Containers

Why containers?

Container technology addresses many challenges faced in modern software development, deployment, and operations. Its combination of lightweight, portable, and isolated environments, along with the tooling ecosystem and alignment with modern architecture practices, has made it a popular choice for organizations aiming to improve their software development and deployment processes.

In order to understand the technology, and its future direction, one must understand what were the challenges faced in the past. Let's look at it.

First Era - Bare Metal

In the early days of computing, applications were deployed directly onto physical hardware, referred to as "bare metal." Each application ran on its own dedicated hardware, leading to resource inefficiencies and difficulties in scaling. This approach lacked flexibility, as hardware resources were tightly coupled to specific applications.

• In the early decades of computing, there was no concept of virtualization or containerization.
• Applications were developed to run on specific hardware configurations.
• Scaling required purchasing additional hardware and manually deploying applications on new machines.
• There was no isolation between applications, which could lead to resource contention and security risks.
• The lack of abstraction meant that software dependencies and hardware characteristics were tightly intertwined. This can make it extremely difficult to manage and maintain software that has conflicting requirements such as different version of low-level library (due to how they were initially packaged).

Second Era - Virtual Machine

Virtualization introduced the concept of running multiple instances of an operating system on a single physical machine. Virtual Machines (VMs) allowed for better resource utilization and isolation compared to bare metal deployment. Each of these VMs hosted its own guest operating system and applications, enabling greater flexibility and easier management.

Here's how VM technology works:

1. Hypervisor: At the core of VM technology is a software layer known as a hypervisor. The hypervisor manages and allocates the physical resources of the host machine, such as CPU, memory, storage, and networking, among the virtual machines. There are two main types of hypervisors:

   • Type 1 Hypervisor (Bare-metal): This hypervisor runs directly on the host's hardware, without the need for a host OS. Examples include VMware vSphere/ESXi, Microsoft Hyper-V, and Xen.
   • Type 2 Hypervisor (Hosted): This hypervisor runs on top of a host OS. It provides a layer of abstraction between the VMs and the host hardware. Examples include VMware Workstation, Oracle VirtualBox, and Parallels Desktop.

2. Virtualization Layer: The hypervisor creates and manages virtual machines by emulating the hardware of a physical computer. Each virtual machine has its own virtualized hardware components, including a virtual CPU, memory, storage, network interfaces, and more.

3. Guest Operating Systems: Within each virtual machine, you can install a guest operating system of your choice. These guest OSes can be different from the host OS and can include various versions of Windows, Linux, or other operating systems.

4. Isolation: Virtual machines are isolated from each other, meaning that the activities and processes within one VM do not affect the others. This isolation provides security and stability, making VMs suitable for running different applications with varying requirements.

5. Portability: VMs encapsulate the entire environment of an application, including the OS and its dependencies. This makes VMs highly portable, allowing you to move them between different physical machines or cloud environments with relative ease.

6. Resource Management: The hypervisor allocates physical resources to each virtual machine based on predefined settings or dynamic resource allocation. This allows you to control the amount of CPU, memory, and storage that each VM can use.

7. Snapshots and Cloning: VM technology often supports features like snapshots (capturing the state of a VM at a specific moment) and cloning (creating duplicate copies of a VM). These features are useful for backup, testing, and development purposes.

8. Isolation and Security: VMs provide strong isolation between applications, making them suitable for scenarios where security and separation are critical, such as hosting multiple tenants on a single physical server.

9. Overhead: While VMs offer excellent isolation, they can also introduce some overhead due to the virtualization layer and the emulation of hardware components. This overhead can impact performance, especially in situations where high performance is required.

VM technology has been widely used in data centers, development environments, testing environments, and cloud computing. It allows for efficient resource utilization, server consolidation, and the ability to run multiple different operating systems and applications on a single physical machine. The shift to virtual machine deployment addressed some challenges of bare metal, such as better resource utilization and enhanced isolation. However, VMs still had overhead due to running multiple complete operating systems on a single physical machine. With the rise of container technology, which offers even lighter-weight isolation, VMs are sometimes being replaced or complemented by containers in certain use cases.

Third Era - Container

Containers introduced lightweight and efficient application isolation by sharing the host OS kernel and libraries. Containers encapsulated applications and their dependencies, providing consistency between development, testing, and production environments. This approach significantly reduced resource overhead and allowed for faster application deployment and scaling.

Here's how container technology works:

1. Isolation: Containers provide process and filesystem-level isolation, allowing multiple containers to run on the same host without interfering with each other. Each container has its own filesystem, libraries, and runtime, which ensures that applications and their dependencies are encapsulated and don't clash with one another.

2. Shared OS Kernel: Unlike traditional virtualization, where each virtual machine (VM) runs a separate operating system, containers share the host machine's operating system kernel. This shared kernel results in faster startup times and reduced overhead compared to VMs.

3. Images: Containers are created from container images, which are lightweight and contain the application code, runtime, libraries, and other dependencies required to run the application. These images are defined using a configuration file (like Dockerfile in Docker) and can be versioned and stored in container registries.

4. Orchestration: Container orchestration tools, such as Kubernetes, allow you to manage and automate the deployment, scaling, and management of containerized applications. These tools help distribute containers across a cluster of machines, ensuring high availability, load balancing, and efficient resource utilization.

5. Portability: Containers are designed to be highly portable, meaning you can build a containerized application on your development machine and run it on any platform that supports the container runtime. This consistency between development, testing, and production environments reduces "it works on my machine" issues and makes it easier to troubleshoot and debug.

6. Resource Efficiency: Since containers share the host's operating system kernel, they consume fewer resources compared to running multiple VMs with separate kernels. This efficiency allows you to pack more containers onto a single physical machine, improving resource utilization.

7. Fast Deployment: Containers start up quickly and can be spun up or down on-demand, making them ideal for microservices architectures and agile development practices.

8. Versioning and Rollbacks: Container images can be versioned, allowing you to roll back to previous versions of an application by simply switching to an older image. This enhances application maintainability and simplifies the process of updating or reverting changes.

One of the most popular container technologies is Docker, introduced in 2013, played a pivotal role in popularizing this technology. It leverages Linux namespaces and control groups (cgroups) for process isolation and resource management. Container images contained the application code, runtime, libraries, and configuration, ensuring consistent behavior across environments. This allow them to promote the technology as "build once, run anywhere". Containerization reduced the "it works on my machine" problem by providing reproducible environments.

In general, the shift to container deployment addressed the resource inefficiencies of VMs by providing lightweight isolation and efficient resource sharing. It also improved portability, consistency, and speed of application deployment.

Container Development

The history of containers is a story of technological evolution driven by the need for more efficient and lightweight methods of application deployment, isolation, and management. The concept of containers has undergone significant advancements over the years, transforming the landscape of software development and deployment. Here's a chronological overview of the development history of containers:

1. Chroot and Jails (1979-2000s): The concept of containment began with the introduction of the Unix "chroot" command in 1979, which allowed processes to be isolated within a designated directory. In the 2000s, FreeBSD introduced "jails," which extended the idea of chroot to provide enhanced process isolation, filesystem separation, and network isolation.

2. Linux-VServer (2001-2004): Developed by Jacques Gélinas in the early 2000s, Linux-VServer allowed multiple isolated instances of a Linux operating system to run on a single physical machine. This technology provided rudimentary containerization capabilities by isolating processes, filesystems, and network interfaces.

3. OpenVZ (2005-2011): OpenVZ expanded on the Linux-VServer concept, enabling more efficient resource allocation and better isolation by utilizing a shared Linux kernel. It allowed for better resource utilization and more effective isolation, but it still lacked full portability due to its reliance on a specific kernel version.

4. cgroups and Namespaces (2007-2010): In 2007, control groups (cgroups) were introduced into the Linux kernel. Cgroups allowed for resource allocation and limiting of resources such as CPU, memory, and disk I/O. Around the same time, Linux namespaces were also introduced, enabling the isolation of various aspects of the operating system, such as processes, network, and filesystems.

5. Docker (2013): Docker, founded by Solomon Hykes, popularized and revolutionized containerization. Released in 2013, Docker combined cgroups, namespaces, and other technologies into a user-friendly platform that made it easy to create, distribute, and run containers. Docker's standardized format and tooling accelerated container adoption and made it possible to run applications consistently across different environments.

6. Container Runtimes and Standards (2015-2017): As the container ecosystem expanded, the Open Container Initiative (OCI) was formed in 2015 with the goal of establishing open industry standards for container formats and runtimes. This led to the creation of the Docker image format and the development of runtimes like rkt (pronounced "rocket") and runc (used by Docker and other container platforms).

7. Kubernetes and Orchestration (2014-present): With the rise of containers, managing and orchestrating them became a challenge. Docker Swarm and Google's Kubernetes, released in 2014 as an open-source project, provided a powerful solution for automating the deployment, scaling, and management of containerized applications. Kubernetes wins against all competitors due to its ease of scalibility. Kubernetes enabled the creation of complex microservices architectures and introduced concepts like pods, services, and declarative configuration.

8. Container Ecosystem Expansion (2015-present): The container ecosystem continued to expand with various tools and platforms focusing on specific use cases. Container orchestration platforms like Mesos, Amazon ECS , and Nomad (from HashiCorp) emerged, offering alternatives to Kubernetes. Additionally, container security, monitoring, and networking solutions developed to support the growing demand for containerized applications. It must be noted, however, that the whole container ecosystem now largely focus on Kubenetes or Nomad technology with cloud provider building plugins for these technologies.

9. Serverless and Cloud-Native (2010s-present): The concepts of serverless computing and cloud-native applications further transformed the way applications were developed and deployed. Serverless platforms abstract away the underlying infrastructure, allowing developers to focus solely on code, while cloud-native practices emphasize building applications as a collection of loosely coupled microservices.

The development of containers has drastically changed the software development landscape, making application deployment faster, more scalable, and more efficient. The ongoing evolution of container technologies continues to drive innovation and reshape how applications are developed, deployed, and managed.

Fourth Era - Container Orchestration

As container adoption grew, the need for automating deployment, scaling, and management of containerized applications emerged. Container orchestration platforms, like Kubernetes, were developed to address these complexities. Here are some key components and concepts of container orchestration technology:

1. Cluster Management: Container orchestration systems manage a cluster of machines, often referred to as nodes, that host and run containers. These machines can be physical servers, virtual machines, or cloud instances.

2. Container Orchestration Tools: Some of the most well-known container orchestration tools include Kubernetes, Docker Swarm, and Apache Mesos. These tools provide a framework for deploying and managing containerized applications at scale.

3. Container Lifecycle Management: Orchestration platforms handle the entire lifecycle of containers, including deployment, scaling, updating, and termination. They ensure that the desired number of containers are running at all times and automatically replace failed containers.

4. Service Discovery: In a distributed environment, containers need to discover and communicate with each other. Container orchestration tools offer service discovery mechanisms that allow containers to locate and interact with each other without needing to know their exact locations.

5. Load Balancing: Orchestration systems manage the distribution of incoming network traffic across multiple containers to ensure optimal performance and availability.

6. Horizontal Scaling: Containers can be scaled horizontally by creating more instances of a container to handle increased workload. Orchestration tools make it easy to scale up or down based on demand.

7. Self-Healing: Container orchestration platforms automatically detect when a container fails or becomes unresponsive and take corrective actions, such as restarting the container or replacing it with a healthy one.

8. Rolling Updates and Rollbacks: Orchestration systems allow you to update applications seamlessly by gradually replacing old containers with new ones, minimizing downtime. If an update causes issues, you can roll back to a previous version.

9. Resource Allocation: Orchestration tools help manage the allocation of computing resources like CPU and memory to ensure that containers have the necessary resources to run efficiently.

10. Configuration Management: Container orchestration platforms allow you to define and manage configurations for your containers, making it easier to ensure consistent behavior across different environments.

11. Stateful and Statelessness: Orchestration systems handle both stateful and stateless applications. Stateless applications store no data between requests, making them easier to scale, while stateful applications require persistent data storage and careful management during scaling and updates.

12. Persistent Storage: Orchestration tools offer mechanisms for managing persistent storage volumes that can be attached to containers, allowing stateful applications to retain data across container restarts or rescheduling.

13. Infrastructure Abstraction: Orchestration tools abstract the underlying infrastructure, so you can deploy and manage containers across various cloud providers or on-premises environments without rewriting your application code.

Container orchestration technology has revolutionized the way organizations build and manage their applications, enabling them to deploy complex, resilient, and scalable systems with relative ease. Among these technologies, Kubernetes, released by Google in 2014, has emerged as one of the most popular and powerful container orchestration platforms, offering a wide range of features for managing containerized applications.

The shift to container orchestration recognized the complexity of managing large-scale container deployments. Orchestration platforms automated tasks that were previously manual, enabling efficient scaling, failover, and management of containerized applications.

In summary, the evolution of production deployment concepts reflects a drive towards efficiency, isolation, portability, and automation. From bare metal to container orchestration, each era addressed the challenges of the previous one and provided innovative solutions to enhance application deployment, scalability, and management in an ever-evolving technological landscape.