Understand CNAPPs with Our Guide
Understand CNAPPs with Our Guide
What is containerization?
Containerization is a software deployment process that packages applications with all the libraries, files, configurations, and binaries needed to run them into one executable image. This isolates applications and allows them to run, sharing only the OS kernel with the host machine. Containerization allows developers to create a single software package that can run on multiple devices or operating systems. A containerized application will “just work” because it does not depend on the user to provide access to the files it needs to operate. Everything it needs is prepackaged with it. Containerization offers increases in portability, scalability, and resource efficiency, and it provides a less resource-intensive alternative to virtual machines (VMs) while addressing many of their drawbacks.
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A simplified version of containerizing a software application includes the following three phases:
- Develop. At the development stage, when a developer commits the source code, they define an application’s dependencies into a container image file. Because the container configuration is stored as code, it is highly compatible with traditional source code management. Container image files are usually stored alongside the source code of the application, making containerization as simple in some cases as adding an image file and all associated dependencies to the source code.
- Build. At the build stage, the image is published to a container repository, where it is versioned, tagged, and made immutable. This is the step that essentially creates a container. Once an application includes an image file and is configured to install and pull required dependencies into an image, it is ready to be materialized and stored. This can either be done locally or in an online repository, where it can be referenced and downloaded.
- Deploy. At the deploy stage, a containerized application is deployed and run locally, in continuous integration/continuous delivery (CI/CD) pipelines or testing environments, in staging, or in a production environment. Once it is accessible by an environment, the image represents an executable and can be run.
Although there are many different containerization technologies and container orchestration methods and platforms to choose from, the Open Container Initiative works to define industry standards and specifications for container runtimes and images. Organizations should thoroughly evaluate available technologies before adoption to determine which one is right for them.
Container orchestration
Container orchestration is the automation of the process of provisioning, deploying, scaling, load balancing, and managing containerized applications. It reduces the possibility of user error and increases development efficiency by automating the software development life cycle (SDLC) of the hundreds (if not thousands) of microservices contained in a single application.
Benefits of containerization
Containerization presents many advantages over the traditional method of software development, where applications run directly on the host machine and are packaged only with application assets. Similar to VMs, containerization provides benefits in terms of deployment, security, resource utilization, consistency, scalability, support for microservices, and integration with both DevOps practices and CI/CD workflows. Containerization can even surpass the performance of VMs. Here’s how containerization provides value in modern software development and deployment:
- Portability: A containerized application can reliably run in different environments because its dependencies are self-contained. A containerized application does not require that a host machine have dependencies pre-installed, reducing friction in the installation and execution process.
- Isolation: Because containerized applications are isolated at the process level, a fatal crash of one container will not affect others, isolating the fault to just one application. This also has ramifications for security. Because an application’s resources are virtualized within the container, potential threat actors must pursue other means to secure access to the host system.
- Resource efficiency: A containerized application contains only its own code and dependencies. This makes containerized apps significantly lighter packages than VMs, which must contain portions of the operating system code to create a more extensively provisioned virtual machine. Containerization allows the ability to run multiple containers in a single compute environment, greatly increasing resource utilization efficiency.
- Consistency: Because a containerized application remains consistent across multiple runtime environments, a container can reliably run in development, staging, and production environments.
- Scalability: Containers are easier and faster to deploy and more secure than traditional applications, making them easier to scale. This results in lower overhead and more efficient use of resources.
- DevOps enablement: Containerization allows developers to automate considerable portions of the SDLC, following DevOps practices. It helps streamline both development and testing, resulting in a faster SDLC and shortened time to market.
- Microservices support: Microservices are small, independent services that communicate through APIs. They allow developers to create applications that can be updated in small pieces, microservice by microservice, instead of all at once. Through containerization, it’s possible to create microservices that run efficiently in any environment. Since containerized applications use fewer resources than VMs, their host machines can run more microservices in total.
- CI/CD integration: Integrating containerization with CI/CD development practices results in faster deployments. Containers are light and portable, which makes them easier to test and deploy. They can also be created automatically, making them a perfect fit for CI/CD pipelines. Since the required dependencies are coded into the container, they also eliminate considerations involved with library compatibility.
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Read Customer StoryContainers vs. virtual machines
VMs date back to the 1970s and have traditionally been used to create a duplicated runtime environment. Functionally, VMs operate similarly to containers: They place the resources an application or operating system needs to run in an isolated environment on the host hardware. The two differ in terms of scope. A virtual machine fully replicates the operating system and emulates certain attributes of the system it is emulating. This creates a virtual duplicate of the machine and the software it runs. A container, however, contains only the application and the libraries and binaries it needs to run. Containers don’t emulate systems; they work with them by utilizing the OS kernel on the host machine. As a result, containers use far fewer resources than VMs. Containerization typically uses less RAM, disk space, and CPU overhead than running VMs. The following chart compares containers and VMs across a variety of criteria:
Aspect | Containers | Virtual Machines |
---|---|---|
Isolation | Uses OS-level virtualization, sharing the host OS kernel among containers. Each container has its isolated user space. | Provides full OS virtualization, running guest OS on top of a hypervisor, with each VM having its own kernel and user space. |
Resource overhead | Lightweight; shares host OS resources efficiently, consuming less memory and disk space. | Heavier; each VM includes a guest OS, requiring more memory and disk space compared to containers. |
Startup time | Starts quickly; containers can be launched in seconds. | Slower startup; VMs typically take longer to boot, as they involve booting an entire OS. |
Performance | Near-native performance; minimal overhead due to shared kernel. | Slightly lower performance due to overhead of virtualization layer and separate OS instances. |
Scalability | Highly scalable; can spin up multiple containers on a host without significant resource overhead. | Scalable, but more resource-intensive; requires more memory and CPU for each additional VM. |
Deployment flexibility | Flexible deployment; portable across different environments with consistent behavior. | Less flexible; VMs are less portable due to differences in guest OS and configuration. |
Security | Less isolation compared to VMs; shares host kernel, which may pose security risks if not properly configured. | Provides strong isolation; each VM is sandboxed with its own OS, reducing security risks. |
Use cases | Ideal for microservices, cloud-native applications, and rapid development/testing. | Suitable for running multiple applications with different OS requirements or legacy systems. |
Microservices and containerization
Microservices are small, independent services that communicate over APIs. They allow for faster deployment and greater flexibility than monolithic applications. The difference between microservices and containers is that one is about development, and the other is about deployment. Microservices offer a more agile approach to software development by allowing developers to create individual services that perform specific tasks. These microservices can then be updated and maintained individually by specific teams, greatly streamlining the development process. A container can then house the microservices. By deploying microservices into a container instead of a VM, teams gain all of the benefits of containerization. They are also able to isolate their respective microservices, improving resilience and efficiency. Microservices have traditionally been used to modernize existing monolithic applications. The application’s various functions can be broken up into microservices, allowing teams to revise and update more quickly.
How microservices and containerization complement each other
An example of how microservices and containerization can complement one another begins with a single, monolithic application. Imagine this application performs three separate functions, each in its own layer:
- Serving web requests
- Processing requests with business logic
- Communicating with the database layer
Over time, the complexity of each of these layers increases, and the business decides to separate the layers into three separate microservices:
- A web service
- A core logic API service
- A database service
Once these three layers are decomposed into microservices, the company decides to containerize them. This gives the microservices independence from one another, allowing for the many benefits of containerization.
Containerization use cases
The most common containerization use cases include:
- Microservices: As explained above, small, independent microservices are frequently containerized.
- CI/CD: Containerized code is much easier to automate and deploy rapidly, making it a natural fit for CI/CD workflows.
- Cloud migration: In cloud migration, legacy applications are containerized and deployed in cloud environments. The “lift and shift” approach allows them to be modernized without rewriting all of the code.
- Internet of things (IoT) devices: Because IoT devices have limited computing power, updates must often be processed manually. Containerization allows developers to automate these updates.
Containerization tools
This table includes a mix of container runtimes, orchestration platforms, and container management tools used for building, deploying, and managing containerized applications. Each tool offers unique features and capabilities to suit various deployment scenarios and infrastructure requirements.
Tool | Description | Website |
---|---|---|
Docker | Leading container platform for developing, shipping, and running applications in containers. | Docker |
Kubernetes | Container orchestration platform for automating deployment, scaling, and management of containerized applications. | Kubernetes |
Podman | Daemonless container engine designed as a drop-in replacement for Docker. | Podman |
Docker Compose | Tool for defining and running multi-container Docker applications using a YAML configuration file. | Docker Compose |
OpenShift | Kubernetes-based container platform for enterprise application development and deployment. | OpenShift |
Amazon ECS | Fully managed container orchestration service provided by Amazon Web Services (AWS). | Amazon ECS |
Google Kubernetes Engine (GKE) | Managed Kubernetes service provided by Google Cloud for deploying, managing, and scaling containerized applications. | GKE |
Apache Mesos | Distributed systems kernel that abstracts CPU, memory, storage, and other compute resources away from machines. | Apache Mesos |
Nomad | Distributed job scheduler and cluster manager from HashiCorp for deploying applications at scale. | Nomad |
LXC/LXD | Linux Containers (LXC) and LXD are container technologies that provide OS-level virtualization on Linux. | LXC/LXD |
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