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Introduction
Kubernetes is an open-source platform used to manage and orchestrate containerized applications. It helps automate the deployment, scaling, and management of containerized applications in a flexible and efficient way.
In this blog, we will discuss about Kubernetes architecture. We will also discuss the working of Kubernetes architecture. So, let's get started.
What is Kubernetes Architecture?
Kubernetes architecture is designed to provide a robust and scalable platform for managing containerized applications. The key components include the API server, etcd (a distributed key-value store for configuration data), scheduler, and controller manager. Kubernetes architecture is crucial for modern application deployment and management due to its powerful features and benefits. One of the primary reasons for its importance is container orchestration.
Kubernetes automates the deployment, scaling, and management of containerized applications, simplifying the complexities of running distributed applications. It enables seamless scaling based on demand, ensuring optimal resource utilization and high availability. Moreover, Kubernetes is designed to be resilient, automatically handling node failures and ensuring applications are always available and running. Its efficient resource allocation prevents wastage and maximizes hardware utilization. Kubernetes also provides built-in load balancing, distributing incoming traffic to maintain performance and reliability.
Overview of Kubernetes Architecture
Kubernetes has a master-worker architecture resembling a ship's steering wheel that manages applications in containers.
Master Server: The master node is an essential component of the cluster, responsible for coordinating and managing the entire system.
Node (Workers): Worker nodes are Linux-based machines where containers are scheduled and run, handling application workloads.
The architecture of Kubernetes looks like:
Basic Components of Kubernetes Architecture
The basic components of Kubernetes architecture consist of two main parts: the master server and the nodes (or workers). The master server is a crucial component responsible for managing and coordinating the entire Kubernetes cluster. It includes various essential components like the API server, scheduler, controller manager, and etcd, which act as a distributed key-value store for configuration data.
On the other hand, the nodes are worker machines in the cluster where containers are scheduled and executed. Each node has a Kubelet, which is responsible for communicating with the master and managing containers on the node. The combination of the master server and nodes allows Kubernetes to efficiently orchestrate containerized applications, ensuring seamless deployment, scaling, and management.
Kubernetes Control Plane Components
It is the master node of Kubernetes. If we were to manage all these pods (which we learned earlier in this article) present on each node, handling them would become almost impossible. So this is when the Kubernetes control plane helps. This is also one of the significant advantages of Kubernetes. So all these pods are managed by the Kubernetes control plane. Its primary role is to handle all this by providing an API, defining, deploying, and managing the pods.
Let's learn about the components that make up the control plane and their respective roles. All these control components are essential to perform actions in the cluster.
Kube- API Server
The API-Server handles data validation and configuration for all API objects. It acts as an entry point for any request to access the server; it validates if the user is authentic. The kube-API Server manages the API calls for creation, deletion, scaling up pods, or storing the data in the ETCD (originated from two ideas, the Unix “/etc” folder and “d”- distributed systems) database. It also handles the interaction between the master and worker nodes. All the components of the control plane interact with the kube-API server. The API server performs all the actions within the cluster.
Kube Scheduler
The Kube scheduler is responsible for deciding where exactly a pod will run. It determines the best suitable node for the pods as the pods have different resource requirements, and the node has other resource limits. It makes sure the pod goes to a node that can handle it. After deciding, the Kube scheduler sends this information to the API server.
ETCD Database
It holds all the important data that Kubernetes uses in key-value form. It stores the number of pods and nodes present in the cluster. The API server interacts with the ETCD database and stores the information regarding the pod launching in a particular node. ETCD client is a command-line client through which we can access the information in the ETCD database. ETCD database can't be accessed directly by another control plane component.
Controller Manager
It acts as the brain of Kubernetes as the core Kubernetes logic takes place here. Its fundamental responsibility is life-cycle management, as it makes sure all the components are working properly. It contains different controllers that have various roles. All these controllers monitor the status of a particular component. Let's look at some of these.
Node Controller
It monitors the status of the node. If a node gets down, the node controller has to recreate that node. It maintains the desired count of nodes in the cluster.
Replication Controller
It monitors the status of pods. After a specific time interval, they check the status of pods. If any pod gets damaged, it recreates that pod. It makes sure that desired count of pods is present in the cluster.
Kubernetes - Worker Nodes Components
Worker nodes are a critical part of the Kubernetes architecture responsible for running and managing containers. They form the backbone of the cluster, executing the workload and hosting the applications. The main components of Kubernetes worker nodes are:
Node
Node here is the server or the virtual machine on which Kubernetes is working. We can have more than one master and n number of workers. In Kubernetes, we operate on clusters which are groups of one or more worker nodes. Each of these nodes contains the services that are needed to run pods.
Pod
It is the smallest deployable unit of Kubernetes where we deploy our application. But we learned earlier in this article that a container does the same. The pod is a wrapper for the container. We can deploy multiple containers with the same storage, resources, and network in one pod.
Kubelet
Kubelet handles all the activities happening in the node and is called the node manager. When the AI server requests the kubelet to create a container, it further requests the docker, which creates that container. When the container is created, the kubelet returns the status of pods to API- server, and the API server updates this information in the ETCD database.
Kube Proxy
It is the last control plane component responsible for all the communication between the Pods. It runs on each node present in the cluster. It regulates network rules on these nodes. These network rules allow communication to the pods from networks inside or outside the cluster.
Container Runtime Engine
The container runtime is responsible for executing and managing containers on the worker nodes. Kubernetes supports multiple container runtimes, with Docker being one of the most commonly used. The container runtime ensures that containers are created, started, and stopped as required by Kubernetes.
How does Kubernetes Architecture work?
So whenever the user requests the kube - API server to create a pod, it follows the following steps -
It creates a pod, considering the amount of space or resources available.
Now a container has to be created when it has created a wrapper.
So the Kube Scheduler decides the best suitable node (as per the created pod) to schedule the pod.
Then the Kube-API server requests the kubelet of that node to schedule the pod.
The kubelet requests the docker to create a container within that pod.
With this being done, kubelet returns the pod's status to the Kube-API server.
Then the kube API-server updates the ETCD database providing it with the information of the node in which the pod has been scheduled.
Kubernetes Architecture Best Practices
Kubernetes architecture best practices are essential to ensure the successful deployment, scaling, and management of containerized applications. Some key best practices include:
High Availability: Design your Kubernetes cluster with redundancy and fault tolerance in mind. Ensure that critical components, such as the master node and etcd, are deployed in a highly available configuration to avoid single points of failure.
Resource Allocation: Carefully allocate resources to containers based on their actual requirements. Avoid overcommitting resources, which can lead to performance issues and contention. Utilize Kubernetes resource limits and requests appropriately to optimize resource utilization.
Security: Implement robust security practices to protect your cluster and applications. Use Role-Based Access Control (RBAC) to grant appropriate permissions to users and components. Regularly update Kubernetes components and container images to avoid security vulnerabilities.
Networking: Plan and configure networking appropriately for your applications. Use Kubernetes Services and Ingress resources to expose and load balance services effectively. Consider using Network Policies to control the communication between pods.
Monitoring and Logging: Set up comprehensive monitoring and logging solutions to gain insights into cluster performance and application behavior. Utilize tools like Prometheus, Grafana, and ELK (Elasticsearch, Logstash, Kibana) stack for monitoring and logging.
Pod Design: Design your pods with a single responsibility, following the "Single Responsibility Principle." Avoid running multiple applications or unrelated processes within the same pod.
Frequently Asked Questions
What is a Kubernetes Cluster?
A group of computers (nodes) working together to manage containerized applications is known as a Kubernetes cluster.
What type of architecture is Kubernetes?
Kubernetes is a container orchestration platform based on "master-slave" architecture. The "master" manages and controls the cluster, while the "slaves" (also called "nodes") run and manage the containerized applications.
Why are Kubernetes used?
Kubernetes helps to simplify application management, scaling, and updates. Supports high availability and efficient resource use.
How does Kubernetes handle container failures?
Kubernetes handle container failures by detecting failures and automatically restarts or reschedules containers for continuous operation.
Can Kubernetes be used with non-Linux environments?
Yes, Kubernetes be used with non-Linux environments. It supports various operating systems, including Windows and macOS, for multi-platform environments.
Conclusion
In this article, we learned about the architecture of Kubernetes and how an application is deployed in Kubernetes. We discovered the advantages of Kubernetes, including its ability to handle high traffic, auto-scaling, and robust container management. We learned how by leveraging Kubernetes, organizations can achieve greater efficiency in their application deployment.
To learn more about Kubernetes, we recommend reading the following articles:
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