Skip to main content
  1. Learn
  2. Software development
  3. Posts
  4. A simple introduction to Kubernetes and the world of containers

A simple introduction to Kubernetes and the world of containers

PostsSoftware development
Georgina Guthrie

Georgina Guthrie

May 15, 2024

Automatic computer updates are annoying, especially when you’re in a rush. But imagine that on a company-wide scale: it’d be a complete disaster. When the system’s down, people can’t work. Developers need the ability to update and maintain their company’s systems without bringing the whole organization to a standstill. As containers become ever more popular, dev teams need more efficient ways to manage their systems. This is where Kubernetes comes in. Here’s everything you need to know about this sophisticated but powerful tool.

What is Kubernetes?

Kubernetes, or K8s for short, is an open-source container-orchestration tool designed by Google. It’s used for bundling and managing clusters of containerized applications — a process known as ‘orchestration’ in the computing world.

The name Kubernetes originates from Greek, meaning helmsman or pilot.

To fully understand Kubernetes and its advantages, we first need to take a look at how it all started.

Why do we need Kubernetes?

Organizations used to run on physical servers. The problem was that when performing multiple tasks on a single server, one application could take up most of the resources and cause others to underperform. One solution was to have more servers, but as you can imagine, this got expensive pretty quickly.

Then things shifted towards virtualization. Multiple Virtual Machines (VMs) could run on a single physical server’s CPU, which meant that several applications could run simultaneously without performance issues.

VMs also allowed developers to isolate applications, adding an extra layer of security and flexibility. When one application had to be added, updated, or repaired, the overall system remained unaffected. However, large memory usage was a main issue with VMs.

What are containers?

Containers are similar to VMs. They have their own operating systems, file systems, CPU, memory, and process space — and they can be decoupled from the main infrastructure. The main difference is that they have a much lower memory footprint due to their relaxed isolation properties.

Kubernetes container deployment explained
Image Source

We use containers today. Containers run many complex application clusters, which are often challenging to manage efficiently. This is where Kubernetes steps in.

What does Kubernetes do?

In a nutshell, container orchestration tools, like Kubernetes, help developers manage complex applications and conserve resources.

Developers manage the containers that run applications to ensure there’s no downtime. If one container fails, another needs to take its place. Kubernetes handles this changeover automatically and efficiently by restarting, replacing, and killing failed containers that don’t respond to a health check.

It also monitors clusters and decides where to launch containers based on the resources currently being consumed — which means it’s useful for scaling, deployment, and general application management.

Kubernetes architecture explained

The Kubernetes command-line interface is called kubectl. It manages clusters and instructs the Kubernetes API server. The API server then adds or removes containers in that cluster to ensure the desired and actual states match.

The basic Kubernetes process:

  1. Admin defines the desired state of an app and then puts that in the manifest file.
  2. This file is sent to the Kubernetes API Server using a Common Language Infrastructure or User Interface.
  3. Kubernetes stores this file in a database called the Key-Value Store.
  4. It then implements the desired state on all the relevant apps within the cluster.
  5. Kubernetes then continuously monitors the elements to ensure the current state matches the desired state.

A Kubernetes cluster consists of the master node, worker nodes, and pods. Here’s what each of these terms means.

  • Cluster: This is a collection of servers, including the API server.
  • Master node: The master is a collection of components that make up Kubernetes’s control panel. It is used for each cluster decision.
  • Worker Node: Worker nodes check the API Server for new work assignments, which they then carry out and report back to the Master Node.
  • Pods: A pod is the smallest scheduling element. It works as a wrapper for each container. Without it, a container cannot be part of a cluster. If the developer needs to scale an app, they start by adding or removing pods.
  • Kubelet: This sources the pod’s configuration from the API server and ensures the described containers function correctly.
  • Docker Container: These run on each of the worker nodes, which in turn run the configured pods.
  • Kube-proxy: This network proxy performs services on a single worker node.

Kubernetes Architecture Diagram
Image Source

To learn more terminology, visit the Kubernetes website, which includes a full glossary with explanations.

Container engines and container runtime

A container engine is software that oversees the container functions. The engine responds to user input by accessing the container image repository and loading the correct file to run the container. The container image is a file consisting of all the executable code you need to deploy the container repeatedly. It describes the container environment and contains the software necessary for the application to run.

When you use Kubernetes, kubelets interact with the engine to make sure the containers communicate, load images, and allocate resources correctly. A core component of the engine is the container runtime, which is largely responsible for running the container. While the Docker runtime was originally a standard solution, you can now use any OCI-compliant (Open Container Initiative) runtime.

How does Kubernetes work

Kubernetes operates as a sophisticated orchestration tool that automates the management of containerized applications within a cluster environment. Its functionality revolves around a declarative model, where users specify the desired state of their applications, and Kubernetes ensures that the cluster aligns with this specification.

  • Declarative management: At the heart of Kubernetes lies a declarative approach to application management. Users define the desired state of their applications through YAML or JSON manifest files, detailing parameters such as replication requirements, resource allocations, networking configurations, and service endpoints. Kubernetes continuously compares this desired state against the current state of the cluster, automatically adjusting configurations to maintain consistency.
  • API-driven control plane: Kubernetes exposes a powerful RESTful API through its control plane, allowing users to interact with the cluster programmatically. Tools like kubectl facilitate communication with the API server, enabling users to create, update, or delete resources within the cluster seamlessly.
  • Scheduler and controller managers: The control plane consists of various components responsible for cluster management. The Scheduler assigns pods—Kubernetes’ smallest deployable units—to nodes based on resource availability and scheduling constraints. Controller Managers oversee resource states, ensuring that desired configurations are maintained. For instance, the ReplicaSet Controller ensures the desired number of pod replicas is running, while the Deployment Controller handles deployment rollouts and scaling.
  • Node components: Each worker node in a Kubernetes cluster hosts components responsible for executing and managing containers. The Kubelet, an agent running on each node, interacts with the control plane to manage pod lifecycle events. The Container Runtime, such as Docker or containerd, executes containerized applications based on pod specifications. Additionally, the Kube-proxy facilitates network communication between pods and provides network services like load balancing and routing.
  • Pods and containers: Kubernetes abstracts underlying infrastructure details, focusing on managing pods—containers encapsulating one or more application components and shared resources like networking and storage volumes. Pods operate within a unified interface, simplifying application deployment and management while enabling developers to focus on application logic.

What are the benefits of Kubernetes?

Kubernetes is a powerful tool that lets you run software in a cloud environment on a massive scale. If done right, it can boost productivity by making your applications more stable and efficient.

  • Improved efficiency: Kubernetes automates self-healing, which saves dev teams time and massively reduces the risk of downtime.
  • More stable applications: With Kubernetes, you can have rolling software updates without downtime.
  • Future-proofed systems: As your system grows, you can scale both your software and the teams working on it because Kubernetes favors decoupled architectures. It can handle massive growth because it was designed to support large systems. Furthermore, all major cloud vendors support it, offering you more choice.
  • Potentially cheaper than the alternatives: It’s not suitable for small applications, but when it comes to large systems, it’s often the most cost-effective solution because it can automatically scale your operations. It also leads to high utilization, so you don’t end up paying for features you don’t use. Most of the tools in the K8s ecosystem are open-source and, therefore, free to use.

What are the disadvantages of Kubernetes?

As with all things, Kubernetes isn’t for everyone. It’s famously complex, which can feel daunting to developers who aren’t experts in infrastructure tech.

It may also be overkill for smaller applications. Kubernetes is best for huge-scale operations rather than small websites.

Advanced Kubernetes concepts

Scalability and resource optimization

Kubernetes excels in managing the scalability of containerized applications, offering automated solutions for resource allocation and workload distribution.

  • Automated scaling: Kubernetes enables organizations to scale their applications seamlessly in response to fluctuating demand. Through features like Horizontal Pod Autoscaler (HPA) and Cluster Autoscaler, Kubernetes automatically adjusts the number of running instances based on predefined metrics such as CPU usage or incoming traffic. This ensures optimal performance during peak periods while minimizing resource waste during off-peak times.
  • Dynamic resource allocation: With Kubernetes, resource allocation is dynamic and efficient. The platform intelligently schedules workloads across clusters, ensuring that each container receives the necessary computing, storage, and networking resources. By optimizing resource utilization and avoiding overprovisioning, Kubernetes helps organizations reduce infrastructure costs while maintaining high-performance levels.

High availability and fault tolerance

Ensuring high availability and fault tolerance is paramount in modern IT environments, and Kubernetes provides robust solutions to address these challenges.

  • Automated failover: Kubernetes automates the process of detecting and recovering from failures, thereby minimizing downtime and ensuring uninterrupted service delivery. Through features like Pod Restart Policies and Readiness Probes, Kubernetes monitors the health of containerized applications and automatically restarts or replaces instances that become unresponsive or fail to meet predefined criteria.
  • Multi-zone and multi-region deployment: Kubernetes supports the deployment of multi-zone and multi-region clusters, enhancing resilience and fault tolerance. By distributing workloads across geographically dispersed data centers, organizations can mitigate the impact of infrastructure outages or regional disruptions, ensuring business continuity and disaster recovery capabilities.

Ecosystem and extensibility

Kubernetes boasts a vibrant ecosystem of tools, plugins, and extensions that augment its capabilities and cater to diverse use cases.

  • Rich ecosystem: The Kubernetes ecosystem encompasses a wide range of complementary technologies and solutions, including monitoring and logging tools, networking overlays, security enhancements, and application deployment frameworks. This rich ecosystem provides organizations with flexibility and choice, allowing them to select the best-in-class solutions that align with their specific requirements and preferences.
  • Customization and extension: Kubernetes’ modular architecture and extensible design enable organizations to customize and extend the platform to meet their unique needs. From custom resource definitions (CRDs) and operators to third-party integrations and community-contributed plugins, Kubernetes offers a flexible framework for building tailored solutions and addressing complex challenges across various domains, such as DevOps, data management, and machine learning.

Comprehensive security features

Security is a top priority in Kubernetes, and the platform offers a comprehensive suite of features and best practices to protect containerized workloads and infrastructure components.

  • Role-Based Access Control (RBAC): Kubernetes implements RBAC to enforce granular access policies and restrict privileges based on user roles and permissions. By defining roles, role bindings, and service accounts, organizations can ensure that only authorized users and processes have access to sensitive resources and perform permitted actions within the cluster.
  • Network policies: Kubernetes allows organizations to define network policies that control the flow of traffic between pods and enforce segmentation and isolation within the cluster. By specifying ingress and egress rules based on labels and selectors, organizations can implement fine-grained network security policies that prevent unauthorized access and mitigate potential attack vectors, such as lateral movement and data exfiltration.
  • Container image scanning: Kubernetes integrates with container image scanning tools to analyze images for vulnerabilities and compliance issues before deployment. By scanning container images for known vulnerabilities, malware, and configuration weaknesses, organizations can identify and remediate security risks early in the software development lifecycle, ensuring that only secure and compliant images are deployed in production environments.

Kubernetes diagrams

Kubernetes isn’t necessarily the right option for smaller applications, but it is a powerful, flexible choice for big organizations, fast-growing startups, or companies looking to upgrade a legacy application.

Adopting new processes and technology is never easy. But the more flexible and user-friendly you can be when it comes to rolling out this notoriously complex tool, the happier and more collaborative your team will be.

The best way to get started is to give dev teams access to the tool as early as possible so they can test their code and prevent expensive mistakes later on.

You can also help teams understand the basics with a Kubernetes architecture diagram. This diagram visualizes the automation plan for deploying, scaling, and managing containerized applications, making the process easier for teams to understand.

Kubernetes architecture diagram
Kubernetes architecture diagram available in Cacoo

Architecture diagrams are essential for getting your teams working together. And, with the Kubernetes icons and templates now available in Cacoo, you can quickly create and share your architecture with anyone.

This post was originally published on April 8, 2020, and updated most recently on May 15, 2024.



Subscribe to our newsletter

Learn with Nulab to bring your best ideas to life