We are going to discuss Kubernetes architecture and core components as, Kubernetes has become the new standard for orchestrating containerized applications, offering unmatched scalability, flexibility, and reliability. With the sheer growth of microservices architectures and containerized workloads, Kubernetes has become the bible of automation for deployment, scaling, and management.
This beginner guide would explore the architecture of Kubernetes, making it easier to understand its core elements and how they coordinate to enable efficient management of containers across clusters.
For advanced security, HA and performance best practices, read our advanced guide here.
What is Kubernetes?
Kubernetes, shortened and often abbreviated as K8s, is an open-source automated deployment, scaling, and operation system for containerized applications. It abstracts the underlying infrastructure, allowing developers to deploy applications in isolated environments with no concern for the hardware or specific details of the operating systems running on it.
Originally developed by Google but maintained currently by the Cloud Native Computing Foundation, Kubernetes has become the leading orchestration tool for containers because of its flexibility, scalability, and self-healing properties.
Core Components of Kubernetes
Kubernetes’ architecture is built around a series of modular components that work together to create a highly flexible and scalable system to manage containers. Those components fall into Master Node components and Worker Node components.
Master Node Components:
The master node controls and manages the entire Kubernetes cluster. It makes all operational decisions and schedules and controls the worker nodes.
- API Server: This is Kubernetes’ core central management system. It exposes the Kubernetes API which becomes the core interface for system operations. All administration tasks pass through the API server. Here it processes RESTful calls, validates the inputs, and carries out the operations.
- etcd: It is a distributed, key-value store. It is the main database of the Kubernetes system, storing all the cluster’s data, including configurations and the actual state of resources. etcd will be necessary for the consistency one needs across that cluster.
- Controller Manager: The controller manager checks to ensure that the system’s desired state matches the real state. The controller basically tracks the nodes’ states, ensures an accurate number of replicas is maintained in a deployment, and takes care of all background processes such as garbage collection and job completion.
- Scheduler: The scheduler decides to whom the workloads (pods) are to be assigned based on resource availability, quality of service, and any other custom policies that help decide where the pods are to be run within the cluster.
Worker Node Components:
Worker nodes are the places where the actual workloads, containers run. Each worker node hosts one or more pods containing the containerized applications.
- Kubelet: Kubelet is an agent that runs on every worker node and will talk to the API Server. It ensures that the containers are running as per the pod’s specifications. In case a container crashes, Kubelet reports this failure and takes appropriate action by restarting the pod if needed.
- Kube-proxy: This is a network component that forwards the appropriate traffic between different pods and services. It also includes service discovery and performs load balancing across the entire cluster.
- Container Runtime: The container runtime actually runs the containers on the worker nodes. For most use cases, a popular choice is Docker, but Kubernetes also supports other container runtimes, such as containers, CRI-O, and rkt.
To streamline deployments, teams often integrate a Kubernetes container registry to efficiently manage and pull container images across nodes.
Why are Containers required?
Before moving into Kubernetes, explaining why containers are essential in developing modern applications is useful.
Containers package an application with all its requirements so that the packaged version can run uniformly on any environment. Unlike virtual machines, containers share the same kernel as the host system, making containers lightweight and efficient, and much faster than virtual machines.
Important Benefits of Containers
- Portability: Containers ensure that an application runs the same way regardless of where it is deployed.
- Isolation: Each container is isolated from the others, so if one crashes, it does not affect the rest.
- Resource Efficiency: Containers share the OS of the host system and are, hence, more resource-efficient than virtual machines.
Docker Swarm vs Kubernetes
Docker Swarm and Kubernetes are two popular container orchestration platforms; however, they differ significantly in features, scalability, and use cases.
Docker Swarm:
Docker Swarm is Docker’s native clustering and orchestration tool. It is not as hard to use or deploy as Kubernetes. It is apt for small environments or very simple applications.
- Major features:
- Easy and fast deployment.
- Integrated directly with Docker.
- It is ideal for small-size projects that are not so complex and have fewer orchestration needs.
Kubernetes:
Kubernetes is more featureful and scalable, suitable for complex, big applications. Includes features like self-healing, automated rollbacks, strong monitoring, etc.
Key Features:
- Highly scalable and flexible.
- Self-healing capabilities (restarts failed containers).
- Supports advanced networking, load balancing, and auto-scaling.
Generally, Docker Swarm is perfect for small projects and environments, while Kubernetes is considered the industry standard for highly complex and production-grade deployments.
Recommended Read: Kubernetes vs Docker: What’s the Difference?
Hardware Components of Kubernetes
The physical setup running Kubernetes components involves the master node and worker nodes.
Master Node Hardware Requirements:
This master node doesn’t run application workloads but is critical for managing the cluster. It often needs to consume more resources than the worker nodes since it has a role in scheduling, monitoring, and determining the cluster’s state.
- CPU: Minimum 2 CPU.
- Memory: At least 2GB of RAM for small environments; larger environments may need significantly more.
- Storage: Fast storage (SSD recommended) for log and etcd data.
Hardware Requirements for Worker Nodes
Worker nodes perform the actual containerized applications, so their resource requirements are dependent on the workload they run.
- CPU: Minimum 1 CPU per worker node
- Memory: Minimum 1 GB of RAM, depending on the size of the workload.
- Storage: Container images, logs, and application data must be stored.
In high-performance scenarios like machine learning or scientific computing, GPU-enabled Kubernetes nodes can be added to handle compute-intensive workloads.
Software Components of Kubernetes
Besides hardware, Kubernetes components rely on several software elements that control workloads.
- Operating System: Kubernetes is always typically developed on Linux, though some workloads can be managed using Windows nodes.
- Container Runtime: Docker, containerd, and CRI-O are supported by Kubernetes as container runtimes.
- Networking Plugins: Networking plugins like Calico, Flannel, and Weave manage communication between pods and services.
Kubernetes Architecture in Detail
In Kubernetes architecture, a master worker is involved. Master nodes control the cluster, and worker nodes carry application workloads.
Control Plane (Controller Node) Components:
In the control plane discussed above are the API Server, etcd, Controller Manager, and Scheduler. These components individually run as well as their aggregation, managing the whole Kubernetes architecture cluster by deciding how and where workloads get executed.
Organizations often opt for a managed control plane Kubernetes solution to offload operational overhead while maintaining high availability and control.
Data Plane (Worker Nodes) Components:
Worker nodes run actual containers inside pods. A pod is the smallest unit deployed within Kubernetes. A pod can house one or more containers.
- Pods: Each pod has one or more containers and possibly shared storage and networking resources. Kubernetes schedules the pods across the worker nodes, ensuring they are distributed and resilient.
- Services: A service in Kubernetes defines a logical set of pods and ensures that external entities can access them. It allows for load balancing and service discovery.
How is Kubernetes Used in Enterprise?
Kubernetes is one such platform that has been used multiple times in enterprise applications. It can automatically control thousands of containers at scale, self-heal, and scale, making it suitable for modern DevOps workflows.
- Scalability and Efficiency: Kubernetes can scale up and scale down as needed due to demand. Resourceful utilization is ensured.
- DevOps Integration: Kubernetes integrates highly with CI/CD tools. CI/CD will automate enterprises’ deployments, testing, and update processes.
- Multi-cloud Flexibility: Kubernetes can be run on multiple cloud environments, such as public, private, and hybrid. Implementing such technology prevents lock-in with any vendor within an enterprise and minimizes the cost of using these applications.
- High Availability and Fault Tolerance: With features such as restarts, rescheduling, and load balancing, Kubernetes allows enterprise applications to remain up and running even in failure and high demand situations.
Conclusion: Kubernetes architecture and core components
Kubernetes is the most powerful platform for managing a wide variety of containerized applications at a scale. It offers a means for efficient orchestration, scaling, and managing workloads in production environments based on a master and worker nodes architecture. We need to understand key elements if an organization adopts container orchestration at the enterprise level. Book a free consultation with an AceCloud expert today to learn more about our Kubernetes services.
Related Post
Get in Touch
Credits First!
- 24*7 Human Support
- Pay-as-you-go Pricing
- No Egress Cost
- Multi Tier Security