Containers are rapidly being adopted by organizations worldwide. According to Research and Markets, over 3.5 billion applications are currently running in Docker containers, and 48% of organizations are managing containers at large scale with Kubernetes.
Containers have compelling advantages over the previous generation of virtualization technology. They are faster, more lightweight, and easier to manage and automate than virtual machines (VMs), and are phasing out VMs in many common scenarios.
We’ll discuss the advantages of containers over VMs, compelling reasons to start using containers, and key requirements for successfully adopting containers in your organization.
In this article, you will learn:
Containers vs Virtualization
Let’s briefly review the differences between traditional virtualization and containerization, to understand the compelling advantages of containers, and the reasons for their rapid adoption.
What is the Difference Between Virtual Machines and Containers?
Virtual machines (VMs), pioneered by VMware over two decades ago, are used by most large enterprises to build a virtualized computing environment. A virtual machine is an emulation of a physical computer. VMs make it possible to run several operating systems on one server, dramatically improving resource utilization of enterprise applications.
VMs are managed by a software layer called a hypervisor, which isolates VMs from each other and allocates hardware resources to each VM. Each VM has direct or virtualized access to CPU, memory, storage, and networking resources.
Each virtual machine contains a full operating system with applications and associated libraries, known as a “guest” OS. There is no dependency between the VM and the host operating system, so Linux VMs can run on Windows machines, and vice versa.
Containers are an isolated unit of software running on top of an operating system (usually Linux or Windows). Unlike virtual machines, they only run applications and their dependencies. Containers do not need to run a full operating system on each instance—rather, they share the operating system kernel and gain access to hardware through the capabilities of the host operating system. This makes containers smaller, faster, and more portable,
Like virtual machines, containers allow developers to increase CPU and memory utilization on physical machines. However, containers have taken it a step further.
Related content: read our guide to Docker architecture ›
Use Cases in Which Containers are Preferred to Virtual Machines
Here are three main scenarios in which containers provide compelling advantages compared to virtual machines:
- Microservices—containers are highly suitable for a microservices architecture, in which applications are broken into small, self-sufficient components, which can be deployed and scaled individually. Containers are an attractive option for deploying and scaling each of those microservices.
- Multi-cloud—containers provide far more flexibility and portability than VMs in multi-cloud environments. When software components are deployed in containers, it is possible to easily “lift and shift” those containers from on-premise bare metal servers, to on-premise virtualized environments, to public cloud environments.
- Automation—containers are easily controlled by API, and thus are also ideal for automation and continuous integration / continuous deployment (CI/CD) pipelines.
7 Reasons to Adopt Containers in Your Organization
Portability – Ability to Run Anywhere
Containers can run anywhere, as long as the container engine supports the underlying operating system—it is possible to run containers on Linux, Windows, MacOS, and many other operating systems. Containers can run in virtual machines, on bare metal servers, locally on a developer’s laptop. They can easily be moved between on-premise machines and public cloud, and across all these environments, continue to work consistently.
Resource Efficiency and Density
Containers do not require a separate operating system and therefore use fewer resources. VMs are typically a few GB in size, but containers commonly weigh only tens of megabytes, making it possible for a server to run many more containers than VMs. Containers require less hardware, making it possible to increase server density and reduce data center or cloud costs.
Container Isolation and Resource Sharing
You can run multiple containers on the same server, while ensuring they are completely isolated from each other. When containers crash, or applications within them fail, other container running the same application can continue to run as usual. Container isolation also has security benefits, as long as containers are securely configured to prevent attackers from gaining access to the host operating system.
Speed: Start, Create, Replicate or Destroy Containers in Seconds
Containers are a lightweight package that everything needed to run, including its own operating system, code, dependencies, and libraries.
You create a container image and then deploy a container in a matter of seconds. Once you have the image set up, you can quickly replicate containers and easily and quickly deploy as needed. Destroying a container is also a matter of seconds.
The lightweight design of containers ensures that you can quickly release new applications and upgrades like bug fixes and new features. This often leads to a quicker development process and speeds up the time to market as well as operational tasks.
Containers make it easy to horizontally scale distributed applications. You can add multiple, identical containers to create more instances of the same application. Container orchestrators can perform smart scaling, running only the number of containers you need to serve application loads, while taking into account resources available to the container cluster.
Improved Developer Productivity
Containers allow developers to create predictable runtime environments, including all software dependencies required by an application component, isolated from other applications on the same machine. From a developer’s point of view, this guarantees that the component they are working on can be deployed consistently, no matter where it is deployed. The old adage “it worked on my machine” is no longer a concern with container technology.
In a containerized architecture, developers and operations teams spend less time debugging and diagnosing environmental differences, and can spend their time building and delivering new product features. In addition, developers can test and optimize containers, reducing errors and adapting them to production environments.
Related content: read our guide to Docker in production ›
What is Needed for Successful Adoption of Containerization?
Here is a checklist that can help you successfully containerize your applications:
Setup and Design
|Use fine-grained components||The smaller the unit, the easier it is to orchestrate. Break your components into fine-grained independent units. You should be able to design, deploy, scale, and maintain each unit independently.|
|Prefer disposable components||When possible, design and build stateless and lightweight containers. This enables the orchestration platform to easily monitor and handle the container life cycle. However, if you do need to run stateful applications, you can do so using StatefulSets.|
Security and Orchestration
|Implement container security||It is critical to implement security measures and policies across the entire container environment, which includes container images, containers, the hosts, registries, runtimes, and your orchestrator. For example, use secrets to protect sensitive data and harden your environment.|
|Leverage container orchestrators||Deploying containerized applications in production involves deploying, running, and managing a massive amount of containers—sometimes thousands, sometimes tens and hundreds of thousands. To efficiently manage containers, you need a container orchestration platform that provides automation and management capabilities for tasks like deployment, scaling, resource provisioning, and more. A popular open source option is Kubernetes.|
Automation and Efficiency
|Automate your pipeline|
In addition to automating the orchestration of containers, you can also automate your entire development pipeline—or as many aspects of it as possible. Automation can help you quickly iterate and make any necessary changes. For this purpose, you can leverage a container orchestration platform as well as other tools that integrate well together.
|Infrastructure as Code (IaC)||IaC lets you define various aspects of the infrastructure in declarative fies, which are used to automate the process. Container platforms often provide IaC capabilities that let you define the environment and turn it into the codebase. There are also tools that are dedicated to providing IaC capabilities for certain phases of the development pipeline, like security or resource optimization.|
|Practice agile development||Agile methodologies help teams improve the development lifecycle by making it more efficient and breaking through silos. For example, DevOps, which stands for development and operations, helps ensure that development and operational tasks are handled quickly and effectively. This can significantly help teams that build and manage containerized environments.|
|Promote a self-service developer experience||Teams should be able to independently provision their projects. This means collaborators need control over resources like code repositories and compute power, automation features, and access to image repositories. When providing access and privileges, be sure to use granular permissions.|
Get started with containers with our in-depth guides: