What is Kubernetes and where is it used?

Contents:

• When to Use Kubernetes
• How Kubernetes Came to Be
• How Kubernetes Works
• How to Become a Kubernetes Specialist
• What Questions Are Asked in Interviews
• Risks of Using Kubernetes and Cloud Infrastructure
• Differences Between Solutions from Different Cloud Providers
• Disadvantages of Kubernetes
• Alternatives to Kubernetes
• Results

Cloud Solution Architect, based in France, works at Pluto Informatics. He holds a Linux Foundation System Administrator (LFCS) certification and is a Microsoft Azure Certified Expert. He also holds a Kubernetes Administrator and Security Specialist qualification, confirming his high level of professional expertise in cloud technologies and IT infrastructure management. Links play a key role in the structure of the internet, providing connections between different web pages. They help users find the information they need and also contribute to improving the SEO positioning of websites. It is important to use internal and external links correctly to increase the visibility of content in search engines. Internal links connect pages within a single site, which helps distribute traffic and improves indexing. External links pointing to other resources add authority and trust to your content. Link optimization involves using keywords in anchor text and creating high-quality content that attracts users and encourages them to share links. An effective linking strategy can significantly improve a website's search engine rankings and increase its traffic.

Kubernetes is a powerful container orchestrator developed at Google using the Go language. It significantly simplifies the process of managing containerized applications, automating their deployment, scaling, and management. Previously, solutions existed for creating and deploying virtual machines, such as Microsoft Hyper-V and VMware products, but Kubernetes offers a more flexible and efficient approach to resource management in cloud environments. This makes it an ideal choice for modern DevOps practices and microservices architecture.

Docker provides the ability to manage multiple containers simultaneously, making it an indispensable tool for developers. However, insufficient technologies existed for deploying large, multi-component products that use containers in their architecture. This creates a need for more comprehensive solutions to optimize the development and deployment of containerized applications. Using orchestration tools like Kubernetes can significantly simplify container management and scaling, ensuring service reliability and high availability.

Kubernetes was designed to automate the deployment of container clusters, providing the ability to flexibly configure policies and parameters. It supports Infrastructure as Code, which simplifies infrastructure management and improves the efficiency of application development and deployment processes.

Kubernetes enables more efficient allocation of server resources through the use of containers. Unlike virtual machines, which run separate copies of operating systems and require significant resources, containers are lightweight and faster. Kubernetes allows you to run multiple containers on a single server without having to create a separate operating system for each one. This significantly reduces resource costs and improves the overall performance of the infrastructure.

• Why Kubernetes is needed
• How Kubernetes appeared
• How Kubernetes works
• How to become a Kubernetes specialist
• What questions are asked during an interview

• Risks of using Kubernetes and cloud infrastructure
• Differences between solutions of different cloud providers
• Disadvantages of Kubernetes
• Alternatives to Kubernetes

When to use Kubernetes

Kubernetes is actively used by SRE engineers and DevOps specialists to improve the efficiency of application development and packaging. After developers write code and create program binaries, a specialist is needed to prepare images for hosting the application and set up a deployment pipeline. Kubernetes simplifies container management and automation, which facilitates faster and more reliable software delivery. Imagine that our application has a significant number of users, which requires significant resources to operate. Instead of building a supercomputer, the modern IT industry prefers to use distributed systems. These systems consist of many relatively weak servers that are combined to provide the necessary power and performance. This approach has many advantages: resources can be scaled as application demands grow, and individual servers can be easily replaced in the event of a failure. Distributed systems provide reliability and flexibility, making them an ideal solution for modern high-load applications. We have an application that must run on a distributed system consisting of dozens or even hundreds of servers. When using Docker or other containerization tools, each server must be configured and administered individually. This means that we cannot apply uniform configurations to the entire group of servers, which turns the process into partially manual work. Even if we create a set of automation scripts, they will not be universal and will require modifications for other cases. This leads to the need to develop new solutions for each unique scenario, which increases the time and effort spent on administration.

Kubernetes offers an effective solution for managing application infrastructure. With its help, we can set the necessary parameters, such as application resources, network architecture, and other aspects. Kubernetes takes over the management of connected servers, which significantly simplifies the tasks of administrators and developers. This reduces the time spent on routine operations and increases the overall efficiency of working with cloud and on-premises environments.

How Kubernetes Came to Be

The book "Site Reliability Engineering" discusses in detail Google's internal project - the Borg cluster management system. In 2014, Google open-sourced the project, and in 2015, in collaboration with the Linux Foundation, established the Cloud Native Computing Foundation (CNCF). The Kubernetes source code was donated to this foundation as part of Google's technical contribution. The CNCF actively develops open-source projects aimed at creating utilities and libraries for developing applications designed for cloud-native architectures. This collaboration marked an important step in the evolution of cloud technologies and contributed to the widespread adoption of containerization and microservices architecture in software development. Kubernetes is a graduate of the Cloud Native Computing Foundation (CNCF) and has reached Graduated Project status. This status was awarded upon reaching a stable release, confirming its maturity and readiness for widespread use in production. Kubernetes remains a key tool for managing containerized applications, providing scalability, automation, and high availability.

The first versions of Kubernetes had a more monolithic architecture and focused on running Docker in the background. With the development of the CNCF program, Kubernetes has evolved into a stable and extensible product, allowing for technology changes at every level of the virtual infrastructure. Currently, Kubernetes offers significant customization options: users can independently choose any technology for working with containers, storage, and networking. This makes Kubernetes a universal tool for managing containerized applications, providing flexibility and adaptability to specific business needs.

Kubernetes's development approach has contributed to its popularity as a solution for production systems and enterprise use. The platform has acquired additional security-focused components and improved the stability of resource and process management algorithms. This makes Kubernetes a reliable tool for deploying and managing containerized applications in modern IT infrastructures.

How Kubernetes Works

Kubernetes includes two key components: an architectural component that manages containers, and an interface that allows users to interact with the system. These core elements enable efficient deployment, scaling, and management of containerized applications in a cloud environment. Kubernetes streamlines resource management processes and automates updates, making it an indispensable tool for developers and system administrators.

• The Control Plane is the orchestrator, API, and configuration database.
• Node Pools are servers with available resources.

The Control Plane is managed by the Kubernetes Master Node server. Kubernetes nodes, called Worker Nodes, are grouped into a Node Pool. Typically, one Node Pool corresponds to a group of servers with similar characteristics. For example, separate pools can be created for Windows-based servers, Linux servers, and GPU-powered servers. This allows you to optimize resource management and simplify the deployment of applications in a Kubernetes cluster environment.

On each A kubelet agent is installed on a node, which is a separate physical server or virtual machine. This agent plays a vital role, receiving instructions from the Master Node and providing interaction with various components, drivers, and extensions for network security monitoring. This creates a reliable platform for deploying applications in Kubernetes.

In Kubernetes, an application itself is described through a deployment resource, which includes several pods. Each pod can contain one or more containers. Pods are the units of scaling in Kubernetes, forming the basis of the system. When selecting a node to run a specific application component, the smallest unit of resources is a pod, rather than a separate container or physical server. This simplifies resource management and allows the application to be effectively scaled depending on demand.

The Kubernetes component hierarchy includes several key elements. A Node Pool is formed from Worker Nodes, which run applications. An application is managed through a Deployment, which organizes pods. Each pod hosts containers containing the components necessary for the application to run. This structure allows for efficient resource management and application scaling in a cloud environment.

Kubernetes operates in a similar way to traditional clusters. The main component of the system is the Kubernetes Master Node, which manages the Control Plane and includes:

• API for administrators and developers;
• a configuration database with parameters for containers, applications, deployments, networks, and storage;
• an orchestrator or scheduler that runs containers.

Kubernetes is a powerful platform for managing containers, uniting nodes—servers with common characteristics. These nodes can be grouped into pools based on parameters such as the operating system (e.g., Windows or Linux), the presence of graphics processing units (GPUs), and other specific resources. Administrators define the characteristics of each pool, such as computing power, memory capacity, and available storage. Kubernetes then automatically allocates resources by identifying suitable nodes in the cluster and launching application pods on these nodes. This ensures optimized resource utilization and efficient load management in cloud and on-premises environments.

Kubernetes allows you to set a minimum and maximum number of pods for an application, allowing the system to maintain a stable number of running instances. However, managing and scaling the number of nodes, which are individual physical servers or virtual machines, is the responsibility of administrators, hypervisors, or cloud platforms such as Azure, GCP, and AWS. Kubernetes does not perform this task automatically.

If any infrastructure element fails, Kubernetes automatically takes action to correct the problem. For example, it can restart a pod or deployment to restore the system's compliance with the configurations loaded via the API and stored on the Master Node. This allows an application, whose components are divided into pods and containers, to operate in a resource space united in a Kubernetes cluster—a kind of container cloud. This ensures high availability and resilience for applications, allowing them to efficiently use resources and quickly adapt to changes in load.

How to Become a Kubernetes Specialist

Working as a Kubernetes administrator requires a deep understanding of the components and all aspects of the platform's resources. It can be thought of as a cloud within a cloud. Consider IaaS (Infrastructure as a Service) cloud services: they consist of several layers, such as storage, networking, compute, and virtualization. To successfully install and configure Kubernetes, you need to be well-versed in this entire stack. Understanding each element of the infrastructure not only allows for effective Kubernetes management but also troubleshooting, making administration more efficient and reliable.

Virtualization layers are also present within Kubernetes, implementing unique mechanisms for organizing virtual storage, virtual networks, and computing resources. Thus, two layers coexist within the infrastructure: a data center or IaaS cloud stack and a Kubernetes stack. This combination enables efficient resource management and optimized application performance in a cloud environment.

Ultimately, the administrator will need to understand everything except the "physical" network and basic concepts. By core concepts, I mean the following:

• what is a network,
• how to work with distributed storage,
• how to work with distributed computing resources.

When applying these concepts in your daily work with Kubernetes internals, you will need to thoroughly study the basics - understand the settings, choose the right tools, and master their functionality.

I work extensively in large enterprises, where certifications play a key role. All Kubernetes certifications are practical. To successfully pass these exams, it is not enough to simply select the correct answers or check boxes. You must demonstrate the ability to write configurations and commands within a limited time directly on the command line. For example, you need to create 25 configurations in an hour and a half, and this task is impossible to complete without a deep understanding of the topic.

For those who aspire to become an expert in Kubernetes, I strongly recommend preparing for certifications. The questions on the certification exams are no less challenging than those you might encounter in interviews. By completing the certification, you'll be confident in your knowledge and be able to successfully answer interview questions. Preparing for certification will not only deepen your knowledge but also increase your competitiveness in the cloud and containerization job market.

I hold the Certified Kubernetes Administrator (CKA) and Certified Kubernetes Security Specialist (CKS) certifications. I also hold the Certified Kubernetes Application Developer (CKAD) certification, offered by the Linux Foundation. It took me six months to earn these certifications, despite having worked with infrastructure for over six years. Earning these certifications validates my knowledge and skills in Kubernetes, which is important for DevOps and cloud professionals.

To prepare for the CKS exam, I completed the Killer Shell Support Team course on the Udemy platform. I also have a subscription to Pluralsight, which offers CKA-related courses, such as Certified Kubernetes Administrator (CKA). The Linux Foundation also offers preparatory training, but I found its text-and-diagram format rather boring. In contrast, offline training is more interactive and engaging. In such sessions, the instructor demonstrates all the necessary aspects in a short time and answers participants' questions. For a deeper understanding of Kubernetes security, I recommend checking out the CIS Kubernetes Benchmarks, which will help you better prepare for the exam.

I have two books from O'Reilly:

• Site Reliability Engineering
• Cloud Native DevOps with Kubernetes

YouTube offers many useful resources, especially the channels of Kubernetes ambassadors. A full list is available on the CNCF website. These channels analyze various case studies, demonstrate commands, and offer practical exercises, such as setting up micro-Kubernetes on a Raspberry Pi. I recommend checking out the videos from DevOps consultant Nana Janashia, which can significantly deepen your knowledge of Kubernetes.

What questions are asked during the interview?

If you have certifications, the main difficulty in the interview may arise as part of the System Design Interview. Here, questions related to application design, architectural patterns, service meshes, and microservices will be discussed. It is recommended to watch the presentation from Netflix, which can help understand these topics. However, it is worth noting that these questions are related to the design of distributed applications, and not directly to Kubernetes.

Companies may ask questions related to the specific features of the specific provider on which Kubernetes will be deployed. For example, in the case of Azure, where I specialize, in addition to Kubernetes, there is also its own ecosystem, including tools such as Application Gateway from Microsoft. This allows you to integrate Kubernetes with other services and improve application management. It is important to consider aspects such as performance, security, and compatibility to get the most out of the platform's capabilities. For a deeper understanding of Azure Kubernetes Service, you can review successful use cases. Questions about how Kubernetes functions in a specific context, such as a data center or cloud environment, are highly specific. Important aspects here include the drivers and storage types offered by cloud providers, as well as their integration with Kubernetes. While these topics are not covered in certification exams and may not be relevant to everyone, they may be important for some professionals. For DevOps engineers involved in application deployment, this information may not be critical. Nevertheless, it is helpful for administrators to be aware of such nuances. Most teams have a dedicated cloud solution expert who is always available to provide assistance.

Risks of Using Kubernetes and Cloud Infrastructure

When working with Kubernetes, it is important to adhere to standards, as most use cases have a similar structure, and unique situations are rare. In Europe, Kubernetes remains a rare solution, as companies prefer more traditional technologies, such as virtual machines. This is due to the availability of a larger pool of specialists who are able to effectively work with virtualization. Choosing Kubernetes in European companies is a risky move, making it an atypical scenario for many organizations.

In France, Kubernetes is often used to overcome dependence on a specific cloud service provider, known as vendor lock-in. This platform allows companies to avoid vendor lock-in, providing flexibility and choice among various cloud solutions. The use of Kubernetes helps optimize infrastructure and simplify the application deployment process. This allows organizations to adapt to market changes and effectively manage their resources. Cloud services such as Platform as a Service (PaaS) offer significant advantages, allowing developers to deploy applications without having to delve into the implementation details of the middleware layer, as is the case with the LAMP stack (Linux/Apache/MySQL/PHP). This allows developers to focus on a higher level of abstraction and speeds up the development process. However, to ensure application compatibility across various cloud platforms, it is worth considering the use of Kubernetes and containerization. However, if an application depends on the specifics of a particular PaaS, this can complicate migration between cloud providers. Therefore, it is important to plan the application architecture in advance to minimize potential difficulties when migrating to another platform. When choosing Platform as a Service (PaaS), there is a risk of vendor lock-in, as there are a limited number of cloud solutions on the market. The main players in this segment are Microsoft, Amazon, Alibaba, and Yandex. It's important to keep in mind that template development requires customization for each cloud provider's specific configurations. This can complicate future migrations and increase dependency on the chosen solution. Many companies are currently concerned that sanctions may cause their cloud provider to cease operations in the countries where they operate. This will result in the unavailability of web applications, making it difficult to migrate them to another service. All scripts and code are typically customized for a specific cloud provider, complicating the migration process. In an unstable political environment, it's important to consider the risks associated with reliance on a single provider and consider using multi-cloud solutions to enhance business resilience. For companies outside the IT sector, another challenge arises: their IT infrastructure is not their core business. These companies view IT as an auxiliary service necessary to meet internal business needs. As a result, the number of IT specialists in such organizations can be limited, making supporting a multi-cloud architecture virtually impossible. This creates challenges in resource management, security, and integration of various cloud solutions.

A typical multicloud use case involves purchasing servers from Azure and Amazon and deploying a Kubernetes cluster on each. One cloud provider becomes the primary, while the second serves as a backup and a fallback option in the event of a failure. The application is containerized and configured for Kubernetes, allowing the company to easily switch between clouds without additional investment, other than the costs of ongoing support for this model and initial configuration for dual-cloud operation. This approach provides flexibility, increases system resiliency, and optimizes infrastructure costs.

Migrating from virtual machines to Kubernetes significantly reduces risks and can be a more cost-effective solution. However, this process is not simple, as it requires a complete technology change. In France, this transformation is complicated by the need to either rebuild the IT team or retrain existing specialists. From a business perspective, this is a complex organizational process that can take three to six months.

An alternative option is to outsource specialists. It is important to choose a stable and certified company, as Kubernetes is a relatively new technology in the corporate sector. Finding a qualified external team can be challenging, so it is worth considering the reputation and experience of potential partners.

Differences between solutions of different cloud providers

Each Kubernetes provider has unique features in the areas of networking, storage, and computing power. For example, Microsoft Azure offers GPU-enabled servers and has implemented Confidential Computing technology, which enables memory encryption during process execution. This is important because even with physical access to the server, data remains protected. These features make Azure an attractive choice for users requiring high levels of security and performance. When choosing a Kubernetes provider, it's important to consider these features to optimize operation and ensure application reliability.

If your application has specific requirements, you may need to not only choose Kubernetes for infrastructure but also find a cloud provider that can efficiently deploy your unique code. This is especially important if your application requires GPU computing. This is typical for artificial intelligence applications, which rely heavily on graphics card resources. Therefore, GPU Compute is not available with all cloud providers. It's important to carefully select a provider to ensure it supports the technologies you need and can deliver the performance you require.

Kubernetes Disadvantages

Security in Kubernetes is an important aspect that requires careful monitoring of various components. This includes both external security measures at the cluster and node level, as well as internal protection mechanisms specific to specific container images. In recent years, specialized anti-malware solutions for Kubernetes have been developed that scan all processes within containers, providing protection against potential threats and vulnerabilities. These tools help maintain a high level of security, minimizing risks and preventing attacks.

A virtual machine is a complete abstraction from the host server on which it runs. Each virtual machine has its own operating system, which significantly reduces the risk of unauthorized access to the server compared to containers. This isolation provides a higher level of security, as potential threats from the virtual machine are less likely to affect the host system.

To solve this problem, it is necessary to use activity scanning, network traffic encryption, and install security components and solutions for authentication of containers and applications. Although this makes the task of Kubernetes administrators more complex, such measures are an integral part of our professional activities. Security in Kubernetes requires constant attention and implementation of best practices to protect data and infrastructure.

Kubernetes is not a platform-as-a-service (PaaS), so developers must package not only the application itself but also all its dependencies, including middleware. However, this task is significantly simplified by the availability of a large number of ready-made and preconfigured container images available in public registries. These images allow for quick and efficient application deployment, minimizing the time spent on environment setup and configuration. Using ready-made solutions accelerates development and deployment, and improves the stability and security of applications in cloud infrastructure.

The requirements for application containerization create certain limitations for companies that do not develop software in-house. As a result, many organizations face the need to maintain legacy infrastructure alongside their primary infrastructure. This problem can be solved through gradual application replacement: rewriting old systems with modern architectural models and technologies, or completely migrating to SaaS solutions that do not require infrastructure management. This approach allows you to optimize processes, reduce costs, and improve business efficiency.

Administering Kubernetes can be complex, so we recommend using cloud services to simplify the process. Setting up and managing a cluster requires extensive knowledge and experience, making self-administration impractical for most users. Cloud solutions offer ready-made tools and support, making working with Kubernetes much easier and allowing you to focus on developing and deploying applications.

There are many options for configuring Kubernetes, which increases the risk of choosing inappropriate components and configurations. This can lead to such a unique installation that it will be difficult to find specialists to help resolve any issues that arise in the future. A lack of available consultants and qualified staff can be a serious obstacle to the effective use of your system. Therefore, it is important to carefully select the configuration and components to ensure support and problem-solving capabilities in the future.

One solution is to self-certify your IT solution. This includes auditing systems, configuring them, aligning them, and maintaining them in accordance with generally accepted industry standards. Regular audits with each new release will help ensure your solution remains compliant and current. However, it's important to note that in most cases, the investment in this process may not be worth it.

It's recommended to use solutions offered by cloud providers, as most of them offer Kubernetes as a Service. This makes deploying and managing a Kubernetes cluster more convenient and accessible. It's also important to note that Certified Kubernetes means that all cloud providers certify their Kubernetes solutions with the Cloud Native Computing Foundation. This foundation maintains an up-to-date list of certified providers, guaranteeing users high-quality service and compliance with modern standards. Choosing a certified provider ensures the reliability and security of your application in the cloud, making it an important consideration when deciding on a Kubernetes deployment platform.

With KaaS (Kubernetes as a Service), you pay for dedicated compute and storage resources. This often includes a fee for the Master Node, which is responsible for providing the API and allocating resources. However, worker nodes, which host pods, will incur separate charges. This is important to consider when planning your cloud budget, as costs can vary depending on the configuration and system load.

There are other pitfalls, too. Currently, all cloud providers use uniform Kubernetes versions with standard builds. However, plans are underway to free them from the requirement to adhere exclusively to the main version, giving them more freedom. This will allow each cloud provider to develop their own Kubernetes builds tailored to their specific drivers. This approach may lead to improved integration and functionality, but it will also create new challenges in terms of compatibility and support.

This will create new opportunities for providers, but will complicate the task for administrators. For example, effective support of Kubernetes on Azure requires a deep understanding of the internals of the Azure platform, as well as up-to-date knowledge of the specifics of working with this cloud.

Alternatives to Kubernetes

Kubernetes has a number of competitors among container orchestrators, such as Apache Mesos, HashiCorp Consul, Windows Server, and Docker Swarm. These solutions allow for the efficient management of virtual machines and containers, giving users various options for building infrastructure. However, Kubernetes has become the de facto standard in this area thanks to a variety of convenient tools for managing roles, access, security policies, and identity. Its popularity is also driven by an active community and support, making it a preferred choice for organizations of all sizes.

FaaS (Function as a Service) and serverless technologies are another alternative to Kubernetes. In this approach, application code is executed at the point of request, and the application itself is broken down into independent functions, each designed to handle a specific type of request. This makes such systems more portable and integrated than entire applications developed for specific PaaS. Various providers offer similar solutions, but they often have their own API, such as Droplets from DigitalOcean. Using FaaS allows you to optimize resources and reduce infrastructure costs while ensuring application flexibility and scalability.

Using virtual machines is still a more expensive alternative to containers. This solution requires more resources, which can be justified if you are developing a microservices architecture. Virtual machines provide operating system-level isolation, which is useful for complex applications, but their resource consumption can be a barrier to performance optimization and cost reduction. Therefore, when choosing between virtual machines and containers, it's important to consider the specifics of the project and scalability requirements, balancing isolation with resource efficiency.

There are various Kubernetes options, among which Red Hat OpenShift stands out, offering additional features and support for users. OpenShift is a Kubernetes-based platform that simplifies the deployment, management, and scaling of containerized applications. This platform provides integration with development tools and provides advanced security features, making it an ideal choice for enterprises looking to optimize their DevOps processes.

Conclusion

• Kubernetes is worth using if your project has tens or hundreds of containers.
• Kubernetes automatically determines when to scale resources, when to add new capacity to the project, and so on, based on the configuration.
• Despite the fact that Kubernetes provides a certain freedom due to its high level of abstraction, you may still encounter the problem of Vendor Lock. Locking yourself into the specifics of the largest cloud providers makes solutions non-portable.
• To avoid the risks associated with cloud provider lock-in, it makes sense to deploy infrastructure on two providers: one will be the primary and the other will be a backup.
• Maintaining a Kubernetes infrastructure is expensive and requires a strong team of specialists. An in-house team will cost a lot of money, and with outsourcing, there is a high risk of choosing the wrong contractor.
• In Europe, companies are very slow to adopt Kubernetes and still prefer more familiar and therefore less risky virtual machines.

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