A container is a tool that can standardize the packaging and deployment of software applications. Containers create portable and self-contained environments isolated from the rest of the system. This enables an application with all essential dependencies to be bundled and distributed as a single package.
With how ubiquitous Docker has become in software development, many assume containerization started with Docker. However, this isn’t the case.
The concept of containers was introduced as early as 1979 with the creation of chroot, a command that changes the root directory on Unix OSes. chroot made the root directory for the process different from the actual root. This was helpful for builds because it enabled developers to isolate the builds from the file system, ensuring they had all the build dependencies and providing better build dependency allocation.
The chroot system call was quite popular until 2002, when FreeBSD jails came about. FreeBSD jails enabled developers to assign IP addresses to the jails, further supporting the development of a container ecosystem.
In 2006, Google released process containers, a feature designed to limit the number of resources these file systems could allocate. Later, in the 2.6.24 kernel, these process containers were merged into the Linux kernel as control groups (cgroups) — Google’s early attempt at containers.
It wasn’t until 2008 that the first fully-fledged containers that required no patching of the Linux kernel became available. LXC, the name of the initial implementation, used both cgroups and Linux namespaces to isolate workgroups.
In 2011, Warden was released. Let Me Contain That For You (LMCTFY) followed in 2013 just before Docker’s release that same year.
Today, many containerization platforms are available on the market. However, Docker is the most popular choice among developers, largely because of how easy it is to use.
Containers are an application-layer abstraction separated from the host OS. Instead of providing its own OS, each container shares the OS’s kernel with other containers, and the underlying OS has limited resources accessible. A containerized application can operate on several types of infrastructure, including the cloud, virtual machines (VMs), bare metal, and others, without changing the program for each IT environment. Additionally, one machine can run multiple containers.
The foundation of containerization is container images. Container image files can be full, static, and executable representations of an application or service, depending on the technology. Each image has a readable layer written on top of static, unchangeable layers. And, because each container has a unique layer that customizes that particular container, the underlying image layers may be stored and reused in several containers.
While the container engine runs images, you can use a container scheduler alongside or instead of an orchestration platform, like Kubernetes, to handle deployments. Containers provide a high degree of mobility since each image supplies the requirements necessary to run the code in a container.
To work, container images must have an image specification and runtime. Runtime requirements, files comprising all essential data for performance and runtimes, describe the behavior of a file system bundle.
An application or a microservice can be packaged into a container image and subsequently deployed for use in the container platform. A container platform is a client-server software that facilitates the container’s execution—in other words, a containerization tool like Docker. The container platform provides three important components:
Containers address the issue of preserving an application’s dependability when it’s transferred between different computing environments. Say, for example, you build an application locally, using a specific local version of a dependency. If you deploy that application on a server with a different version of that dependency, you could experience application downtime, loss of data, or other issues.
Since containers contain the application’s runtime environment, its dependencies, other binaries, and libraries in one package, containers encourage consistent application behavior regardless of the OS or underlying infrastructure differences.
Containers provide flexibility in building, testing, and deploying your applications across environments. Other benefits include:
With containers, applications are bundled with everything they need to run, making it easy to move or run them anywhere.
Since containers don’t include OS images and share the machine’s OS kernel, they use fewer system resources than VM environments, reducing overhead.
Because the environment is self-contained, it will run the same anywhere, increasing application consistency and effectiveness.
Deployments and rollbacks are more efficient due to image immutability. Additionally, this enables you to focus on managing your applications instead of infrastructure.
When operating within a container, a program operates in its own isolated environment and can’t impact other running applications unless you specifically enable it to do so. This isolation improves security and minimizes the potential attack surface.
As event-driven architecture and serverless computing become more popular, the need for containers that can be deployed quickly and easily to the edge of the network is becoming more important. A new type of container called an edge container was created to address these demands.
Edge containers are set up at the edge of a network, physically closer to users or devices, to reduce latency and improve availability. They provide many advantages over other types of containers because, unlike those used in cloud computing, they don’t run in regional locations like data centers. Moreover, they can be deployed swiftly, are significantly lighter, have increased security, and are more resilient to network disturbances.
Applications that must run close to the network’s edge can access computational resources from edge containers. Additionally, distributed applications can perform better with edge containers. Edge containers also benefit applications that need to swiftly react to network changes and those that gather data from non-networked devices.
The term “edge container” is often used interchangeably with other types of edge computing solutions, but edge containers aren’t the same. While edge computing is principally similar to edge containers, the latter offers benefits of containerization, such as portability and ease of use, while still being able to deploy your application on any device with an edge gateway. Other edge computing solutions may be limited to a specific gateway or device.
With containers gaining popularity, lots of organizations and businesses are adopting them. Here are some common ways these organizations use containers.
Organizations are switching from monolithic applications to microservices. These microservices have isolated workload environments thanks to containers simplifying the process of scaling a microservice architecture.
Containers can distribute applications across different cloud environments on-premises, to the cloud, and vice-versa due to their portability. They also make deploying to a cloud environment from an on-premises environment easy.
Containers offer a convenient approach to creating and testing programs, which boosts developer productivity. You can execute an application from your laptop without hosting it on the main OS if you’re in the early stages of development and want to test a version.
Providing a perfect testing environment is unnecessary. Rather, to test the application, you can spin up a container with the necessary dependencies. When environment setup and debugging are less of a concern, developers can focus on new product features instead.
Containers make application building, testing, and deployments easier, simplifying the implementation and automation of CI/CD pipelines for DevOps teams.
