Software development companies are increasingly seeking environments that are predictable, isolated and repeatable. Achieving this without compromising the software code’s consistency in all developer systems within the app infrastructure requires advanced technology. Luckily there is one: containerization.
Containerization is a growing trend in almost all industries. Indeed all signs indicate that the majority of IT experts around the world are accelerating the use of containers. Their goals include:
- Reducing IT costs.
- Increasing automation.
- Speeding up deployment cycles.
- Building and testing artificial intelligence (AI) models and apps.
But what is containerization? This article will discuss containerization, types plus uses.
What is containerization
Containerization is a process of packaging software so that it can be run independently from its operating environment. This enables the software to be developed on any platform, regardless of whether it is a physical server or virtual machine. Containerization has become increasingly popular in recent years as it offers huge benefits over traditional virtualization techniques.
Containerization provides a higher level of isolation as each container only has access to the resources that have been specifically allocated to it. This makes it more difficult for malware or other malicious code to spread between containers. In addition, containerized applications can be quickly deployed and updated, as there is no need to install or configure a separate virtual machine for each application.
Containerization can also help to reduce costs, as multiple containerized applications can be run on the same physical server or virtual machine. This makes efficient use of resources and can help to reduce the overall cost of ownership. It’s no wonder then that containers have become the standard unit of today’s cloud-native applications.
If we were to single out one reason that is making containerization so much popular, it has to be the fact that this technology enables developers to build and deploy applications more securely and faster. With traditional approaches, code has to be completed in a specific computing environment, else it often results in errors and bugs when transferred to a new location.
Running containers on the other hand eliminates errors and bugs by bundling the software code with the related libraries, configuration files, and dependencies needed to run the code. The single software package, the container, is separate from the host operating system. It becomes a stand-alone ecosystem and offers a portable computing environment capable of running across various platforms without any issue.
More companies getting in
Though the concept of containerization is decades old, the emergence of the Docker Engine in 2013 increased the adoption of this technology. Today, companies use containerization increasingly to not only build new apps but also modernize existing ones for the cloud.
Containers use the same shared operating system kernel and don’t need the computing resources of an OS within each application. This is why they are referred to as lightweight. They inherently have a smaller capacity than virtual machines, which makes them need less start-time and enables more containers to run on similar computing resources as a single VM. As a result, containers enhance server efficiency and reduce server plus licensing costs.
The main types of containerization and uses
The following are the main approaches to containerization for custom apps developed using distributed technologies.
1. Server consolidation
Server consolidation is a type of containerization where multiple server instances are run on a single server. This can provide a number of benefits, including reducing server costs, improving server utilization, and simplifying server management. There are a few different ways to achieve server consolidation, including blade servers, and server clustering.
Since containers don’t have multiple operating system memory footprints; they can use shared memory and other computing resources across the instances, which delivers dense consolidation possibilities.
By containerizing microservices, developers can create complex applications with decoupled processes that can handle an infinite number of scenarios. Containers result in much wider data functionalities where microservices work together to develop new services and applications.
For instance, eBay started its operations with a monolithic application in 1995. Down the line, various issues began popping up, forcing eBay to develop a set of microservices written in several programming languages. The development team uses Docker and Kubernetes to build and test containers. Today, eBay’s integration infrastructure is entirely container-dependent, with over 1,000 microservices.
3. Containers and Internet of Things (IoT)
ManyIoT software development companies are now using containers. By packaging their code into containers, they can easily deploy their applications on IoT devices with limited resources. The ability of containers to isolate each application from the others makes it easier to manage the complex network of interconnected devices that is typical of an IoT system.
There is also the advantage of most IoT applications requiring minimal processing power, meaning they can run even much more effectively in containers. You can bundle sensor-specific libraries with the app in a container to provide app portability across IoT devices.
For example, Lindsay Corporation had issues with legacy infrastructure and applications, mainly older Windows servers that could not support its IoT vision. However, with containerization and adoption of Docker, Azure, and edge computing, Lindsay migrated its servers and applications to the cloud environment. Docker enabled the corporation to connect over 450,000 IoT-enabled irrigation systems worldwide and save more than 700 billion gallons of water.
4. Multi-Tenancy and Containers as a Service (CaaS)
CaaS is a type of container-based virtualization that allows providers to deliver container engines, orchestration, and other computing resources as a cloud service. This approach increases agility and simplifies the development process.
Multi-tenancy allows a single software instance to serve a group of end-users in a single tenancy. As a result, the provider can automate the development process of any containerized app, reducing the deployment time and offering convenient maintenance.
For example, Pinterest migrated its platform to containerized technology to manage the growing workload and resolve operational issues. However, migrating the infrastructure was challenging because of the scale and complexity. Pinterest decided on a phased approach. They also built a multi-tenant cluster with a unified interface for long-running batch jobs and services.
5. Hybrid and multi-cloud approaches
Businesses, from global enterprises to startups, understand the agility, operational efficiency, and cost savings a hybrid cloud approach offers. This is why most organizations are considering a hybrid and multi-cloud strategy with containers for everything from app development and hosting to disaster recovery.
Based on multi-cloud management best practices, users use this pairing to capitalize on the flexibility of multiple cloud infrastructures and programming languages. Another benefit is the versatility of hosting workloads in public clouds, on-premise, or within managed infrastructures.
Types of containerization technology
Though Docker is one of the most popular containers, it is critical for developers to understand the types of container options available, given the expansion and growth they have had in recent years.
Some of the popular types of containers include:
Docker is an open-source containerized platform and one of the most widely used. It combines the app’s source code with the existing operating system as well as its respective dependencies and libraries. Docker allows the software code to run in any computing environment, making it more versatile.
One of the emerging best practices is using Docker and Kubernetes, a container orchestration technology. Integrating them creates an isolation mechanism, allowing you to augment container resources effectively.
LXC is an open-source platform from LinuxContainers.org. This container aims to offer isolated application environments similar to virtual machines but with the benefit of running on a shared operating system kernel.
LXC follows the Unix processing model, which has no central daemon. The model allows each container to behave like it is managed by a separate program instead of one central program.
LXC works in different ways from Docker. For instance, an LXC container lets you run more than one process, while Docker is designed so that it is better to run a single operation in each container.
CRI-O is also an open-source platform and an implementation of the Kubernetes Container Runtime Interface (CRI) to allow the use of Open Container Initiative (OCI) compatible runtimes. It aims at replacing Docker as Kubernetes’ container engine.
CRI-O lets Kubernetes use any OCI-compliant container runtime to run pods. It supports Kata and runC container runtimes.
rkt containers, also referred to as ‘Rocket,’ emerged from CoreOS as a solution to the security vulnerabilities in the earlier versions of Docker. These containers have a set of supported tools and a strong community to rival Docker.
In 2014, CoreOS established the App Container Specification to drive innovation in the container space. This move later produced several open-source projects.
rkt is similar to LXC in not using a central daemon. As a result, the platform offers more precise control over containers at an elemental container level.
The key drawback of rkt containers is that they don’t provide complete end-to-end solutions. You must use them with other technologies or as substitutes for specific elements of the Docker system.
runC is a lightweight, universal container runtime that was initially a low-level Docker component and worked under the hood, integrated within the platform architecture. But, it has since been established as a standalone modular tool.
The goal behind the release was to enhance the portability of containers. runC offers a standardized open-source container runtime that works independently of Docker in other container systems. However, it can also work as part of Docker.
Because of the rising popularity of containerization, Open Container Initiative (OCI) decided to minimize the specifications and standards of container technology. Thus, companies have broader choices to select from this wide variety of open-sourced container engines available today.
Types of container orchestration technology
A single application can have numerous containers, and they could be in thousands in the case of microservices-based applications. It isn't easy to manage these containers manually. This is where orchestration comes in.
Container orchestration is the automation of the containerization process, including the deployment, scaling, management, and networking of containers.
The role of container orchestration platforms and tools is to manage distributed, containerized apps at a massive scale. Developers use container orchestration to control, schedule, and coordinate various elements' activities, distribute updates, monitor health, and institute recovery processes. Some container orchestration tools wrap containers into structures known as pods. Computers within the same pod share computing resources while maintaining isolation from those in other pods. Pods also enable scaling containerized apps as a unit.
A node is a single machine and the smallest commuting hardware unit a pod runs on. Several nodes bring resources together to form a master machine, known as a cluster.
Here are the top three types of container orchestrators.
Kubernetes is a popular orchestration tool that supports declarative automation and configuration. Google originally developed and handed it over to the Cloud Native Computing Foundation.
This platform uses YAML and JSON files to orchestrate containers and introduces the notion of clusters, nodes, and pods.
2. Docker Swarm
Docker Swarm is a fully integrated container orchestration platform for packaging and running containerized apps. It’s not only helpful in deploying apps as containers but also in locating container images in other hosts.
Docker Swarm came in 2003, almost a decade before Kubernetes. It popularized orchestrating containers for companies that sought to move away from virtual machines. Furthermore, it is ideal for smaller applications that require a less complex orchestrator.
The main challenge with Docker Swarm is that it only operates on virtual machines within Windows and MacOSX. It can also have problems when linking containers to storage.
3. Apache Mesos
The University of California developed Apache Mesos to offer an easy-to-scale, lightweight, and cross-platform container orchestration platform. It runs on Windows, MacOSX, and Linux with an API that supports popular programming languages such as C++, Java, and Python.
Unlike Docker Swarm and Kubernetes, Mesos offers only cluster-level management of up to 10,000 nodes. It is ideal for large organizations as it may be an overkill for smaller enterprises with leaner budgets.
Clearly containerization is the future of app development as containerized environments are dynamic and portable, allowing them to adapt more quickly and provide more agility than virtual machines. It’s definitely worth exploring if you want to make your software much more portable, scalable and secure.