Introduction to Containers

Overview of Container Technology

Containers are one of the building blocks of cloud native computing. They are similar to, but much more lightweight than, earlier VMs such as those offered by VMware.

Containers are immutable, so if you need to make a change, you have to create a new container.

They comprise two basic elements:

• A container image is a lightweight, stand-alone, executable software package that includes everything an application needs to run: code, runtime, systems, tools, libraries and settings.
• Containerization involves a standard packaging format and an engine for running containers. Container images become containers at runtime when the container engine unpacks the application and runs it in a way that isolates the software from any other containers running on the same infrastructure.

By containing the application within an executable package, containers establish an operating environment that solves the frequent issue of “it works on my machine.”

Importance in Cloud Native Computing

Containers have transformed the way applications are created and deployed.

The portability and reliability provided by them is vital for DevOps methodologies like continuous integration and continuous deployment (CI/CD). Containers simplify the CI/CD process by enabling developers to construct, test and launch applications in an environment reducing mistakes. Containers also enhance resource utilization through tighter bin packing, which reduces both environmental impact and running cost.

Although they aren’t strictly speaking required in microservices environments they have become synonymous with them. This is because containerized applications are fast to start, and in microservices architectures, we start up and tear down systems frequently.

Therefore, as businesses increasingly embrace microservices and related cloud native technologies, containers play a role in promoting agile development and swift innovation. Their capacity to improve scalability, dependability and ease of maintenance positions them as key elements of modern software design.

History and Evolution of Containers

Early Container Technologies

Containers have been around in commercial software systems for over two decades. An early version of container technology was seen in FreeBSD jails, which emerged in the 2000s. These jails enabled the partition of the FreeBSD operating system into several independent mini-systems called jails, all sharing the same kernel with very little overhead.

Solaris Containers, a feature of Sun Microsystems’ Solaris OS, emerged at about the same time. A Solaris Container is based on a combination of system resource controls and the boundary separation provided by zones. Zones act as completely isolated virtual servers within a single operating system instance. They enable administrators to create virtualized OS environments within a Solaris instance, enhancing security and optimizing resource usage.

Introduction of Linux Containers (LXC)

In 2008, the concept of containers became a part of the Linux kernel, with the introduction of Linux Containers (LXC), an operating-system-level virtualization method for running multiple isolated Linux systems on a control host using a single Linux kernel. Initially developed by IBM, LXC relies on the Linux kernel cgroups functionality and support for isolated namespaces. This enabled applications to operate securely on the same physical hardware. Companies such as Google use LXC to oversee their infrastructure, demonstrating how containers can enhance resource management efficiency and scalability.

Emergence of Docker and Its Significance

LXC laid the groundwork for container technology, but it was the emergence of Docker in 2013 that really popularized containers, shifting them left from being tools primarily for system administrators to tools primarily for developers, and, with Microsoft’s help, expanding them to cover Windows servers as well as Linux and other Unix-derivatives.  Docker simplified the creation, deployment and management of containers, offering both a CLI and, by 2015 a GUI Interface called Kitematic, which the firm acquired.

By simplifying the complexities of LXC, Docker empowered developers to bundle their applications and dependencies into container images, ensuring performance across various setups.

The impact of Docker was significant. It streamlined the process of transitioning software from development to production without requiring rebuilding, effectively bridging the gap between development and operations. This paved the way for the wide-scale adoption of containers, which in turn drove the development of container orchestration solutions like Kubernetes and Docker Swarm.

Docker’s original open source philosophy, which means the Docker Engine is licensed under the Apache License 2.0, gave rise to initiatives such as runC, Containerd and the Moby Project, which pushed container technology ahead. Moreover, efforts to bolster container security and efficiency led to innovations such as Kata Containers.

Docker and other industry leaders also created an open governance structure for creating open industry standards around container formats and runtimes. Called the Open Container Initiative, or OCI, this currently maintains standards for runtime, image and distribution. Having an industry-standard container image format allows interoperability between multiple competing platforms.

What Is Containerization?

Definition and Basic Concepts

Containerization involves packaging an application with its dependencies into a container. Containers use the host OS kernel and segregate the application processes within their own environment. This streamlined approach enables containers to launch, halt and operate swiftly.

Differences Between Containers and Virtual Machines

Containers and virtual machines (VMs) offer environments for running applications. They vary in architecture and resource usage. VMs operate on hypervisors with a guest operating system, resulting in increased resource utilization. In contrast, containers share the host OS kernel, making them lighter and more efficient. This efficiency enables density and optimal use of computing resources.

Benefits of Containerization

The benefits of containerization are numerous.

• Portability: Containers can run consistently across different environments, making them ideal for multicloud and hybrid cloud strategies.
• Scalability: Containers can be easily scaled up or down to handle varying loads, enhancing application performance and resource utilization.
• Efficiency: By sharing the host OS kernel, containers reduce overhead and improve the density of applications running on a single host.
• Isolation: Containers provide process and resource isolation, enhancing security and stability by ensuring that issues in one container do not affect others.

Core Components of Container Technology

Container Engines

Container engines serve as the software that enables containers to operate on a host system. They oversee the life cycle of containers from their inception and deployment to scaling and eventual shutdown.

There are many container engines, including Docker, RKT, CRI-O, and LXD. In addition, many cloud providers, Platforms as a Service (PaaS), and container platforms have their own built-in container engines, which consume Docker or OCI-compliant container images.

Container Orchestration Tools

As containers started gaining traction, many people started looking at solutions for how to manage containers across multiple machines. Writing in “Building Microservices” Sam Newman noted that “Docker had two attempts at this (with Docker Swarm and Docker Swarm Mode, respectively); companies like Rancher and CoreOS came up with their own takes; and more general purpose platforms like Mesos were used to run containers alongside other sorts of workloads. Ultimately, though, despite a lot of effort on these products, Kubernetes has in the last couple of years come to dominate this space.”

Container Images and Registries

Container images are self-contained bundles that encompass all components to execute a software application, such as the code, runtime environment, libraries and setup files. These image packages can be shared via container repositories that act as storage hubs for container images.

• Docker Hub: Docker Hub is the most popular container registry, providing a vast library of pre-built images that can be pulled and used in Docker environments. It allows developers to share and distribute containerized applications easily.
• Google Container Registry: Google Container Registry is a private container image storage service on Google Cloud Platform, offering secure, high-performance image storage.
• Amazon Elastic Container Registry (ECR): Amazon ECR is a fully managed Docker container registry that makes it easy for developers to store, manage, and deploy Docker container images.

How Containers Work

Container life cycle: The container life cycle includes several stages: build, ship and run. During the build phase, a container image is created with all necessary dependencies. The image is then shipped to a registry where it can be accessed and pulled by other systems. Finally, during the run phase, the container engine executes the container based on the image.

Isolation and security: Containers employ techniques such as namespace isolation, which isolates process IDs, network interfaces, file systems and control groups, which manage resource allocation and limits. These mechanisms prevent unauthorized access, limit the impact of vulnerabilities and enhance overall system security.

Resource management: Containers share the host OS kernel but are restricted to their allocated resources, such as CPU, memory, and I/O. This efficient resource management allows for higher application density and better use of hardware compared to virtual machines.

Popular Container Technologies

Docker

Docker is the best-known container engine. Alongside the engine itself, Docker offers a suite of products including:

• Docker Desktop, which acts as a launchpad for container development.
• Docker Hub, the largest and most active registry of container images.
• Docker Scout, which provides insights on software supply chain vulnerabilities and company policy violations, from development to production.
• Build Cloud, which can dramatically speed up the building of containers.
• Docker Debug, which provides a built-in toolbox for developers working with containers.

Kubernetes, Cycle, Nomad and Tanzu Application Service

Kubernetes, created by Google, stands out as the platform for orchestrating containers. It handles tasks like deploying, resizing and overseeing applications in containers across host clusters. Kubernetes offers an adaptable system, with capabilities such as automated resource allocation, self-recovery mechanisms, discovering services and balancing loads. Its versatility and broad range of tools make it the preferred option for overseeing container setups. It does, however, have a reputation for complexity.

Of the current alternatives to Kubernetes, the main ones to consider are:

• Cycle: Sitting somewhere between a PaaS and an orchestrator, Cycle aims to simplify the management of containers. It doesn’t use Docker or Kubernetes, but it is OCI compliant, meaning the underlying containers are cross-compatible.
• HashiCorp’s Nomad: Deployed as a single binary, written in Go, it has a responsive community of maintainers on GitHub. Well-known users of the platform include Autodesk, Cloudflare and Roblox. It has a very flexible model for running different sorts of application workloads — including Java applications, virtual machines (VMs), Hadoop jobs and so on — and allows for a great deal of customization.
• VMware Tanzu Application Service: previously known as Pivotal Cloud Foundry (PCF), Tanzu Application Service is designed to run Microservice applications across clouds. It works on vSphere and all the major cloud providers and is particularly suited to .NET, Spring and Spring Boot-based applications.

Containerd

Containerd is a container runtime that handles all aspects of the container life cycle, such as transferring images, executing containers and managing storage. It is meant to be integrated into systems like Docker, offering features for container operation. Containerd follows the standards set by the Open Container Initiative (OCI) for runtimes and images, promoting consistency and uniformity among container technologies.

runc

runc is a lightweight, portable container runtime that directly implements the Open Container Initiative (OCI) runtime specification. It serves as the underlying runtime for Docker and Containerd, providing a standardized way to run containers. runc focuses on simplicity and performance, making it a critical component of modern container ecosystems.

Kata Containers

Kata Containers strives to merge the advantages of containers and virtual machines by offering virtualized containers with security and isolation. By using a hypervisor to operate each container in its virtual machine, Kata Containers guarantees robust isolation while maintaining the speed and effectiveness of containers. This method proves beneficial for executing workloads or bolstering security in shared environments.

Implementing Containers in Cloud Environments

Integration with Cloud Providers

Most major cloud providers offer curated Kubernetes experiences such as Azure Kubernetes Service (AKS), Amazon Elastic Kubernetes Service (EKS) or Google Kubernetes Engine (GKE). For on-prem workloads, a Kubernetes distribution such as Red Hat’s OpenShift or Tanzu Application Platform fulfills a similar purpose.

Hybrid and Multicloud Strategies

Containers are great for cloud approaches because they are easy to move around and maintain consistency across various settings. Companies can run applications in containers on-premises, in the cloud or across cloud services, without needing to make major changes. This adaptability makes it possible to use resources efficiently, save money and enhance resilience by steering off being tied down to a vendor and enabling smooth transitions between settings.

Serverless

Although typically thought of as an alternative to containers, FaaS/Serverless products such as Azure Functions, AWS Lambda or Google Cloud Functions, which offer a means of building distributed systems that arr delightfully simple, all rely on some sort of container technology under the hood.

Security Considerations

Security is a critical aspect of container implementation. Best practices include:

• Image access management: Restricting developers to using trusted sources for container images such as Docker official images, Docker Verified publisher images or your own corporate images, and regularly scanning them for vulnerabilities.
• Container isolation: An example would be techniques such as running all containers unprivileged through the Linux user namespace, vetting some critical system calls to prevent container escapes, and monitoring for suspicious activities.
• Network security: Ensuring secure communication between containers and isolating network traffic using tools like service meshes.

Future Trends in Container Technology

The impact of ML and AI

We expect to see the further democratization of container technology, making it easier to onboard junior developers who haven’t worked with them before. This will likely include specific tooling, for example using AI tools such as GitHub Copilot to help developers transact within GitHub, build files and execute.

The rise of AI also sees a shift to more remote workloads; while our laptops get ever more capable, the intense and specialist compute demands these projects involve mean it simply isn’t possible to run everything on a local machine. As a consequence, we are seeing a renewed push to facilitate remote building, testing and running of environments, but we need to be able to do this in a way that keeps the developer feedback loop fast and tight. We expect to see container tooling become truly hybrid, and it will likely also expand, with UI designed for data science professionals as well as software developers.

Further Abstractions

Serverless approaches, where the containerization is abstracted away to the point it is all but invisible to the developer, suggest the possibility that whilst containers and orchestrators will continue to be around, they may become less and less visible to typically enterprise developers.

Advancements in Container Security

With the rise of ever more sophisticated supply chain attacks, there is a growing emphasis on improving container security. Anticipated developments in the future involve enhancements in runtime security tools, automated scanning for vulnerabilities, robust methods for verifying the authenticity of container images, and support for fully air-gapped environments. These upgraded security measures aim to assist companies in safeguarding their containerized applications against emerging risks.

Enhanced Orchestration and Automation

The upcoming advancements in container orchestration are expected to center on enhancing the automation of managing containerized applications. This will involve implementing scheduling algorithms, optimizing resource allocation and enhancing integration with AI and machine learning for predictive scaling and anomaly detection. These improvements aim to streamline container orchestration processes, making them more effective and easing the workload on development and operations teams.

Learn More About Containers at The New Stack

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