Containers have revolutionized how applications are built, deployed, and managed, making software development easier, faster, and more efficient. With their ability to allow applications to run consistently across different computing environments, containers have become a popular technology in cloud computing orchestration.

Containers are self-contained, executable units of software that package application code along with all its dependencies, including libraries, frameworks, and configuration files. Containerized applications run consistently and reliably in any computing environment, be it a desktop, traditional data center, or cloud platform.

Dgtl Infra explains what containers are, how they work, and what they are used for. Additionally, we explore key concepts including the importance of a container engine and the process of container orchestration. Finally, Dgtl Infra discusses the advantages and disadvantages of containers, along with managed container services from leading cloud service providers (CSPs) like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud.

What are Containers?

Containers emerged as a solution to the challenges of deploying and managing applications, consistently and efficiently, when moved from one computing environment to another. For instance, over the course of its lifecycle, an application has to shift from a development and test environment to a production environment. It may also have to migrate from a physical, on-premise server to the public cloud. As such, it is difficult to ensure that the application runs smoothly in each of these potentially different environments, and inconsistencies and incompatibility issues can arise.

Containerization is a standardized technique that places an application or service together with all its dependencies, such as specific versions of runtime components (language interpreters, libraries, and system tools), required to run the application in a standalone, executable package called a container.

Containers solve issues related to version mismatches and dependencies by abstracting applications from the environment that they run in. They provide a virtualized environment that includes all of the system tools, libraries, and application settings necessary for applications to run. This technique allows applications and services to run in any computing environment and on any infrastructure that supports containers. It makes containers a great fit for cloud computing, where applications must be deployed, scaled, and managed across multiple servers and environments (i.e., public cloud, private cloud, hybrid cloud, and multi-cloud).

What is the Difference Between a Container and a Virtual Machine (VM)?

Containers are often compared with virtual machines (VMs), such as those offered by VMware, as they are both single, portable units of packaged compute. However, they are very different and solve different problems.

Virtual Machines VM Container Containers Difference Comparison

Unlike VMs, containers do not have their own separate instance of an operating system (OS) with dedicated resource allocation. Instead, they share the host OS, while resources can be allocated dynamically and efficiently based on the application needs. Consequently, multiple containers can be deployed on a server regardless of its hardware limitations.

In other words, VMs abstract an operating system from the physical server, whereas containers abstract applications from the underlying OS. Similar to how VM hypervisors virtualize the hardware to host multiple isolated operating systems, a container engine virtualizes the operating system to host multiple isolated applications (OS-level virtualization). In fact, containers can run on top of virtual machines, providing an additional layer of abstraction and isolation.

Containers are also naturally more lightweight than VMs, as they do not package an OS image or require static resources. They are purposefully built to run an application and package only the absolute minimum amount of data and executables required. Being lightweight and efficient, containers are better suited for modern development and deployment approaches, such as DevOps, microservices, and serverless computing.

Conversely, VMs provide a higher level of isolation and security since they have their own operating system and dedicated resources. This makes them better suited for environments and industries subjected to strict regulatory compliance. Providing full virtualization of the underlying hardware, VMs are also a viable alternative for running applications that require direct access to specific hardware or network interfaces.

How do Containers Work?

Containers leverage operating system-level virtualization, which allows multiple isolated runtime instances – containers – to run on a single host, sharing its operating system (OS) and other resources. The containerization process starts with creating a container image, which contains all the information required to run a container, such as the application code, OS, and other dependencies (libraries, frameworks, and configuration files).

OCI (Open Container Initiative) is a Linux Foundation project that provides open industry standards for container images and ensures compatibility and interoperability between different container technologies and systems. Docker image format, the most widely used container image format, also conforms to the OCI container image specifications.

The container image is stored in a repository, such as Docker Hub. Stored images can be pulled and run on any host that has a container engine, such as Docker, rkt (pronounced “rocket”), and LXD (Linux Container Daemon). The container engine runs on the container host (e.g., a physical computer or cloud server) and downloads the container image and initiates a new instance of it. A container, in containerization, is essentially a container image that has been initiated or executed by the container engine.

Containers are completely isolated from their host and other containers running on the same host. Once the container engine starts running a container and the packaged application code, any changes made to the container, such as file system updates, will not affect the container host or other containers. This capability of providing abstraction between the native operating systems or the native cloud provider and the application and data that define the business solution, allows for portability, which was the initial selling point for containers. However, containerization can provide much more than interoperability and portability.

What are Containers Used For?

Containers generally provide good support to the development community during the move to cloud computing, making it possible to move applications between different development, test, and production environments. Also, containers complement microservices architecture, allowing developers to break monolithic applications into smaller, more manageable, and reusable components.

Additionally, containers can provide an enhanced runtime environment for applications that can be better than a standard OS, including the ability to cluster containers using container orchestration platforms, such as Kubernetes. Clustering allows containers to be deployed and managed across multiple hosts or nodes in a coordinated manner, such that they function as a single unit. This ensures better availability, scalability, and resource management.

Most enterprises now choose container orchestration and clustering to build net-new cloud applications as well as to redesign and rebuild applications for public cloud environments.

Container Engine and Container Orchestration

Container engines and orchestration platforms are the key components that enable containerization for modern application development and deployment. Containers and container orchestration largely refer to Docker-style containers and Kubernetes container orchestration.

Container Engine

A container engine, also known as a container runtime or container manager, is a software platform that manages the entire lifecycle – creation, management, and execution – of containers. It is deployed on a host operating system and provides the low-level functionality needed for managing containers and the underlying resources, such as CPU, memory, and storage.

Examples of popular container engines include Docker, rkt, and LXC (Linux Containers) / LXD (Linux Container Daemon).


Docker provides a platform as a service (PaaS) that enables users to run containerized applications on a desktop in a simplified and standardized manner. The Docker Engine is the core component of the Docker platform. It is the market-leading container engine, and many cloud platforms include services that support Docker containers. Essentially, it is a containerization tool that provides an application programming interface (API) and a command-line interface (Docker Client) to allow users to run and manage Docker containers.

Docker containers are highly portable and can be run on various platforms, including Linux, Windows, and macOS.

Container Orchestration

The term container orchestration primarily refers to the full lifecycle of managing containers in dynamic environments like the cloud, where machines (servers) come and go on an as-needed basis. Container orchestration provides the ability to run many similar or different containers in clusters to provide better scalability and flexibility.

Container orchestration platforms build on top of container engines and provide additional functionality for managing and coordinating the deployment, scaling, and management of multiple containers as a single unit. This includes tasks such as scheduling containers across multiple hosts, managing network and storage resources, and ensuring that containers are highly available and recover gracefully in case of failure.

Examples of popular container orchestration platforms include Kubernetes, Docker Swarm, and Apache Mesos. Together, container engines and orchestration platforms enable the use of containers by providing the necessary tools and infrastructure for creating, managing, and deploying containerized applications at-scale.


Kubernetes, also known as K8s, is an open-source container orchestration system used to control clusters of containers. It uses container orchestration and clustering systems that can launch, manage, and destroy containers with ease on any number of platforms. Kubernetes provides features including automated deployment and scaling of containers, load balancing, self-healing, and automatic recovery.

More broadly, Kubernetes has become the de facto standard for container orchestration and is widely used in modern application development and deployment, especially for cloud-native applications. It can run on most platforms and clouds and supports multiple container runtimes, including Docker.

Advantages and Disadvantages of Containers

Advantages of Containers

The advantages of containers are isolation & security, portability, lightweight design, resource utilization, reusability & support, and resiliency & scalability.

1) Isolation and Security

Packing everything that an application needs into a container, isolates the application from the server on which it is running. This results in process-level isolation, meaning that processes running in a container cannot interfere with processes running outside the container or in other containers. Similarly, each container is limited to the amount of CPU, memory, and other resources allocated to it.

Each container can also have its own security policy and access controls, allowing containers to run with different levels of security. Vulnerabilities and failures in one container do not affect other containers or the underlying host for the most part.

2) Portability

Containers can run anywhere, on virtual machines (VMs) or physical servers, on-premises or in the cloud. They pack all the dependencies that the containerized applications need to run, making applications platform-agnostic and portable across computing environments. This portability is the key benefit of containerization as it eliminates the risk of provider or vendor lock-in.

3) Lightweight Design

Containers share the host operating system (OS) instead of running their own instance of an OS. This makes them more lightweight, faster to start, and resource-efficient as compared to virtual machines (VMs). Containers are designed to be ephemeral and disposable, making them a perfect fit for dynamic cloud environments.

4) Resource Utilization

Containers provide a highly-efficient way of managing and utilizing resources, as compared to traditional VMs and bare metal servers. More specifically, containers do not require a full operating system and hardware virtualization layer, which means they do not have to replicate the same resources for each instance. Containers only use the resources they absolutely need to run and can be rapidly spun up and destroyed on an as-needed basis to avoid any resource wastage.

5) Reusability and Support

Containers have a large ecosystem of third-party providers for everything, including security systems, databases, governance systems, and operations systems. Being reusable and prevalent, developers can almost always find a solution for their unique requirements, instead of building everything from scratch.

6) Resiliency and Scalability

Containers can be easily replicated or cloned across multiple nodes and clusters for both scalability and resilience. The container orchestration platform can automatically reroute traffic to backup containers, to keep the applications available even if one or more nodes fail. Similarly, container orchestration platforms can create new containers as demand increases and destroy them when they are no longer needed. This way, containerized applications can handle varying levels of traffic.

Disadvantages of Containers

The disadvantages of containers are overapplication, cost, operational complexity, and a skills gap.

1) Overapplication

Containers, like any other technology, are not suitable for all applications. Specifically, applications with unique or custom dependencies, high resource consumption, or real-time performance needs may not be able to tolerate the overhead costs of containerization. Organizations need to analyze their systems before containerizing them. For example, pursuing portability when the application is unlikely to ever move from its current host platform is futile.

2) Cost

Organizations often underestimate the amount of time and money required to move existing applications to a container. The cost of leveraging containers includes the cost of development, deployment, and operations. Businesses may end up spending excessive amounts of time and money on building or moving containerized applications.

3) Operational Complexity

Containers bring additional complexity, meaning organizations need abstraction and automation tools to manage them effectively. That can be problematic for organizations that need to operate containers and container orchestration systems, in addition to their existing platforms and tools for legacy applications.

4) Skills Gap

Building containerized solutions correctly requires training and experience in leveraging the right technology for unique scenarios. When organizations cannot find the right talent, they may choose to settle for underqualified developers and designers or delay moving to containers altogether. Either of these choices can lead to additional costs and risks.

Container Services in the Cloud

Containers provide an effective development and deployment technology for the cloud, which in turn promotes the use of cloud computing platforms. In fact, the “cloud native” movement was largely built on containers, container orchestration (Kubernetes), and microservicesall tightly coupled technologies.

The primary objective of leveraging containers in the cloud is to avoid cloud and platform lock-in. Containers and container orchestration services carry out the heavy lifting of application processing and utilize the underlying platforms to only provide primitive platform services, such as compute, storage, networking, database, and security. Under this architecture, the underlying platforms, in particular public cloud providers, are no longer at the center of the architecture, but are mere compute and storage service providers.

Container Orchestrators by Cloud Service Providers

All major cloud service providers (CSPs) deliver container orchestrators and support leading container engines and orchestration platforms to allow organizations to deploy and manage containerized applications without having to oversee the underlying infrastructure.

Below are examples of container orchestrators provided by Amazon Web Services (AWS), Microsoft Azure, and Google Cloud:

Amazon Web Services (AWS)

Organizations can use Amazon Elastic Container Service (ECS) or Amazon Elastic Kubernetes Service (EKS) to orchestrate swarms of Docker containers on AWS using Amazon Elastic Compute Cloud (EC2) resources.

  • Amazon ECS: fully-managed container orchestration service that supports Docker containers
  • Amazon EKS: fully-managed Kubernetes service
Microsoft Azure
  • Azure Kubernetes Service (AKS): fully-managed Kubernetes container orchestration service
  • Azure Container Instances (ACI): serverless container hosting service that supports multiple container engines, including Docker and Open Container Initiative (OCI)
  • Azure Service Fabric: distributed systems platform for deploying and managing scalable, highly available, and reliable microservices and containers
Google Cloud
  • Google Kubernetes Engine (GKE): fully-managed Kubernetes service
Mary Zhang covers Data Centers for Dgtl Infra, including Equinix (NASDAQ: EQIX), Digital Realty (NYSE: DLR), CyrusOne, CoreSite Realty, QTS Realty, Switch Inc, Iron Mountain (NYSE: IRM), Cyxtera (NASDAQ: CYXT), and many more. Within Data Centers, Mary focuses on the sub-sectors of hyperscale, enterprise / colocation, cloud service providers, and edge computing. Mary has over 5 years of experience in research and writing for Data Centers.


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