What Is Containerization?
Get the lowdown on containerization, from how it works to the benefits it brings for DevOps, CI/CD, and multi-cloud strategies.
What Is Containerization?
Containerization Definition
Traditionally, application code was developed in a specific computing environment. Relocating application code to another environment, such as from computer systems to virtual machines (VMs), often resulted in bugs and errors. Containerization removes this problem by isolating application code and dependencies in a separate user space known as a container. As containers are small and lightweight, they require less startup time, enabling development and operational teams to quickly test and run applications on any environment, platform, or infrastructure. This drives higher efficiency by enabling developers to create, run, and deploy applications faster and more securely.
A Deeper Look at How Containers Work
When we refer to the magic of containers, we're highlighting some impressive kernel engineering. Unlike VMs, containers don't emulate an entire system. Instead, they rely on a set of advanced features within the host OS’s kernel to establish a secure, isolated environment for your application.
Picture it this way—your host computer runs a single OS, and all containers share the same kernel. However, each container is made to believe it operates in its own separate space. This is accomplished using two main technologies: namespaces and control groups (cgroups).
- Namespaces: These provide the primary layer of isolation. A namespace divides kernel resources, so each process sees only its own set. For instance, a PID namespace gives a container its own process list, hiding other processes from view. A network namespace supplies a unique network stack, including its own IP addresses and ports. There are also namespaces for user IDs, mounts, and inter-process communication, making each container feel like a separate machine.
- cgroups: While namespaces offer isolation, cgroups focus on controlling resources. They let you specify how much CPU, memory, disk I/O, and network bandwidth a container can use. This is vital for system stability and performance, ensuring no single container can monopolize resources and affect others.
When you execute a command such as docker run [your-image], the container engine handles several tasks for you:
- It retrieves the container image, which consists of multiple layers; these layers are stacked, allowing efficient reuse of base images
- It employs a container runtime (such as containerd or cri-o) to establish a new, isolated setting
- It configures the necessary namespaces and cgroups to sandbox the container and manage its resources
- It starts your application's process within this environment
The real advantage is how lightweight this process is. Because containers don't require a full guest OS, they start in seconds, use fewer resources, and can be deployed in greater numbers on a single server. This leads to greater cost savings and efficient resource usage.
Containers versus Virtual Machines
A few years back, we tackled the notorious "works on my machine" problem using virtual machines. VMs were a significant improvement, but containers have pushed matters further.
Here’s what’s important:
- OS Overhead: VMs are like apartment buildings where each unit has its own independent electrical and plumbing systems. Every VM runs its own guest OS, which consumes considerable disk space, memory, and CPU. Containers, on the other hand, resemble apartments sharing a single, efficiently managed electrical and plumbing system—the host OS kernel. This makes containers extremely lightweight.
- Speed and Agility: Containers don’t need to boot a complete OS, so they start in seconds rather than minutes. This allows for quick creation and removal, making them ideal for agile development and rapid deployment.
- Portability: VMs offer some level of portability, but transferring large VM images can take time. Containers are much smaller and more self-contained, making them significantly more portable and enabling more consistent deployments across environments.
- Resource Efficiency: Since containers share the host kernel, you can run many more of them on a single server than VMs, resulting in improved resource efficiency and greater cost-effectiveness.
What Are the Benefits of Containerization?
- High Portability of Applications: One of the major benefits of containers is they enable developers to move the containerized applications from one server to many servers quickly. Unlike a traditional computing environment, where the transfer of applications from one system to another may lead to integration issues with the OS, the transfer of containerized applications is much easier and faster due to their high portability, which reduces inconsistencies.
- Rapid Development Environment: Containerization offers faster feedback on application performance, enabling development teams to make changes in the source code if necessary. It also allows development teams to track those changes as soon as the application starts running. This helps in promoting a rapid development environment and enhancing productivity. Additionally, it saves time and increases efficiency by reducing dependency errors and simplifying the application installation process.
- Improved Scalability: Containerization allows applications to scale instantly. By adding or removing resources from the containers, teams can scale specific functions of the application in real time without affecting the performance of the entire application. For instance, developers can scale database components without impacting the front-end servers.
- Enhanced Security: Containerization provides enhanced security by encapsulating all the application's crucial information, such as code and functionalities. This allows for quick and easy sharing of specific resources among internal and external teams and provides enhanced security of application resources.
- Simple and Fast Deployment: Containerization simplifies and speeds up the application deployment and configuration process. Containers are small and lightweight, so they boot faster and require fewer resources for their deployment. Additionally, they can be deployed on multiple virtual servers and different cloud platforms, such as Google Cloud and Amazon Web Services (AWS).
Typical Container Use Cases
Discussing the true value of containers means addressing some of the toughest problems in contemporary IT. Containers are now essential to the way we develop and operate software. Below are some of the most frequent and influential ways containers are used.
Use Case #1: Simplifying the DevOps Pipeline
Consistency is crucial for DevOps teams. Developers create code on their laptops, testers run it in staging, and operations deploys it to production. Containers address the "it works on my machine" issue by packaging the application with all its dependencies. This ensures the code you write, test, and deploy remains identical across environments. Such consistency and portability greatly enhance the continuous integration and continuous deployment (CI/CD) pipeline, enabling faster and more reliable feature delivery. Containers are ideal for DevOps workflows.
Use Case #2: Migrating Legacy Applications
Do you have an old application running on a physical server? Many organizations face this challenge. Rewriting a monolithic application is often costly and time-consuming. However, containers offer an alternative. You can "lift and shift" the application into a container, encapsulating both the app and its environment. This makes it much simpler to move to a modern, scalable infrastructure—whether private or public cloud. It’s a practical first move toward digital transformation and cloud migration without the high costs of a complete redesign.
Use Case #3: Supporting Hybrid and Multi-Cloud Approaches
Many organizations do not rely solely on a single cloud provider. Some retain sensitive information on-premises, while others utilize multiple clouds for various services. Containers are ideally suited for these scenarios. Since containers operate consistently across environments, they offer deployment flexibility, allowing you to shift workloads between your on-premises data center and public clouds, or from AWS to Azure. This adaptability helps you avoid being locked into one vendor and enables you to select the most suitable platform for each workload, resulting in a truly hybrid and multi-cloud environment. You can also leverage specialized platforms such as OpenShift on IBM Cloud to oversee your container deployments across different cloud providers.
Use Case #4: Driving the Future of Technology
Containers also play a crucial role in advancing technologies such as the Internet of Things (IoT) and edge computing. IoT devices and edge servers typically have limited processing power. Because containers are lightweight and require minimal resources, they are ideal for running applications on these devices. Container orchestration can be used for IoT and edge computing workload management, enabling centralized management and updates of applications on thousands of devices—a transformative capability for industries such as manufacturing and healthcare. This approach simplifies the deployment and management of cloud-native applications that are built for scalability and resilience from the outset.
Microservices versus Containerization
If containerization is the car, microservices are the engine, wheels, and steering wheel—distinct components that each play a vital role but must work together for the system to function. A microservices architecture breaks down a large, monolithic application into a collection of smaller, independently deployable services, each responsible for a specific business capability. This approach allows teams to develop, test, and deploy these services separately, improving flexibility and resilience.
Containers provide the perfect runtime environment for microservices due to:
- Isolation: Each microservice runs inside its own container, ensuring its dependencies and configurations are kept separate from other services, which reduces the risk of conflicts
- Independent Deployment: You can update, roll back, or deploy a single microservice without affecting the operation of the rest of the application, enabling more frequent and safer releases
- Scalability: Individual microservices can be scaled up or down based on their unique resource requirements, making it much more efficient than scaling an entire monolithic application and allowing you to handle varying loads for different parts of your system
Containers and Cloud Computing
Containerization and cloud computing are a natural pairing, much like a keyboard complements a mouse. Containers are ideal for the cloud due to their flexibility and ability to scale. They allow applications to be packaged with all their dependencies, making deployment and management much easier across different environments. This portability ensures applications run consistently regardless of where they are deployed, whether on a developer's laptop, in a private data center, or in the public cloud.
- Hybrid and Multi-Cloud: Containers make it simple to move workloads between your on-premises data center and public cloud environments, supporting genuine hybrid cloud and multi-cloud approaches. This flexibility means organizations can avoid vendor lock-in and optimize their infrastructure costs by choosing the best environment for each workload.
- Containers as a Service: Cloud providers offer managed solutions such as Amazon Elastic Container Service and Google Kubernetes Engine, allowing you to run containers at scale without handling the underlying infrastructure yourself. These services simplify container orchestration, scaling, and security, enabling teams to focus on building and deploying applications rather than managing servers.
- Serverless Computing: Although containers offer significant flexibility, serverless computing is also an option for straightforward, event-driven tasks where you pay only for what you use. Containers provide greater control, while serverless delivers maximum simplicity and cost-effectiveness for particular scenarios. Depending on your application’s needs, you can choose between containers for complex, long-running workloads and serverless for lightweight, on-demand functions.
Orchestrating the Swarm: The Rise of Kubernetes
Once you have more than a few containers, managing them can quickly become a hassle. That’s where container orchestration steps in. Think of it as the brain behind your containerized applications, taking over routine management tasks such as starting, stopping, and monitoring containers, so you don’t have to handle everything manually.
Kubernetes, the leading solution for container orchestration, enables you to:
- Automate Deployment: You only need to define what applications you want to run, and Kubernetes handles the deployment process automatically. Whether you need to roll out updates or revert to previous versions, the process is seamless and requires minimal effort.
- Scale Your Apps: Kubernetes can automatically adjust the number of running containers to match the current workload, ensuring your application performs well during traffic spikes and conserves resources during quieter periods.
- Manage Resources: Kubernetes intelligently allocates CPU, memory, and storage, making sure containers are distributed efficiently across your infrastructure for optimal performance and cost-effectiveness.
- Provide Fault Tolerance: If a container or an entire server fails, Kubernetes detects the issue and automatically restarts the affected containers on healthy nodes, minimizing downtime and keeping your application available.
We believe Kubernetes is an essential tool for any IT professional responsible for managing containers at scale, helping to simplify operations and improve reliability.
Advanced Container Security Practices
When it comes to securing containers, you've got to think in layers. Security isn't only a single tool or a one-time check—it's a continuous process involving the entire lifecycle of your containers, from development to production.
One of the most critical aspects is the container image itself. An image is built on layers, often starting with a public base image. If the base image has a known vulnerability, every image you build on top of it will inherit the same risk. This is why vulnerability scanning is so important. You can integrate security scanners into your CI/CD pipeline to automatically check for security issues before an image ever gets to production.
Beyond the image, it's crucial to think about runtime security. Once a container is running, how do you ensure it isn't doing something it shouldn't? This is where container runtime security tools come in. They can monitor container activity and alert you to suspicious behavior, such as a web server trying to access the host's file system or a process attempting to escalate its privileges. This is a vital layer of defense against zero-day exploits.
You also need to apply the principle of least privilege to your containers and the users who manage them. A container should only have the permissions it needs to perform its function. For example, it's a bad idea to run a container with root privileges unless absolutely necessary. Similarly, access to your container orchestration platform, such as Kubernetes, should be tightly controlled with role-based access control (RBAC) to ensure only authorized users can deploy or modify containers.
Finally, don't overlook network security. By default, containers on the same host can often communicate freely with each other. This is where network policies become essential. They allow you to define rules for how containers can talk to each other and to the outside world. Think of it as a firewall for your containerized network, ensuring each container can only communicate with the services it's supposed to. Using these layered approaches helps you build a more robust and resilient container environment.
Leading Application Containerization Service Providers
The container ecosystem has many great players. Here are some of the heavy hitters and other important platforms you'll encounter:
- Docker: Docker is an open-source platform that was instrumental in popularizing container technology; it provides the tools to build, share, and run containers with a simple workflow
- Kubernetes: We mentioned Kubernetes before, but it's worth highlighting again as the go-to container orchestration platform; it automates the deployment, scaling, and management of your containerized applications
- Open Container Initiative: This initiative was created to establish open standards for containers, ensuring interoperability between different container runtimes and tools
- Linux Containers: This is an older technology that provides a way to run multiple isolated Linux environments on a single host; it’s still in use, but many have moved to Docker and Kubernetes for their more user-friendly tooling
- Windows Server Containers: This is Microsoft's native container technology for Windows, which provides a way to run Windows applications in a containerized environment
Other players in the space include CoreOS rkt, Docker Swarm, and containerd, which are all crucial parts of the larger container landscape.
What Is Containerization?
Containerization Definition
Traditionally, application code was developed in a specific computing environment. Relocating application code to another environment, such as from computer systems to virtual machines (VMs), often resulted in bugs and errors. Containerization removes this problem by isolating application code and dependencies in a separate user space known as a container. As containers are small and lightweight, they require less startup time, enabling development and operational teams to quickly test and run applications on any environment, platform, or infrastructure. This drives higher efficiency by enabling developers to create, run, and deploy applications faster and more securely.
A Deeper Look at How Containers Work
When we refer to the magic of containers, we're highlighting some impressive kernel engineering. Unlike VMs, containers don't emulate an entire system. Instead, they rely on a set of advanced features within the host OS’s kernel to establish a secure, isolated environment for your application.
Picture it this way—your host computer runs a single OS, and all containers share the same kernel. However, each container is made to believe it operates in its own separate space. This is accomplished using two main technologies: namespaces and control groups (cgroups).
- Namespaces: These provide the primary layer of isolation. A namespace divides kernel resources, so each process sees only its own set. For instance, a PID namespace gives a container its own process list, hiding other processes from view. A network namespace supplies a unique network stack, including its own IP addresses and ports. There are also namespaces for user IDs, mounts, and inter-process communication, making each container feel like a separate machine.
- cgroups: While namespaces offer isolation, cgroups focus on controlling resources. They let you specify how much CPU, memory, disk I/O, and network bandwidth a container can use. This is vital for system stability and performance, ensuring no single container can monopolize resources and affect others.
When you execute a command such as docker run [your-image], the container engine handles several tasks for you:
- It retrieves the container image, which consists of multiple layers; these layers are stacked, allowing efficient reuse of base images
- It employs a container runtime (such as containerd or cri-o) to establish a new, isolated setting
- It configures the necessary namespaces and cgroups to sandbox the container and manage its resources
- It starts your application's process within this environment
The real advantage is how lightweight this process is. Because containers don't require a full guest OS, they start in seconds, use fewer resources, and can be deployed in greater numbers on a single server. This leads to greater cost savings and efficient resource usage.
Containers versus Virtual Machines
A few years back, we tackled the notorious "works on my machine" problem using virtual machines. VMs were a significant improvement, but containers have pushed matters further.
Here’s what’s important:
- OS Overhead: VMs are like apartment buildings where each unit has its own independent electrical and plumbing systems. Every VM runs its own guest OS, which consumes considerable disk space, memory, and CPU. Containers, on the other hand, resemble apartments sharing a single, efficiently managed electrical and plumbing system—the host OS kernel. This makes containers extremely lightweight.
- Speed and Agility: Containers don’t need to boot a complete OS, so they start in seconds rather than minutes. This allows for quick creation and removal, making them ideal for agile development and rapid deployment.
- Portability: VMs offer some level of portability, but transferring large VM images can take time. Containers are much smaller and more self-contained, making them significantly more portable and enabling more consistent deployments across environments.
- Resource Efficiency: Since containers share the host kernel, you can run many more of them on a single server than VMs, resulting in improved resource efficiency and greater cost-effectiveness.
What Are the Benefits of Containerization?
- High Portability of Applications: One of the major benefits of containers is they enable developers to move the containerized applications from one server to many servers quickly. Unlike a traditional computing environment, where the transfer of applications from one system to another may lead to integration issues with the OS, the transfer of containerized applications is much easier and faster due to their high portability, which reduces inconsistencies.
- Rapid Development Environment: Containerization offers faster feedback on application performance, enabling development teams to make changes in the source code if necessary. It also allows development teams to track those changes as soon as the application starts running. This helps in promoting a rapid development environment and enhancing productivity. Additionally, it saves time and increases efficiency by reducing dependency errors and simplifying the application installation process.
- Improved Scalability: Containerization allows applications to scale instantly. By adding or removing resources from the containers, teams can scale specific functions of the application in real time without affecting the performance of the entire application. For instance, developers can scale database components without impacting the front-end servers.
- Enhanced Security: Containerization provides enhanced security by encapsulating all the application's crucial information, such as code and functionalities. This allows for quick and easy sharing of specific resources among internal and external teams and provides enhanced security of application resources.
- Simple and Fast Deployment: Containerization simplifies and speeds up the application deployment and configuration process. Containers are small and lightweight, so they boot faster and require fewer resources for their deployment. Additionally, they can be deployed on multiple virtual servers and different cloud platforms, such as Google Cloud and Amazon Web Services (AWS).
Typical Container Use Cases
Discussing the true value of containers means addressing some of the toughest problems in contemporary IT. Containers are now essential to the way we develop and operate software. Below are some of the most frequent and influential ways containers are used.
Use Case #1: Simplifying the DevOps Pipeline
Consistency is crucial for DevOps teams. Developers create code on their laptops, testers run it in staging, and operations deploys it to production. Containers address the "it works on my machine" issue by packaging the application with all its dependencies. This ensures the code you write, test, and deploy remains identical across environments. Such consistency and portability greatly enhance the continuous integration and continuous deployment (CI/CD) pipeline, enabling faster and more reliable feature delivery. Containers are ideal for DevOps workflows.
Use Case #2: Migrating Legacy Applications
Do you have an old application running on a physical server? Many organizations face this challenge. Rewriting a monolithic application is often costly and time-consuming. However, containers offer an alternative. You can "lift and shift" the application into a container, encapsulating both the app and its environment. This makes it much simpler to move to a modern, scalable infrastructure—whether private or public cloud. It’s a practical first move toward digital transformation and cloud migration without the high costs of a complete redesign.
Use Case #3: Supporting Hybrid and Multi-Cloud Approaches
Many organizations do not rely solely on a single cloud provider. Some retain sensitive information on-premises, while others utilize multiple clouds for various services. Containers are ideally suited for these scenarios. Since containers operate consistently across environments, they offer deployment flexibility, allowing you to shift workloads between your on-premises data center and public clouds, or from AWS to Azure. This adaptability helps you avoid being locked into one vendor and enables you to select the most suitable platform for each workload, resulting in a truly hybrid and multi-cloud environment. You can also leverage specialized platforms such as OpenShift on IBM Cloud to oversee your container deployments across different cloud providers.
Use Case #4: Driving the Future of Technology
Containers also play a crucial role in advancing technologies such as the Internet of Things (IoT) and edge computing. IoT devices and edge servers typically have limited processing power. Because containers are lightweight and require minimal resources, they are ideal for running applications on these devices. Container orchestration can be used for IoT and edge computing workload management, enabling centralized management and updates of applications on thousands of devices—a transformative capability for industries such as manufacturing and healthcare. This approach simplifies the deployment and management of cloud-native applications that are built for scalability and resilience from the outset.
Microservices versus Containerization
If containerization is the car, microservices are the engine, wheels, and steering wheel—distinct components that each play a vital role but must work together for the system to function. A microservices architecture breaks down a large, monolithic application into a collection of smaller, independently deployable services, each responsible for a specific business capability. This approach allows teams to develop, test, and deploy these services separately, improving flexibility and resilience.
Containers provide the perfect runtime environment for microservices due to:
- Isolation: Each microservice runs inside its own container, ensuring its dependencies and configurations are kept separate from other services, which reduces the risk of conflicts
- Independent Deployment: You can update, roll back, or deploy a single microservice without affecting the operation of the rest of the application, enabling more frequent and safer releases
- Scalability: Individual microservices can be scaled up or down based on their unique resource requirements, making it much more efficient than scaling an entire monolithic application and allowing you to handle varying loads for different parts of your system
Containers and Cloud Computing
Containerization and cloud computing are a natural pairing, much like a keyboard complements a mouse. Containers are ideal for the cloud due to their flexibility and ability to scale. They allow applications to be packaged with all their dependencies, making deployment and management much easier across different environments. This portability ensures applications run consistently regardless of where they are deployed, whether on a developer's laptop, in a private data center, or in the public cloud.
- Hybrid and Multi-Cloud: Containers make it simple to move workloads between your on-premises data center and public cloud environments, supporting genuine hybrid cloud and multi-cloud approaches. This flexibility means organizations can avoid vendor lock-in and optimize their infrastructure costs by choosing the best environment for each workload.
- Containers as a Service: Cloud providers offer managed solutions such as Amazon Elastic Container Service and Google Kubernetes Engine, allowing you to run containers at scale without handling the underlying infrastructure yourself. These services simplify container orchestration, scaling, and security, enabling teams to focus on building and deploying applications rather than managing servers.
- Serverless Computing: Although containers offer significant flexibility, serverless computing is also an option for straightforward, event-driven tasks where you pay only for what you use. Containers provide greater control, while serverless delivers maximum simplicity and cost-effectiveness for particular scenarios. Depending on your application’s needs, you can choose between containers for complex, long-running workloads and serverless for lightweight, on-demand functions.
Orchestrating the Swarm: The Rise of Kubernetes
Once you have more than a few containers, managing them can quickly become a hassle. That’s where container orchestration steps in. Think of it as the brain behind your containerized applications, taking over routine management tasks such as starting, stopping, and monitoring containers, so you don’t have to handle everything manually.
Kubernetes, the leading solution for container orchestration, enables you to:
- Automate Deployment: You only need to define what applications you want to run, and Kubernetes handles the deployment process automatically. Whether you need to roll out updates or revert to previous versions, the process is seamless and requires minimal effort.
- Scale Your Apps: Kubernetes can automatically adjust the number of running containers to match the current workload, ensuring your application performs well during traffic spikes and conserves resources during quieter periods.
- Manage Resources: Kubernetes intelligently allocates CPU, memory, and storage, making sure containers are distributed efficiently across your infrastructure for optimal performance and cost-effectiveness.
- Provide Fault Tolerance: If a container or an entire server fails, Kubernetes detects the issue and automatically restarts the affected containers on healthy nodes, minimizing downtime and keeping your application available.
We believe Kubernetes is an essential tool for any IT professional responsible for managing containers at scale, helping to simplify operations and improve reliability.
Advanced Container Security Practices
When it comes to securing containers, you've got to think in layers. Security isn't only a single tool or a one-time check—it's a continuous process involving the entire lifecycle of your containers, from development to production.
One of the most critical aspects is the container image itself. An image is built on layers, often starting with a public base image. If the base image has a known vulnerability, every image you build on top of it will inherit the same risk. This is why vulnerability scanning is so important. You can integrate security scanners into your CI/CD pipeline to automatically check for security issues before an image ever gets to production.
Beyond the image, it's crucial to think about runtime security. Once a container is running, how do you ensure it isn't doing something it shouldn't? This is where container runtime security tools come in. They can monitor container activity and alert you to suspicious behavior, such as a web server trying to access the host's file system or a process attempting to escalate its privileges. This is a vital layer of defense against zero-day exploits.
You also need to apply the principle of least privilege to your containers and the users who manage them. A container should only have the permissions it needs to perform its function. For example, it's a bad idea to run a container with root privileges unless absolutely necessary. Similarly, access to your container orchestration platform, such as Kubernetes, should be tightly controlled with role-based access control (RBAC) to ensure only authorized users can deploy or modify containers.
Finally, don't overlook network security. By default, containers on the same host can often communicate freely with each other. This is where network policies become essential. They allow you to define rules for how containers can talk to each other and to the outside world. Think of it as a firewall for your containerized network, ensuring each container can only communicate with the services it's supposed to. Using these layered approaches helps you build a more robust and resilient container environment.
Leading Application Containerization Service Providers
The container ecosystem has many great players. Here are some of the heavy hitters and other important platforms you'll encounter:
- Docker: Docker is an open-source platform that was instrumental in popularizing container technology; it provides the tools to build, share, and run containers with a simple workflow
- Kubernetes: We mentioned Kubernetes before, but it's worth highlighting again as the go-to container orchestration platform; it automates the deployment, scaling, and management of your containerized applications
- Open Container Initiative: This initiative was created to establish open standards for containers, ensuring interoperability between different container runtimes and tools
- Linux Containers: This is an older technology that provides a way to run multiple isolated Linux environments on a single host; it’s still in use, but many have moved to Docker and Kubernetes for their more user-friendly tooling
- Windows Server Containers: This is Microsoft's native container technology for Windows, which provides a way to run Windows applications in a containerized environment
Other players in the space include CoreOS rkt, Docker Swarm, and containerd, which are all crucial parts of the larger container landscape.
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