Application containerization - definition & overview

Application containerization is a rapidly developing technology that is changing how developers test and run application instances in the cloud. Application containers house all the runtime components necessary to execute an application in an isolated environment, including files, libraries, and environment variables. With today's available containerization technology, users can run multiple isolated applications in separate containers that access the same OS kernel.

Application containerization is a relatively new methodology in the world of IT, but there are already several companies vying for the biggest market share of this rapidly growing trend. Today's application containerization market leaders are the Amazon Elastic Container Service, Docker Platform and Kubernetes Engine.

Amazon's Elastic Container Service (ECS) is a scalable container orchestration platform that supports Docker containers and gives Amazon Web Services (AWS) customers the ability to run containerized applications. With Amazon ECS, users can implement simple API calls to launch or stop docker-enabled applications and access other AWS features like AWS CloudTrail event logs, Amazon CloudWatch Events, IAM roles, load balancers and more.

Docker containers were first launched in 2013 as an open-source project called Docker Engine. A Docker container is a package of code that includes an application and all of its dependencies. A container image is a lightweight package of executables that includes all of the code, runtime, system tools, libraries and configuration files needed to run an application. Container images become containers at runtime, isolating the software instance from its environment and ensuring that it performs uniformly regardless of differences between the development and staging environments.

The Google Kubernetes Engine provides a managed environment for deploying and scaling containerized applications using the Google Cloud infrastructure. Kubernetes (K8s) was developed and released as an open-source containerization management system, but was later packaged and commercialized along with additional features and customized functionality with the Google Cloud Platform. These additional features include:

• Load-balancing for compute engine instances

• The ability to designate subsets of nodes within a cluster

• Automatic scaling of node instances in your cluster on an on-demand basis

• Automatic software upgrades

• Self-healing auto-repair feature helps to maintain node health and availability

• Logging and monitoring tools that provide increased visibility of the node cluster

Containerization and virtualization are both applications of technology that help software developers make the best use of their computational resources and IT infrastructure budgets. Each of these innovations also allows developers to deploy increasing numbers of application instances at a relatively low cost compared to purchasing new hardware — but that's just about where the similarities end. To better understand the differences between application containerization and virtualization, let's review the basic architecture for both types of systems.

Whether you're using virtualization or containerization to meet your software development needs, you'll need to start with a host machine and an installed operating system.

Virtualization technology depends on a specific type of software application called a hypervisor. A hypervisor, also called a virtual machine monitor, is a piece of hardware, software or firmware that creates and runs virtual machines. The hypervisor sits between the host machine and guest operating systems. Each created virtual machine imitates a defined hardware configuration and runs its own operating system. It must also include the bins and libraries required to run the desired application.

The architecture for application containerization is fundamentally different from that of virtualization, especially in that it does not require a hypervisor. Containers also do not run their own individual instances of the operating system. A container houses the application code along with its dependencies (bins, libraries, etc.). A container orchestration software tool sits between the containers and the host operating system. Each container on the machine accesses a shared host kernel instead of running its own operating system as virtual machines do.

The principal benefit of application containerization is that it provides a less resource-intensive alternative to running an application on a virtual machine. This is because application containers can share computational resources and memory without requiring a full operating system to underpin each application.

Despite the benefits they provide, when compared to virtualization services, application containerization is not necessarily a replacement for virtual computing. Virtual machines were designed to reduce hardware costs and improve resource allocation, while the primary benefit of containerization is that it streamlines application testing and management for software developers. The most important benefits of application containerization can be summarized as follows:

• Containers provide an isolated environment for running applications which is ideal for testing new features

• Containers are smaller, boot faster and require fewer resources than virtual machines

• Containers enjoy multi-cloud platform support and can be deployed on AWS, Google Cloud and other leading cloud services

• Containerized applications can run on any machine, as they contain all of the dependencies required to launch the application

• Containers are lightweight and cost-efficient. IT organizations can support a large number of containers on the same infrastructure

Each application deployed inside a container generates event logs that describe its interactions with users on the network. As IT organizations deploy increasing volumes of containers, there is an increasing need for effective monitoring and log analysis tools to capture and make sense of that data. With innovative tools like our Docker Log Analysis integration, Sumo Logic's container-native monitoring solution, IT organizations can more easily troubleshoot security and operational issues in container-based applications.