Kubernetes Architecture Diagram: An In-depth Explanation

With containerization and microservices adoption in organizations, Kubernetes eases the complexity of deploying, scaling, and managing applications by automating key processes. It gives power to developers and DevOps teams to create asynchronous systems that are highly available and can be used interchangeably across different cloud providers.

For beginners and professionals, understanding the architecture of Kubernetes is important as it serves as the top layer for effective management of containerized workloads. In this article, we will learn how the Kubernetes architecture diagrams work and discuss specific aspects such as the Master Nodes and Worker Nodes hard in the diagrams.

What is Kubernetes?

Kubernetes is a master-slave architecture-based container orchestration platform. Microservices design, in which applications are divided into smaller, independently deployable services, is made possible by this robust open-source platform for managing containerized apps, which automates container deployment and maintenance. Kubernetes provides features such as adaptability, scalability, and resilience.

Kubernetes architecture consists of two main parts: the Master Node (control pane components) and the Worker Nodes (components that manage individual nodes).

Key Features of Kubernetes

• Scalability

Kubernetes is very good at scaling applications dynamically. It provides horizontal scaling by creating more Pods of an application or destroying some based on resource usage. In addition to horizontal scaling, it can also do vertical scaling by enabling containers to take more resources like CPU or memory.

• Automation

Kubernetes automates critical operations, including deployment, updates, and rollbacks, and therefore simplifies application management. In addition to built-in load balancing, Kubernetes performs very well in distributing traffic across several containers, thus reducing operational overhead and making large-scale application management easier.

• Fault-Tolerance

Kubernetes is designed to be resilient. It ensures fault tolerance on the node and Pod levels. Workloads are automatically rescheduled to healthy nodes if a node fails. Failed or unresponsive Pods are replaced immediately.

• Mobility

By abstracting the underlying infrastructure, Kubernetes enables apps to be used in a variety of settings. Businesses can successfully avoid vendor lock-in and implement multi-cloud strategies because of this flexibility.

Kubernetes architecture is the design pattern and layout of its components that interface with one another to create a controlled environment for the deployment and management of containerized applications that are the main focus to be orchestrated in a cluster.

The architecture is built to have several components that work as a distributed system where they all communicate with each other for the deployment, scaling, and management of applications.

How Kubernetes is a Distributed System

At its core, Kubernetes is a distributed system which means it manages a containerized environment over several machines – the nodes. Due to its distributed nature, Kubernetes can be highly available, scalable, and fault-tolerant. Here is how this distributed system functions:

• Control Plane: The top layer or the central control pane is designed to control the state of the cluster. It handles all the decisions regarding the manner and locations of application deployments.
• Worker Nodes: These nodes are where the applications packaged in containers (referred to as Pods) reside. These are the ones who take instruction from the control plane and are referred to as ‘workers’.

Kubernetes Architecture Diagram

At a high level, the Kubernetes architecture consists of two main types of nodes:

• Master Node (Control Plane): The management layer that controls the overall Kubernetes cluster. It consists of a cloud controller manager, etcd, scheduler, etc.
• Worker Nodes: These are the nodes where containers are executed. It consists of container runtime, kubelet, kube-proxy, etc.

Here is the simplified working of a Kubernetes architecture:

1. Master Node and Worker Nodes

The master node is the brain of the Kubernetes cluster. It holds the components tasked with managing the proper state of the cluster as well as coordinating the deployment of applications. A worker node is where the workload happens and consists of several components such as kubelet, kube-proxy, and container runtime.

2. Cluster

K8s cluster is defined as a collection of worker nodes and master nodes that provide containerized application deployment and management capabilities. It is simply the environment in which your containers and applications are launched and operated. The cluster allows the constituents to interact with each other as well enabling fault tolerance and service availability.

3. Pods

K8s does not offer Mac addresses outside of the cluster networks, K8s defines a basic container deployment unit as a pod. Pods are the units to deploy and manage applications as they are containers that reside on worker nodes.

Also Read: What is Pod in Kubernetes?

Kubernetes Architecture Component

Understanding the Kubernetes architecture is crucial and involves navigating to each component of the architecture by learning its functionalities. Below is a diagram showing the Kubernetes architecture components:

Master Node (Control Pane)

Kubernetes Master Node is often said to be the ‘brain’ of the system as it controls the whole Kubernetes cluster. The Master Node is in charge of the cluster and is therefore composed of several components that interact with each other to enable the Kubernetes environment to run smoothly. Among these components include systems that maintain consistent cluster states, schedule workloads, and ensure that the intended objects in the cluster are operational.

Components of the Master Node

1. API Server

The entry point to all the requests clients are making on the Kubernetes cluster is the API Server. It has a REST interface that exposes the control plane of the Kubernetes to the users, components, and even third-party systems.

Functions:

• Client Requests: It receives requests issued by users and sends such requests to other components like Controller Manager or Scheduler.
• Cluster State Management: It permits both reading from and writing into the state of the cluster. Every command sent to Kubernetes has to go through the API Server.
• Authentication & Authorization: It makes sure that any request made to the cluster is first wrapped in a verified identity and one that is allowed to make that request.
• Validation: The schema and rules of Kubernetes are enforced over the incoming requests to validate them.

2. Controller Manager

The Controller Manager is tasked with the job of ensuring that the cluster is always in a certain specified configuration. The cluster configuration is monitored by the API server and the controller manager modifies the configuration as needed.

Types:

• Deployment Controller: Verifies that the number of Pods in existence at any one time does not exceed those specified in the Deployment declaration.
• ReplicaSet Controller: Guarantees that Alaska replicas of a given pod must equal the number stated.
• Node Controller: In charge of managing the nodes’ lifecycle, including identifying when they are malfunctioning.
• Job Controller: Oversees batch job execution and makes sure the right amount of pods are operating for the job.

Function: As determined by user configurations, the controller manager regularly checks the cluster’s present state with the intended state and makes necessary adjustments (e.g., generating Pods, scaling resources).

3. Scheduler

The task of choosing which worker node will run a new pod is handled by the Scheduler. It decides, based on resource availability and policies, which nodes should run pods. The scheduler also cooperates with the controller manager in implementing the desired state of the cluster.

Functions:

• Scheduling Pods: It picks all pending pods and places them on the most appropriate node in the cluster on the basis of factors like CPU and memory load, storage devices, utilization level as well, etc.

4. Etcd

etcd is a distributed key-value storage that became not only a store of all configuration data and the state of the cluster but a single point of truth for the Kubernetes cluster as well. It manages the consistency of all components of Kubernetes by making sure all of them can retrieve information on the current status of the cluster.

Functions:

• Cluster State Storage: This is a set of services that allow the storage of various data in a cluster such as pod properties, node properties, secrets, service discovery, etc.
• Data Persistence: etcd ensures that available critical cluster state data remains consistent so that in case of a system crash, Kali can rectify the issue by reading the cluster’s state in etcd.
• High Availability: etcd clustered includes independent instance and hardware module which takes multiple copies of etcd on other machines. This is done to ensure data replication and availability of access control.

Worker Nodes

The Worker Nodes in Kubernetes are the nodes on which the actual applications (the containers) run. The execution of the workloads is possible through these nodes which are cascaded under the Kubernetes control plane or the master node. While the Master Node is the authority in terms of the decisions and the state of the Cluster, the Worker Nodes are just the machines that run the containers also referred to in this instance as Pods. Worker Nodes are crucial elements to ensure the scalability and good performance of Kubernetes workloads.

Components of the Worker Node

1. Kubelet

Every Worker Node has a primary agent known as the Kubelet. About the directives from the control plane, oversees the start-up, operation, and termination of containers.

Functions:

• Pod Management: The Kubelet is responsible for maintaining and controlling the modified access to Pods assigned to it at the node.
• Health Checks: It uses readiness and liveness probes to routinely inspect the health of a certain container, assuring that its operations are as they were designed and intended to be.
• Synchronization: It allows the state of the node to be updated by having the status of the containers and workloads carried on that node sent to the API Server.
• Configuration: The Kubelet guarantees that the environment variables, volume mounts, and any other relevant and necessary settings that could ensure the containers run properly are already set in the Pods.

2. Kube-Proxy

The Kube-Proxy is responsible for managing network traffic within the Kubernetes cluster. Cluster components make available network and Load balancing of Pods and services through the Kube-Proxy.

Functions:

• Service Discovery: An apparent limitation of Kubernetes is that only Pods that learned about another service so never receive direct requests, therefore Kube-Proxy has to create networking rules to assist the service reach other services or Pods.
• Load Balancing: Kube-Proxy supports the deployment of a Load balancer for services and promotes the business of such services by assuring the movement of foot traffic to many Pods that host the service.
• IP Tables and IPVS: Traffic routing between pods using iptables( or also IPVS when needed) is managed by kube-proxy. This guarantees that any traffic sent to the virtual IP of a service will indeed reach the intended pod.

3. Container Runtime

The container runtime helps in running containers on the worker nodes. Kubernetes comes with a couple of container run-time, one of which is Docker, CRI-O, and many more.

Functions:

• Image Management: The container runtime pulls images of containers from local storage and a container registry such as a docker hub and caches them onto the node.
• Container Lifecycle: The kubelet requests the container runtime to start or stop containers according to pod specifications.
• Resource Management: It implements a set of container resource requirements including memory and CPU usage so that pods will not use more than what the node can support.

Also Read: An Introduction to Kubernetes And Containers

Kubernetes Cluster Addon Components

Along with the Master Node, Worker Nodes, Kubelet, and Kube-Proxy, there exist several add-on components in Kubernetes that provide more functionality to the cluster. The add-on components provide the basic functionalities including networking, monitoring, logging, and securing the resources with the aim of making the operations of Kubernetes clusters seamless and scalable.

Some of the main Addon components include:

• CoreDNS

Purpose: In every Kubernetes cluster, CoreDNS is the default DNS server for the cluster. It provides a way for service and pod lookups as it uses DNS as an address resolution mechanism for clusters.

Function: Whenever pods or services are created in a Kubernetes cluster, CoreDNS provides human-readable names to pods and services so that other pods can easily access them without having to know their IP addresses. CoreDNS makes it easier for applications in the clusters to locate each other.

• Kubernetes Dashboard

Purpose: The Kubernetes Dashboard provides an interface that is easy to use for the deployment and oversight of Kubernetes clusters using a web application.

Function: It allows for easy navigation, cluster resources such as Pods, services, deployments, and namespaces can be used as well. It also allows the application managers to deploy and fix any problems with the applications and check on the status of the Pods and logs.

• Metrics Server

Purpose: The Metrics Server is a component that collects usage data about Pods and Nodes regarding the usage of various resources such as CPU and memory.

Function: It has the capability also to facilitate autoscaling by providing metrics from which the number of Pods in a deployment may be scaled according to the resources that are currently used.

• CNI Plugin

Purpose: Container networking interface (CNI) is a plugin-based architecture. It helps in setting up a network for Pods enabling communication among Pods as well as with the external world.

Function: Allocates IP addresses for Pods ensuring that each of them has a unique IP address in the cluster. Also, defines route maps for the network so pod-to-pod communication in different nodes is enabled.

• Helm

Purpose: Helm is the counterpart of RPM in Kubernetes; it is a package manager that makes it easier to deploy complex applications.

Function: With Helm, you can create, and manage Kubernetes applications deployed via Helm charts which is a packaging format containing all the K8 resources needed for the application in a templatized and versioned form.

• Ingress Controllers

Purpose: Ingress controllers provide load balancer functionality and external accessibility of services running in a Kubernetes cluster.

Function: Users can specify Ingress resources which define how HTTP and HTTPS requests should be managed within the cluster providing load balancing features as well as SSL offloading or more intricate routing schemes as part of the requests.

How Kubernetes Components Work Together

To ensure that our applications are deployed, managed, and scaled in the desired way, Kubernetes’s components work in a distributed manner. To summarize how these elements interact, let us go through the deployment process step by step.

1. Creating a Deployment

Deployment is a concept in Kubernetes for managing applications where Deployment is defined at a high level. While defining a Deployment, you mention the needs such as the number of copies (Pods), container image requirements, resources, environment variables, etc.

The API Server receives the Deployment definition through kubectl or an API call. While Controller Manager aims to maintain the desired state of deployment by generating pods whenever necessary. The Scheduler runs the allocation of pods to the available Worker Nodes based on nodes’ resources and constraints. Once scheduling is done, the container image is pulled by Kubelet on the Worker Nodes and the containers are initiated.

2. Scheduling Pods

The Scheduler must decide which Worker Node hosts the Pods that those Pods should be run on. After Pods have been scheduled, the Kubelet on the GCP selected node is tasked with the creation and management of the Containers within the Pods.

3. Communicating Between Pods via Services

Kubernetes Pods are dynamic, which implies that they can be created or removed at any time. Destroyed Pods will potentially be lost in terms of data and user history. To enable deploying different components and also allowing them to communicate, Kubernetes provides a feature called Services. A Service provides an abstraction layer that determines several specifications like a set of Pods and a policy for accessing them It sets a stable DNS name that can be used by the other Pods for communication.

4. Scaling the Deployment

Kubernetes allows applications to be scaled out easily by adding more Pods to a Deployment. Scaling might be performed in either manual fashion, using the kubectl scale command or it can be performed automatically through Horizontal Pod Autoscalers (HPA) which increases or decreases the number of Pods depending on CPU or memory consumption respectively.

5. Handling Failures

Kubernetes is well-designed to cover a lot of failure cases to meet the desired state of applications. If for any reason a Pod crashes or becomes unhealthy such as a failed liveness probe, kubelet is designed to restart the pod. In the case of a node going down, the node controller discovers the dead node, and the containing Pods are moved to other operational nodes in the cluster.

Best Practices of Kubernetes Architecture

Kubernetes is gaining popularity at a fast pace. However, the complexities associated with managing Kubernetes clusters need to be controlled by implementing these below-mentioned best practices:

1. Design for High Availability

The availability of a master node guarantees that your control plane is fault-tolerant. This might require deploying several API Servers etc., across a cluster or a multi-region deployment. Spread your Worker Nodes across multiple availability zones so that if one zone fails the system is still available.

2. Proper Resource Requests and Limits

Impose resource requests and limits for containers to avoid high resource consumption which can result in instability and performance degradation. Adopt Kubernetes resource limits to control namespace inhabitants from using the added resources beyond limits.

3. Use Namespaces for Logical Isolation

Apart from the default namespace, Kubernetes has provisioned you the ability to isolate workloads logically with the use of Namespaces. Those cover more logical details such as structure and administration of resources, allowing different rules in separate places (for example, dev, staging, production).

4. Leverage Labels and Annotations

Use labels when Pods have to be grouped and selected based on specified characteristics. This is useful for complex deployments or selector-based usage for Services and ReplicaSets.

5. Automate Scaling and Management

To automatically scale pods according to resource utilization metrics like CPU or memory, use Horizontal Pod Autoscalers (HPA). Depending on the cluster’s total resource needs, Cluster Autoscaling can automatically add or delete Worker Nodes.

6Secure Your Cluster

Turn on Role-Based Access Control (RBAC) to limit resource access according to user roles and responsibilities. By restricting access to only essential services, Network Policies can improve security by managing communication between pods and services.

Conclusion

In this article, we have gained an in-depth understanding of Kubernetes architecture diagram starting from its Master Node, Worker Nodes as well as other constituent elements that closely work together towards making Kubernetes functional at a big scale. We have also studied the deployment lifecycle, how components communicate, and the guidelines for effective cluster operation.

Kubernetes is still important in containerized applications management, so one needs to understand its architecture when dealing with container orchestration in contemporary cloud-based systems. Enrol in the Certificate Program in DevOps & Cloud Engineering with Microsoft by Hero Vired to master kubernetes.