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What Is Containerization? | Palo Alto Networks
5 min. read
Containerization is a lightweight virtualization method that packages applications and their dependencies into self-contained units called containers. These containers run on a shared host operating system, providing isolation and consistency across different environments. Containerization enables efficient resource usage, rapid deployment, and easy scaling. Popular tools like Docker and Kubernetes facilitate creating, managing, and orchestrating containers. This technology streamlines development, testing, and deployment by reducing conflicts and ensuring that containerized applications run consistently, regardless of the underlying infrastructure.
Containerization has become an essential part of modern software development practices, particularly in microservices architectures and cloud-native applications.
Why Is Containerization Important?
In recent years, an average 90% of organizations report using containers in production, as surveyed annually by the Cloud Native Computing Foundation (CNCF). The population climbs to 95% for those using containers in the proof of concept (PoC), test, and development environments.
Containers have arrived. They’ve long been helping DevOps teams to scale and create unique services, eliminating the need for dedicated servers and operating systems. Using containers for microservices allows applications to scale on a smaller infrastructure footprint, whether in on-premises data centers or public cloud environments. The containerization approach allows DevOps teams to quickly expand without significant resource constraints, making organizations more agile while enabling isolated testing and preventing interference with other essential services.
Adopting container technology dramatically improves the application lifecycle, from inception to production deployment. But containers aren’t just an enabling technology for cloud-native applications. Containers are a cornerstone technology — and for reasons that closely align with the principles of cloud native.
Microservices Architecture
Containers are inherently suited for microservices. Each microservice can be developed, deployed, and scaled independently, offering greater agility and resilience.
Portability
Containers encapsulate an application and its dependencies, ensuring that it runs the same regardless of where it’s deployed.
Platform Neutrality
Containers enable applications to run seamlessly across various environments and operating systems, reducing compatibility issues and simplifying deployment processes.
Scalability
Containers can be easily orchestrated using tools like Kubernetes, which automates the deployment, scaling, and management of application containers.
Immutability
Containers maintain an unchangeable state once created, ensuring consistent behavior across environments, simplifying rollbacks, enhancing security, and reducing deployment-related errors.
Isolation and Security
While not as isolated as VMs, containers do provide a level of process and file system isolation. Security can be further enhanced using specialized tools and best practices tailored for containerized environments.
Containers: A Modern Contender to VMs
Virtual machines (VMs) have been the bedrock of enterprise computing, providing a dependable way to run multiple operating systems on a single hardware host while offering reliable isolation and security features. Ubiquitous since the early 2000s, organizations continue to utilize VMs in aspects of IT infrastructure, from data centers to cloud services.
Containers gained prominence largely in the last decade as organizations pivoted toward DevOps and agile methodologies. An essential component of modern application architecture, containers challenge the long-standing dominance of VMs in many use cases.
Originating from OS-level virtualization, containers encapsulate an application and its dependencies into a single, portable unit. They offer advantages in resource efficiency, scalability, and portability, making them a popular choice for cloud-native applications and microservices architectures.
Both VM and container technologies now coexist, often complementing each other as enterprises navigate the evolving landscape of application deployment and management.
Figure 1: Differences between containerized and virtual machine applications
Choosing Between Containers and Virtual Machines
The choice between containerized applications and virtual machines (VMs) remains a strategic decision. Both technologies offer advantages and limitations, impacting factors such as performance, security, scalability, and operational complexity.
Containers, built on OS-level virtualization, offer superior resource efficiency and faster startup times. Because they’re modular, easily distributed, elastic, and largely platform agnostic, they greatly reduce the friction of managing full virtual machines. They excel in cloud-native applications and microservices, facilitated by orchestration tools like Kubernetes. Their process-level isolation, though, poses security challenges, albeit with a smaller attack surface.
VMs operate on hardware-level virtualization, running a full guest OS. They offer stronger security through better isolation but consume more resources and have a larger attack surface. VMs are better suited for monolithic applications and come with mature, yet less flexible, management tools like VMware vSphere.
In figure 1, you see a physical infrastructure that includes two virtual machines and three containerized applications. Each virtual machine runs on different operating systems, whereas the containerized applications all run on the same operating system. The ability of containers to run multiple applications on a single physical server, even if the applications operate on different operating systems, streamlines infrastructure management.
Through higher resource utilization and open-source options, containers reduce hardware and software costs. VMs often require proprietary software and more hardware, increasing operational costs.
Organizations should align their technology choice with their needs, goals, existing infrastructure, and security considerations.
| Containers | VMs |
| Lightweight resource consumption | Heavyweight resource consumption |
| Native performance | Limited performance based on hardware |
| All containers share the host OS | Each VM runs its own OS |
| OS virtualization | Hardware-level virtualization |
| Startup time is rapid (milliseconds) | Startup time is slow (minutes) |
| Requires less memory space | Requires more memory space (esp. OS) |
| Process-level isolation and potentially less secure | Fully isolated and adds more security (esp. hypervisor) |
Table 1: Advantages and disadvantages of containers and virtual machines
To Container or Not to Container: Moving Applications to the Cloud
Containerization has revolutionized the way software applications are developed, deployed, and managed, offering a lightweight and portable solution for packaging and running applications consistently across different environments.
But among the "5 Rs" of cloud migration — rehost, refactor, revise, rebuild, and replace — not all involve container technologies.
Figure 2: The three main approaches to a cloud-native transformation, as well as two options
for retiring old platforms
Architecture and Migration
Containers are integral to cloud migration and application management strategies, allowing organizations to benefit from cloud-native tools and methodologies. But the decision-making process surrounding application architecture, technology, and cloud migration methods varies for each organization.
Assessing Application Architecture and Technology
Organizations need to evaluate their existing applications, infrastructure, and technology stacks to understand their current state and identify limitations, opportunities, and compatibility with cloud services. This assessment will help determine the necessary changes, optimizations, and architectural patterns they should adopt for a successful migration.
Choosing a Cloud Migration Method
After assessing the application architecture and technology, organizations can choose the most suitable migration method based on their requirements, budget, timeline, and risk tolerance. Their chosen approach — whether to rehost, refactor, revise, rebuild, or replace — will accommodate factors that include the complexity of their existing applications, the desired level of cloud integration, and their overall cloud strategy.
Rehost: The “Lift and Shift” Approach (IaaS)
Rehosting an application involves minimal changes to the existing application and focuses on moving it as-is to the cloud, which is how rehosting became known as lift and shift. Organizations capitalize on speed and cost-effectiveness by moving their business application to a new hardware environment without altering its architecture. The trade-off comes in the form of maintenance costs, as the application doesn't become cloud-native in the lift-and-shift process.
DRAWBACK: While containers can be used in a rehost strategy, their impact is less transformative compared to the refactor, revise, and rebuild strategies.
Refactor: Embracing Platform as a Service (PaaS)
Refactoring, or repackaging, maintains an application’s existing architecture and involves only minor changes to its code and configuration. Containers offer a way to encapsulate the application and its dependencies, making it easier to move and manage. This also allows organizations to take advantage of cloud-native features, especially through the reuse of software components and development languages.
DRAWBACK: PaaS enables organizations to leverage cloud-native features, particularly through the reuse of software components and development languages. However, porting an application to the cloud without making significant architectural changes could introduce constraints from the existing framework as well as underutilized cloud capabilities.
Revise: Modifying for Cloud Compatibility
The revise approach requires significant changes to the application's architecture, transforming it into a cloud-native or cloud-optimized solution. Organizations adapt existing noncloud code to wield cloud-native development tools and runtime efficiencies. While the upfront development costs can be significant, the payoff comes in the form of enhanced performance and scalability, ultimately maximizing the benefits of cloud services.
Containers contribute substantially to the revise approach, offering a level of abstraction that allows developers to focus on application logic.
Rebuild: A Ground-Up Approach
Rebuilding, as the name suggests, involves completely rebuilding or rearchitecting the application using cloud-native technologies and services. This method is ideal for organizations looking to modernize their applications and take full advantage of the cloud. In doing so, they can fully employ cloud-native tools, deployment methods, and efficiencies, which typically results in the most optimized and resilient applications.
DevOps teams rely on containers as the go-to technology when building an application from scratch. Containers allow for microservices architectures, easy scaling, and seamless deployment.
Replace: Transition to Software as a Service (SaaS)
The replace migration strategy involves retiring the existing application and replacing it with a new cloud-native solution or a software as a service (SaaS) offering. Organizations seeking to reduce their maintenance burden and focus on innovation often opt to replace an application. Speed to market factors into the decision, as the SaaS vendor assumes responsibility for new feature development. Containers in this approach are less relevant to the user, though the SaaS provider may use them extensively.
DRAWBACK: Organizations face constraints imposed by the SaaS vendor or underlying cloud infrastructure, particularly concerning data management.
Selecting the Cloud Migration Method Based on Needs |
||
| Migration | Advantages | Disadvantages |
| Rehost |
|
|
| Refactor |
|
|
| Revise |
|
|
| Rebuild |
|
|
| Replace |
|
|
Table 2: Sample pros and cons for various migration methods
When Micro Means Fast
Cloud-native applications are designed from the ground up to take full advantage of cloud computing frameworks. Similar to refactoring, new container-native applications are often built using microservices architectures, which allow for independent deployment of application components.
The Triad of Modern Application Development
In today's high-speed digital landscape, agility and security aren’t just buzzwords — they’re imperatives. In the race to keep pace, microservices, CI/CD, and containers have gained prominence. Together, these three elements form the backbone of modern application development, offering a robust framework that balances speed, scalability, and security.
Container FAQs
Cloud-optimized refers to software and systems designed to exploit the scalability, performance, and cost efficiencies of cloud computing environments. It involves architecting applications and infrastructure to leverage cloud-native features like auto-scaling, distributed storage, and microservices.
Cloud-optimized applications are built to maximize the benefits of cloud platforms, such as improved resource utilization, reduced operational costs, and enhanced flexibility. They typically employ a modular structure, allowing for easier updates and maintenance, and are designed to handle the dynamic nature of cloud resources.
The Docker engine is a client-server application with three major components: a server running as a daemon, a REST API for interacting with the server, and a command-line interface (CLI) client that communicates with the server via the API. It's responsible for creating and managing Docker containers, the lightweight and portable execution environments. The Docker engine allows developers to package applications and dependencies into containers, which can then be run on any system that has Docker installed, ensuring consistency across different environments.
Container orchestration involves the automated management, scaling, and networking of containers. It is essential in environments where numerous containers are used, ensuring they operate efficiently and cohesively. Orchestration tools, like Kubernetes, Docker Swarm, and Apache Mesos, handle tasks such as deployment of containers, scaling them up or down as per demand, maintaining container health, and enabling communication between different containers. Container orchestration simplifies the complexities of managing containers at scale, providing high availability, resource optimization, and seamless deployment processes.
DevOps is a set of practices and cultural philosophies that aim to unify software development (Dev) and IT operations (Ops). It involves automating and integrating the processes between these teams to build, test, and release software faster and more reliably. Key practices include continuous integration, continuous delivery, microservices, infrastructure as code, monitoring and logging, and communication and collaboration. DevOps encourages a culture of collaboration, where developers and operations teams work closely, share responsibilities, and combine their workflows. This approach reduces silos, improves efficiency, and enhances the quality of software deployments.
A container registry is a storage and distribution system for container images. It allows developers to push, pull, manage, and share container images. Registries can be public or private, with popular public registries including Docker Hub and Google Container Registry. They play a role in containerized software development and deployment workflows, providing a centralized resource for managing the various versions of container images.
Secure and efficient management of container registries is vital in ensuring the integrity and availability of containerized applications.
A container repository is a collection of related container images stored within a registry. Each repository is typically associated with a specific application, service, or component and contains different versions or variations of container images for that component.
Repositories allow developers to organize, version, and manage their container images efficiently — which is helpful, considering that organizations can easily have tens of thousands of images stored in their registries. Images are usually identified by unique tags that can represent versions, environments, or configurations.
Because registries are central to the way a containerized environment operates, it’s essential to secure them.
Unlike the ephemeral storage associated with containers, persistent volumes retain data across container restarts and deployments, crucial for stateful applications like databases. Persistent volumes are independent of the lifecycle of any single container or pod, providing a consistent and reliable storage solution. In Kubernetes, persistent volumes are abstracted from the underlying storage infrastructure, offering a uniform interface to various types of storage backends, enhancing flexibility and ease of use in complex cloud environments.
ReplicaSets are a Kubernetes resource used to ensure the specified number of pod replicas are running at any given time. They provide high availability and redundancy for applications by automatically replacing pods that fail, get deleted, or are terminated. ReplicaSets are crucial for scaling applications, as they can be configured to increase or decrease the number of pod replicas based on demand. They’re fundamental to maintaining the desired state and reliability of containerized applications in Kubernetes-managed clusters, especially in dynamic cloud environments where workload demands can rapidly fluctuate.
LXC, or Linux containers, are lightweight virtualized environments that run on a Linux host, providing a method to isolate processes and resources. They offer an operating system-level virtualization alternative to traditional VMs, enabling multiple isolated Linux systems on a single control host. LXC containers are efficient and fast, as they share the same kernel as the host system but maintain separate namespaces for processes, file systems, network, and users. They’re widely used for deploying and managing applications in a resource-efficient manner, particularly in environments where full virtualization is unnecessary or too resource-intensive.
LXD is an extension of LXC (Linux containers), providing a more user-friendly and powerful system for managing LXC containers. It functions as a daemon and offers a REST API for local and remote access. LXD enhances the capabilities of LXC with additional features like easy storage management, network management, and container snapshots. It's designed for higher density and manageability, offering a VM-like experience with the lightweight performance and resource efficiency of containers. LXD is particularly useful for hosting environments and large-scale container deployments.
Resource limits and quotas in cloud computing are mechanisms to control the consumption of resources by applications or users. Limits define the maximum number of resources — such as CPU, memory, and storage — that a container or pod can use, preventing overconsumption and ensuring fair resource allocation. Quotas, on the other hand, restrict the total resource usage for a namespace, preventing any single user or team from monopolizing cluster resources. These controls are essential for maintaining the health and efficiency of multitenant cloud environments, ensuring that resources are used optimally and cost-effectively.
