications of Docker is in the implementation of microservices architectures. In a microservices framework, applications are decomposed into smaller, independent services, each responsible for a specific function. Docker containers provide an ideal environment for deploying these services, facilitating rapid iteration and deployment of individual components without affecting the entire application. This modularity results in improved scalability, maintainability, and ease of updates.
-=== Continuous Integration/Continuous Deployment (CI/CD) ===
+=== DevOps Practices ===
-Docker plays a crucial role in CI/CD pipelines by providing a consistent environment for build, testing, and deployment phases. CI/CD tools such as Jenkins, GitLab CI/CD, and CircleCI integrate seamlessly with Docker, allowing automated testing of containerized applications. This consistency ensures that applications behave the same in development, testing, and production environments, thus reducing "it works on my machine" issues. By utilizing Docker, developers can streamline the release process and quickly deliver new features and fixes to users.
+Docker is a cornerstone of the DevOps movement, which seeks to unify software development and IT operations. By leveraging Docker, organizations can increase collaboration between development and operations teams, enable better communication, and streamline processes. Automated container deployments simplify the management of production environments and allow for continuous monitoring and feedback, improving the reliability and speed of software delivery.
-=== Development and Testing Environments ===
+=== Cloud Computing ===
-Docker significantly eases the process of setting up development and testing environments. Developers can create containers that mirror the production environment closely, leading to more reliable testing outcomes. They can quickly spin up or tear down instances of services and applications, allowing for experimentation without risking changes to the underlying infrastructure.
+The rise of cloud computing has further propelled Docker's adoption, as organizations migrate their operations to cloud-based platforms. Solutions offered by major cloud providers, such as AWS, Microsoft Azure, and Google Cloud Platform, facilitate the deployment and management of Docker containers at scale. These platforms provide services that simplify container orchestration, storage, and networking, making it easier for organizations to integrate Docker into their cloud environments.
-=== Hybrid and Multi-cloud Deployments ===
+Docker's lightweight nature and portability ensure that applications can be run in any cloud environment, offering valuable flexibility for organizations to choose their infrastructure without vendor lock-in.
-Docker's portability allows organizations to deploy applications across various cloud providers or hybrid environments seamlessly. As a result, organizations can avoid vendor lock-in, utilizing the best features offered by different platforms. For instance, a company could deploy its application on both AWS and Google Cloud based on specific requirements, benefiting from the elasticity and scalability of both platforms.
+== Criticism ==
-== Criticism and Limitations ==
+Despite its popularity and numerous advantages, Docker has faced criticism and limitations that organizations must consider when integrating container technology into their workflows.
-Despite its myriad advantages, Docker has faced some criticism and limitations that have been debated within the tech community.
 === Security Concerns ===
-One major criticism of Docker stems from security. Given that containers share the host OS kernel, a vulnerability in one container can potentially impact others. Therefore, application isolation is less stringent compared to traditional virtual machines. Although improvements have been made in container security, such as the introduction of user namespaces and security profiles, organizations must implement strict policies and practices, routinely scanning images for vulnerabilities and ensuring that containers run with the least privilege principle.
+One of the primary concerns with Docker containers is their security implications. As containers share the host operating system kernel, vulnerabilities in that kernel can expose all containers to potential threats. Additionally, containers often run with elevated privileges, which can increase the risk of unauthorized access or abuse.
-=== Complexity and Learning Curve ===
-Novice users may encounter a steep learning curve when adopting Docker, especially when integrating it with other tools and workflows. Understanding how Docker containers work, how to write effective `Dockerfile` scripts, and navigating orchestration tools can be demanding. Furthermore, teams accustomed to monolithic application architectures may find it challenging to adapt to the microservices paradigm and the associated complexities.
-=== Resource Overhead ===
-While containers are generally more lightweight than traditional virtual machines, they still consume resources on the host machine. Running many containers on a single host can lead to resource contention, especially if not adequately managed. Organizations must monitor resource usage and apply limits on CPU and memory consumption for individual containers to maintain optimal performance.
-== Real-world Examples ==
-Many organizations, from startups to Fortune 500 companies, leverage Docker to enhance their development and deployment processes. A few notable examples include:
+To mitigate these concerns, best practices must be followed, including using minimal base images, regularly updating containers with security patches, and implementing strict access controls. Organizations must also consider employing specialized tools for container security, such as image scanning and runtime protection solutions.
-=== Google ===
+=== Performance Overhead ===
-Google adopted containerization early on and developed Kubernetes, which has become the industry standard for orchestrating Docker containers. Google itself utilizes Docker to manage its internal applications and services, benefiting from the scalability and portability that containerization offers.
+Although containers generally offer better performance than traditional virtualization solutions, there can still be performance overhead associated with running multiple containerized applications. Resource contention can occur when multiple containers compete for limited CPU, memory, and I/O resources, potentially leading to degraded application performance. Proper monitoring and resource management strategies are essential to address these issues and ensure optimal operation of containerized environments.
-=== Netflix ===
+=== Complexity in Management ===
-Netflix uses Docker to manage its microservices architecture, enabling the company to deploy thousands of microservices at scale. The ability to consistently and reliably deploy applications in transient environments has been pivotal in maintaining Netflix's seamless streaming service.
+While Docker provides substantial benefits in terms of agility and scalability, the management of containerized environments—especially at scale—can become complex. The introduction of orchestration tools can add layers of complexity, requiring organizations to invest time and resources in learning and maintaining these systems. Inadequate knowledge and experience can hinder effective implementation, and organizations may need to seek dedicated training for their staff to maximize the value of Docker technologies.
-=== IBM ===
+== Conclusion ==
-IBM has integrated Docker into its services and offerings, promoting hybrid cloud environments that utilize containerization. Docker provides IBM clients with flexibility and consistency for their applications, especially when transitioning between on-premise and cloud environments.
+Docker has transformed the landscape of application development and deployment by providing powerful tools for containerization and orchestration. Its advantages, including portability, consistency, and efficiency, have made it a vital component of modern software practices. Although challenges remain, particularly in areas such as security and management, the continued evolution of the Docker ecosystem reflects the growing importance of container technologies in an increasingly cloud-centric and DevOps-oriented world.
 == See also ==
-* [[Containerization]]
+* [[Container (virtualization)]]
+* [[Microservices]]
 * [[Kubernetes]]
-* [[Microservices]]
-* [[Virtualization]]
 * [[DevOps]]
-* [[CI/CD]]
+* [[Continuous Integration]]
 == References ==
-* [https://www.docker.com Docker Official Website]
+* [https://www.docker.com Docker Official Site]
 * [https://docs.docker.com Docker Documentation]
-* [https://kubernetes.io Kubernetes Official Site]
+* [https://hub.docker.com Docker Hub]
-* [https://www.oracle.com/cloud/what-is-containerization.html Oracle Containerization Overview]
-* [https://www.opencontainers.org Open Container Initiative]
 [[Category:Software]]
-[[Category:Virtualization]]
+[[Category:DevOps]]
-[[Category:Containers]]
+[[Category:Containerization]]