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Introduction to Kubernetes: Benefits for Development

Introduction to Kubernetes: Benefits for Development
Hostman Team
Technical writer
Kubernetes
20.08.2024
Reading time: 9 min

Deploying a containerized application might seem straightforward for the average IT specialist, especially with tools like Docker. You create a Dockerfile with commands for downloading and installing dependencies and setting up the environment within the operating system. Managing and stopping containers is even simpler, often requiring just a few console commands and runtime daemons.

However, challenges arise when scaling the service infrastructure. As the application grows in complexity, the focus shifts from configuring containers to managing and orchestrating them. What was once a simple codebase now evolves into a microservices architecture—a collection of distinct processes that perform specific functions and might even be hosted by different cloud providers.

At this point, the application becomes what systems theory calls a "system with irreducible complexity." This means that the various containerized components need proper coordination, synchronization, and communication. As complexity increases, abstraction becomes essential to avoid creating a tangled mess of legacy code that's difficult to maintain. This is where orchestration systems like Kubernetes come in.

In this article, we will explore what Kubernetes is, how Kubernetes works and what it is usually used for.

What is Kubernetes?

Kubernetes, often abbreviated as k8s, is an open-source platform that automates container operations in Linux. Orchestration eliminates many manual tasks necessary for deploying and scaling containerized applications. It allows you to combine groups of hosts running containers into a single system, making it easier to manage even as your infrastructure grows.

Kubernetes adds an extra layer of coordination that unifies individual containers into a cohesive unit. Whether your application runs on a single computer or across a fully-fledged data center, Kubernetes ensures each software component performs its specialized function while maintaining overall system integrity. This orchestration is crucial for preventing chaos in complex, distributed applications.

Kubernetes was initially developed by a team at Google and later handed over to the Cloud Native Computing Foundation (CNCF), where it rapidly gained a vast community of contributors. Major companies like Google and Red Hat have heavily invested in the project, with Red Hat even building its PaaS platform, OpenShift, on top of Kubernetes.

Kubernetes vs. Docker

There's a common misconception that Kubernetes competes with Docker. In reality, they operate on different levels of abstraction. Docker is a containerization tool that manages containers, while Kubernetes is an orchestrator that "commands" the container manager.

The word "Kubernetes" is derived from the Greek word for "captain," which aptly describes its role in managing and directing containerized applications. Understanding the distinction between Kubernetes and Docker is critical:

  • Kubernetes can be used with Docker or independently.
  • Docker and Kubernetes are not replacements for each other; instead, they complement each other by handling different aspects of containerization.
  • Docker packages and distributes containers, while Kubernetes manages the distribution and scaling of these containers on a larger scale.

Benefits of Kubernetes for Development

Reducing Manual Management Costs

The primary advantage of using Kubernetes is the automation of manual labor. Both large companies and smaller projects use Kubernetes to save time and money on ecosystem management. Kubernetes "understands" how to optimize resource usage, eliminating the need for constant human oversight. Orchestration minimizes server downtime and reduces the need for manual intervention in the event of a node failure, thanks to well-defined logic that automates recovery processes.

Automatic Scaling Up and Down

Vertical and horizontal flexibility is a crucial feature of Kubernetes. Resources (such as the number of containers and microservices) can be adjusted almost instantly, depending on actual application needs. For example, you can increase the number of available Kubernetes containers or enhance the throughput of existing ones by configuring CPU and memory settings, utilizing components like Cluster Autoscaler.

Enhancing DevOps and CI/CD Efficiency

Kubernetes simplifies development, testing, and deployment, making it a vital tool for CI/CD approaches. Its automation and centralized management improve DevOps practices, shortening the intervals between releases and deployments. This is especially important in microservices-based applications, where separate functional blocks interact through defined APIs.

Open-Source Community

Kubernetes is community-driven, resulting in numerous derivative services and platforms, such as Red Hat OpenShift. This community support also means that public clouds like IBM, AWS, Google Cloud, and Microsoft Azure offer excellent support for Kubernetes, making it a robust and flexible tool for modern application development.

In summary, Kubernetes provides a powerful and flexible solution for managing containerized applications, making it indispensable in modern software development.

Kubernetes Use Cases

Kubernetes is built on a client-server architecture. While it's possible to have multiple master servers for increased availability, there is always one main server—the control plane. This main server includes several core components, such as the Kube-apiserver, etcd storage, Kube controller manager, cloud controller manager, Kube scheduler, and a DNS server.

A key part of this architecture is the command-line interface (CLI) kubectl, which serves as the entry point for executing application management commands. The standard syntax follows the pattern:

kubectl [command] [type] [name] [flags]

Before diving into Kubernetes, it's essential to understand its basic entities:

  • Cluster: In k8s, a cluster is a group of nodes that run containerized applications. The orchestrator's configuration settings define how clusters and everything within them are managed.
  • Pod: The smallest deployable unit in Kubernetes. It's essentially one or more containers that run within a single cluster.
  • Node: A node is a physical or virtual machine within a cluster. It includes everything necessary to run and maintain containers, such as a runtime environment and critical services.
  • Service: A Kubernetes service is an abstraction that defines a logical set of Pods and a policy for accessing them. Services enable stable communication and manage network traffic between Pods.

Given its flexibility and versatility, Kubernetes can be used in numerous ways. Let’s look at the most common scenarios Kubernetes is used for.

Developing Containerized Applications

Kubernetes excels at managing multiple containers. Applications running in Kubernetes are easy to deploy and manage, thanks to the Kubernetes Container Runtime, Containerd. This open-source container runtime, originally developed by Google, is designed for use in Kubernetes and other cloud platforms. It can also be used independently to run and deploy containers locally or on private servers.

Cloud Application Development

Kubernetes can be used for individual application development (like a traditional orchestrator) and for creating full-fledged cloud platforms. For instance, a simpler orchestrator like Docker Swarm lacks the flexibility and scalability of Kubernetes and is more limited in its container management capabilities.

Monitoring and Logging

Kubernetes offers a comprehensive set of tools for monitoring, logging, and gathering metrics across the entire ecosystem. This is crucial for analyzing the state of clusters and troubleshooting potential issues, making monitoring one of the most popular Kubernetes use cases. Some widely used monitoring solutions specifically designed for Kubernetes include:

  • Prometheus
  • Stackdriver (developed by Google)
  • Papertrail
  • Datadog (proprietary)
  • Heapster
  • Fluentd
  • Logstash

Managing Network Interactions

Kubernetes enables the configuration of network policies that dictate how applications and clusters interact. Essentially, these are rules that define the interaction patterns between Pods and external services. Managing network policies is a critical component of Kubernetes security, ensuring that private resources are protected from external environments while public resources remain accessible as part of the application's open interface. This prevents service compromise by attackers and reduces the likelihood of network backdoors or open listening ports.

Self-Deployment vs. KaaS

An alternative to self-deploying and maintaining Kubernetes on your own machines is outsourcing this to a cloud provider's pre-configured infrastructure, often referred to as Kubernetes as a Service (KaaS). The benefits are numerous:

  • The provider maintains the ecosystem, ensuring Kubernetes' fault tolerance and security, allowing you to focus solely on business logic and application development.
  • While understanding the basics of Kubernetes (and DevOps in general) is still necessary, costs are reduced, and focus on development is increased.
  • KaaS is ideal for instant deployment and testing of your business logic, while self-deployment requires a broader architectural vision and significantly more time.

How to Deploy Kubernetes

Deploying the orchestrator involves setting up a Kubernetes cluster. This process can be broken down into several steps:

  1. Generate SSH Keys: Each node requires its own key, which is used for remote access to the cluster.
  2. Download Packages: Like any UNIX installation, it's important to update the repository list and ensure that essential packages like apt-transport-https, ca-certificates, and curl are available.
  3. Obtain the GPG Key: This key is necessary to download Docker from the repository.
  4. Install Docker: Docker is needed to manage containers directly.
  5. Install Kubernetes: Load essential modules such as Kubelet, Kubeadm, and kubectl.
  6. Launch the Cluster: First, activate the worker nodes, then designate one of them as the master node, which will manage the entire cluster.

The official Kubernetes website offers materials on how to start using the orchestrator and tutorials on its basic features.

Conclusion

It's clear that Kubernetes will continue to be the leading container orchestration system. Its popularity is likely to grow as more enterprises and small teams, including beginner developers, start utilizing Kubernetes. 

In this short Kubernetes overview, we explored its benefits that include:

  • Effective horizontal and vertical scaling
  • Increased labor efficiency
  • High organizational and infrastructure mobility

These advantages increase user satisfaction and IT department efficiency in large companies. However, one downside of Kubernetes is that the entry barrier can be somewhat higher for less experienced developers.

Kubernetes is particularly effective for building microservices-based applications and can be deployed in virtually any environment, whether locally or in a public cloud. It automatically adjusts cluster sizes to meet a service's specific needs. These features are especially relevant when implementing DevOps and continuous integration and deployment (CI/CD) pipelines. Kubernetes's lifecycle management of containers, alongside DevOps approaches, helps streamline and structure software development.

Kubernetes
20.08.2024
Reading time: 9 min

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23 August 2024 · 5 min to read
Kubernetes

Kubernetes Cluster: Installation, Configuration, and Management

Kubernetes, or K8s, is an open-source container orchestration platform developed by Google. The core concept behind Kubernetes is that a user installs it on a server, or more likely a cluster, and deploys various workloads on it. Kubernetes addresses challenges related to container creation, scaling, namespaces, access rights, and more. The primary interaction with the cluster is through YAML configuration files. This tutorial will guide you through creating and deploying a Kubernetes cluster locally. Creating Virtual Machines We will set up the Kubernetes cluster on two virtual machines: one acting as the master node and the other as a worker node. While deploying a cluster with only two nodes is not practical for real-world use, it is sufficient for educational purposes. If you wish to create a Kubernetes cluster with more nodes, simply repeat the process for each additional node. We will use Oracle's VirtualBox to create virtual machines, which you can download from this link. 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Create the KUBECONFIG environment variable: export KUBECONFIG=/etc/kubernetes/admin.conf Install the Container Network Interface (CNI): kubectl apply -f https://raw.githubusercontent.com/coreos/flannel/master/Documentation/kube-flannel.yml Worker Node On the worker node, run the kubeadm join command obtained during the master node setup. After this, on the master node, enter: sudo kubectl get nodes The output should be: NAME                 STATUS      ROLES                        AGE    VERSIONmaster.local          Ready      control-plane,master          10m    v1.24.2worker.local          Ready      <none>                        79s    v1.24.2 The cluster is now deployed and ready for operation. Conclusion Setting up a Kubernetes cluster involves several steps, from creating and configuring virtual machines to installing and configuring the necessary software components. This tutorial provided a step-by-step guide to deploying a basic Kubernetes cluster on a local environment. 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22 August 2024 · 7 min to read
Kubernetes

Running Kubernetes Clusters in the Cloud with VMware

Containerization is an effective way to deliver applications to customers. If your cloud IT infrastructure is deployed on VMware, you can use CSE, or Container Service Extension, to work with Kubernetes (K8s). This solution significantly accelerates the time from receiving code to deploying it in a production cloud system by automating the management (orchestration) of containers with the software. What is CSE? CSE is an extension to the VMware vCloud Director (VCD) platform that adds functionality for interacting with Kubernetes clusters—from creation to lifecycle management. Its installation allows for a comprehensive approach, integrating the management of both legacy and containerized applications within a single VMware infrastructure, while maintaining uniformity and a systematic management approach. Key features The CSE client facilitates cluster deployment, adds worker nodes, and configures NFS storage. A vCloud Director-based cloud offers high-security, multi-tenant (user-isolated) computing resources. The CSE server is a tool for configuring the configuration file and virtual machine templates. Creating and managing Kubernetes clusters in VMware is relatively complex, especially compared to tools like Docker Swarm, another cluster management tool for remote hosts. Kubernetes is often compared to vSphere, but the discussed platform offers more extensive functionality for managing a containerized IT infrastructure. This compensates for the drawbacks of a complex architecture and the high cost of the product. CSE Features The first thing the developers highlight about CSE is the ability to save on the already implemented VMware vCloud Director platform. All previously installed applications will continue to function as before (virtually invisible to the end client), while adding the ability to work with VMware Container. System resilience remains high regardless of traffic uniformity or platform load dynamics. Benefits of implementing the extension: A tool for managing clusters, node pools, and other resources. Significantly reduced time-to-market for any new developments. Increased availability of web resources, including cloud applications. Automatic server load distribution. Improved reliability and performance of CI/CD processes. The number of containers is unlimited as long as the physical server's resources (memory, CPU, etc.) are sufficient. This allows for parallel development of different projects that are initially isolated from each other. There are also no restrictions on the installed operating systems or programming languages. This is convenient when operating in an international market, even with just one physical server. Installing the CSE Extension in vcd-cli The vcd-cli (Command Line Interface) tool manages the infrastructure from the command line. By default, it does not support working with CSE. To enable it, you need to install the container-service-extension add-on: python3 -m pip install container-service-extension Next, you need to add the extension to the vcd-cli configuration file, located at ~/.vcd-cli/profiles.yaml. Open this file with a text editor and find the line active with the following value: extensions:- container_service_extension.client.cse After saving the changes to the configuration file, log in: vcd login <host> <organization_name> <login> Now, verify that the extension is indeed installed and actively interacting with the host: vcd cse versionCSE, Container Service Extension for VMware vCloud Director, version 3.0.1 vcd cse system infoproperty     value-----------  ------------------------------------------------------description  Container Service Extension for VMware vCloud Directorproduct      CSEversion      2.6.1 Creating a Kubernetes Cluster Next, let's look at activating a Kubernetes cluster within VMware. Integration with the vCloud Director platform allows managing the process from a single point in a familiar interface. Data center resources are typically pooled, and deployment is done through VM templates with pre-installed and pre-configured Kubernetes. You can create a cluster manually with the command: vcd cse cluster create <cluster_name> \        --network <network_name> \         --ssh-key ~/.ssh/id_rsa.pub \        --nodes <number_of_nodes> \        --template <template_name> The cluster and network names are mandatory. The rest are optional and will default if omitted. You can check the full list of active templates with the command: vcd cse template list The selected network must be of type Routed and connected to the internet. If either of these conditions is not met, the cluster initialization process will stall during the master node generation. You can use a "grey" network with NAT or Direct Connect technology. The result of the cluster creation will be visible in the vCloud Director platform's web interface, in the vApps section. After monitoring the status, the final step is to create a configuration file for Kubernetes. Generate it with the command: vcd cse cluster config <cluster_name> > config Then move the file to an appropriate location with the commands: mkdir ~/.kube/configcp config ~/.kube/config The cluster is now fully ready for use—from setting user parameters to deploying virtual machines, applications, and more. However, keep in mind that emulating containerization does have some limitations. Implementation Features For instance, the CSE extension does not support the LoadBalancer service type. Therefore, Kubernetes manifests using it (plus Ingress) will not work correctly. There are solutions to this drawback, and we'll discuss two of the most popular—MetalLB and Project Contour. MetalLB Using MetalLB with Kubernetes involves a load balancer that replaces cloud routing protocols with standard LB protocols. Here's an example of how to use it. 1) Create a namespace and add MetalLB using manifests: kubectl apply -f https://raw.githubusercontent.com/metallb/metallb/v0.9.5/manifests/namespace.yamlkubectl apply -f https://raw.githubusercontent.com/metallb/metallb/v0.9.5/manifests/metallb.yaml 2) Next, configure node connection security. Without this, the transmitted pods will go into a CreateContainerConfigError status, and error messages such as secret memberlist not found will appear in the logs: kubectl create secret generic -n metallb-system memberlist --from-literal=secretkey="$(openssl rand -base64 128)" 3) Check the current status of the utility. If configured correctly, the controller and speaker will be displayed as running: kubectl get pod --namespace=metallb-system  NAME                          READY   STATUS    RESTARTS   AGEcontroller-57f648cb96-2lzm4   1/1     Running   0          5h52mspeaker-ccstt                 1/1     Running   0          5h52mspeaker-kbkps                 1/1     Running   0          5h52mspeaker-sqfqz                 1/1     Running   0          5h52m 4) Finally, manually create a configuration file: apiVersion: v1 kind: ConfigMap metadata:   namespace: metallb-system   name: config data:   config: |     address-pools:     - name: default       protocol: layer2       addresses:      - X.X.X.101-X.X.X.102 You should fill in the addresses parameter with the addresses that remain free and will handle the load balancing. Apply the configuration file: kubectl apply -f metallb-config.yaml The procedure for setting up a LoadBalancer for Kubernetes using MetalLB is complete; next is Ingress support, which is easier to implement with another tool. Project Contour Create a manifest with Project Contour using the command: kubectl apply -f https://projectcontour.io/quickstart/contour.yaml This command automatically deploys the Envoy proxy server, which listens on the standard ports 80 and 443. Conclusion Integrating Kubernetes into VMware with the Container Service Extension (CSE) unifies the management of legacy and containerized applications within VMware vCloud Director. While the setup may be complex, CSE enhances application deployment, scaling, and management, offering a resilient and scalable infrastructure. Despite some limitations, such as native LoadBalancer support, tools like MetalLB and Project Contour provide effective solutions. Overall, CSE empowers organizations to modernize their IT infrastructure, accelerating development and optimizing resources within a secure, multi-tenant cloud environment.
22 August 2024 · 7 min to read

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