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David Fagbuyiro
David Fagbuyiro

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Kubernetes - Physical Servers vs Virtual Machines vs Containers

In the modern era, Kubernetes has brought about a revolution in the deployment and management of applications. It provides a scalable and efficient platform for orchestrating containerized applications. However, when it comes to choosing the underlying infrastructure for running Kubernetes, there are multiple options to consider: physical servers, virtual machines (VMs), and containers. Each option has its own characteristics, benefits, and challenges.
In this article, we will go through the distinctions among these choices and discuss their implications within the framework of Kubernetes deployments.
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Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of applications. It allows developers to focus on writing code without worrying about the underlying infrastructure. Kubernetes achieves this by abstracting away the complexities of managing distributed systems and providing a consistent environment for running containerized applications.

Physical servers

Physical servers are the traditional approach to hosting applications. They are physical machines dedicated to running specific workloads. In the context of Kubernetes, physical servers can be utilized by running Kubernetes directly on the bare metal hardware.
Physical servers offer several benefits. They provide direct access to hardware resources, resulting in better performance and lower latency. They also provide more control over the infrastructure since there is no virtualization layer involved. Moreover, physical servers can be cost-effective for certain use cases, especially when the workload requires a high level of hardware customization.
However, physical servers have limitations in Kubernetes deployments. They lack the flexibility and agility provided by virtualization and containerization. Scaling and provisioning resources can be time-consuming and cumbersome. Additionally, physical servers do not provide the same level of isolation as virtual machines or containers, which may limit application portability and increase the risk of resource conflicts.
Below is a graphical representation of Physical servers:

Image description

Image source: GeeksforGeeks.org 

Virtual Machines

Virtual machines are emulations of physical computers that run on top of a hypervisor. Each virtual machine operates as a self-contained system with its own operating system and resources. In the context of Kubernetes, virtual machines can be used to create a cluster where each virtual machine acts as a worker node.
Using virtual machines in Kubernetes offers several advantages. VMs provide strong isolation between workloads, ensuring that applications do not interfere with each other. They also offer flexibility in terms of resource allocation and scalability. Virtual machines can be easily provisioned and managed, allowing for dynamic scaling based on workload demands. Additionally, VMs enable the use of different operating systems within a single Kubernetes cluster, providing more versatility for application deployment.
However, virtual machines come with certain challenges. They introduce an additional layer of abstraction, which can impact performance and increase resource overhead. Running multiple virtual machines requires more resources compared to running containers directly on physical servers. Moreover, the management of virtual machines adds complexity to the overall Kubernetes infrastructure, requiring additional tools and configuration.

Graphical illustration of a Virtual Machine.

Image description

Graphical illustration of a Virtual Machine. Image Source.

Virtualization improves resource efficiency on a physical server, improves scalability by allowing applications to be quickly added or changed, lowers hardware costs, and much more. You can offer a collection of physical resources as a cluster of disposable virtual machines using virtualization.
On top of the virtualized hardware, each VM is a whole machine with all of its components, including its own operating system.

Containers

Containers are comparable to virtual machines (VMs), except they allow programmes to share the same operating system (OS). As a result, containers are considered light. A container, like a virtual machine, has its own filesystem, CPU, memory, process space, and other resources. They are portable across clouds and OS distributions because they are divorced from the underlying infrastructure.
Containers offer numerous benefits for Kubernetes deployments. They provide excellent isolation between applications, ensuring that each container operates independently without interfering with others. Containers are highly portable and can be easily moved between different Kubernetes clusters or environments. They also enable efficient resource utilization, allowing for higher density and scalability compared to virtual machines.
Below is a graphical illustration of a container.

Image description

Container: ImageSource: GeeksforGeeks.org 

  • Containers have grown in popularity as a result of their additional benefits, which include:
  • Container image creation is more simple and efficient than using VM images for developing and deploying agile applications.
  • Continuous development, integration, and deployment: enables the creation and deployment of dependable and frequent container images, as well as quick and efficient rollbacks (due to image immutability).
  • Separation of concerns between development and operations: produce application container images during build/release rather than deployment, isolating apps from infrastructure.
  • Observability: this feature exposes not just OS-level data and metrics, but also application health and other signals.
  • Consistency in the environment during development, testing, and production: On a laptop, it works the same as it does in the cloud.
  • Portability of cloud and operating system distributions: Runs on Ubuntu, RHEL, CoreOS, on-premises, on major public clouds, and everywhere else.
  • Application-centric management: Moves away from operating an OS on virtual hardware and toward running an application on an OS with logical resources.

Comparison and Evaluation

When choosing between physical servers, virtual machines, and containers in Kubernetes, several factors need to be considered:

Performance considerations
Physical servers generally offer the highest performance since they have direct access to hardware resources. Virtual machines introduce a slight performance overhead due to virtualization. Containers have minimal performance overhead, as they share the host's kernel.

Scalability considerations
Physical servers may require longer provisioning times and may not be as easily scalable compared to virtual machines and containers. VMs and containers can be rapidly scaled up or down based on workload demands.

Resource utilization and efficiency
Physical servers can suffer from underutilization if not properly managed. Virtual machines allow for better resource utilization by running multiple VMs on a single server. Containers consume fewer resources compared to VMs, resulting in higher resource efficiency.

Considering these factors and aligning them with your specific requirements will help you make an informed decision.

Use Cases and Recommendations

The choice of infrastructure for running Kubernetes depends on specific use cases and requirements:

  1. Physical servers are suitable for resource-intensive applications that require maximum performance and control. They are commonly used in environments where specialized hardware is required, such as GPU-accelerated workloads or high-performance computing.

  2. Virtual machines offer a balance between performance, isolation, and scalability. They are a flexible choice for general-purpose workloads and environments.

Conclusion

Finally, there are three main types of infrastructure that can be used with Kubernetes: physical servers, virtual machines, and containers. Each type of infrastructure has its own advantages and disadvantages. If you are looking for scalability, flexibility, and cost-effectiveness, then virtual machines or containers are better options.
For more information on Kubernetes, you can try checking out this Kubernetes Tutorial for Beginners: Basic Concepts. This guide goes through Kubernetes features, basic terms, and concepts regarding how to get started running your own containerized solutions.

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