Kubernetes is an open source platform that helps automate the deployment, scaling, and management of containerized applications. It groups containers into clusters and manages them as a single entity. Stable and efficient operation of the services is thus guaranteed. With features like load balancing, self-healing, and phased deployments, Kubernetes makes operating modern applications much easier.
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What is Kubernetes?
Kubernetes (K8s) is an open source container orchestration system, initially developed by Google and now maintained by the Cloud Native Computing Foundation (CNCF). It administers containerized applications in distributed environments by automating startup (and restart), scaling, monitoring, and automatic replacement of failing containers.
Its architecture, written in Go language (Golang), is based on a control plane and several worker nodes, with different components such as the scheduler (Scheduler), responsible for central management. Using declarative configurations (e.g. in YAML files), we define the desired state of the system, which Kubernetes strives to maintain at all times. The tool can be used both in the Cloud, on local computers and in data centers On-Premises.
Note
In the first versions of Kubernetes, we spoke of a “master node” (master node). The official documentation now uses the term control plan (control plane), more precise and inclusive. Likewise, the machines that run applications were once only called minions ; today they are referred to as worker nodes (worker nodes).
Kubernetes is a container orchestration system. This means that the software does not create containers, but manages them. To do this, Kubernetes relies on process automationmaking it simpler for developers to test, maintain, and deploy applications. The Kubernetes architecture is based on a clear hierarchy:
- Container : contains applications and their software environments.
- Pod: The basic unit of Kubernetes, a pod groups together one or more containers that share the same network and storage resources.
- Node: executes one or more pods Kubernetes and can correspond to a virtual or physical machine.
- Cluster: groups several nodes into one cluster Kubernetes.
The Kubernetes architecture is also based on principle of the control plan and worker nodes. These correspond to the executed parts of the system, managed and controlled by the control plane.
The role of the control plane is, for example, to distribute the pods across the nodes. Thanks to a continuous monitoringit automatically intervenes when a node fails and can reassign or recreate the affected pods to compensate for the failure. The current state is constantly compared to the desired state and adjusted if necessary. The control plane also serves as an access point for administrators, who orchestrate containers through it.
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Kubernetes node
The worker node is a physical or virtual server on which one or more containers run. It includes a dedicated runtime environment for containers. There we also find the Kubeletan agent responsible for communicating with the control plane, which starts and stops containers. With cAdvisor, the Kubelet integrates a service that records resource usage, useful for performance analysis. Finally, the Kube-proxy allows the system to ensure the Load Balancing and establish network connections over TCP or other protocols.
Kubernetes control plane
The control plane is also a server (or a set of servers). To control and monitor worker nodes, it runs the Controller Managera component that brings together several processes:
- THE Node Controller monitors nodes and reacts when one fails
- THE Replication Controller ensures that the desired number of pods are running simultaneously; in modern configurations it is replaced by ReplicaSetstypically managed through deployments
- L'Endpoint Controller manage objects
endpointresponsible for ensuring the connection between services and pods - THE ServiceAccount and Token Controller Administers namespace and creates API access tokens
In addition to the Controller Manager, a database called etcd is used. In this key-value database, the cluster configuration is stored and managed by the control plane. The component Scheduler automates the distribution of pods to worker nodes. Communication with the nodes goes through theAPIServerintegrated into the control plane, which provides a REST interface and exchanges data in JSON format. Thanks to this interface, the different controllers can interact effectively with the nodes.
Kubernetes and Docker: complementarity or rivalry?
The question of who performs better in the Kubernetes vs Docker comparison doesn't really arise, because both tools are designed to work together. Docker (or another container platform like rkt) builds and runs the containers, while Kubernetes accesses them for orchestration and process automation. Kubernetes alone does not support creating containers.
The real competition lies rather with Docker Swarma tool dedicated to Docker orchestration. It also works with clusters and offers features similar to those of Kubernetes.
What are the advantages of Kubernetes?
Kubernetes offers many benefits that enhance scalability, operational reliability, and efficiency.
✓ Automated scalability: Kubernetes uses resources optimally. Instead of letting machines run idle, it frees up those resources for other tasks or pauses them, thereby reducing costs.
✓ High fault tolerance: Thanks to replication and automatic recovery, applications continue to work even if certain components fail.
✓ Optimized use of resources: Pods and containers are intelligently distributed across available nodes to optimize computing power.
✓ Simplified deployment and rollbacks: New application versions can be deployed with minimal effort, and rapid rollback to previous versions remains possible if necessary.
✓ Platform independence: Kubernetes runs on local servers, in the Cloud or in a Hybrid Cloud, ensuring workload portability.
✓ Service discovery and load balancing: Kubernetes automatically detects services in the cluster and distributes traffic in a balanced manner, without requiring an external load balancer.
✓ Efficient management by API: Thanks to a central API, all components of the cluster can be administered and automated, including via external tools and CI/CD pipelines.
What is Kubernetes used for?
Kubernetes is best suited when applications run in containers and a scalable, highly available infrastructure is required. Here are some typical use cases:
- Microservice architectures: In practice, K8s is often used to manage microservices architectures, where many small services are developed, tested, and maintained independently. Businesses rely on Kubernetes to automate development and production environments and respond more quickly to new requirements.
- CI/CD: Kubernetes is widely used in continuous integration (CI) and continuous deployment (CD) because it can reliably automate deployments and manage releases.
- Multi-Cloud and Hybrid Cloud: In Multi-Cloud or Hybrid Cloud strategies, Kubernetes deploys workloads (workloads) independent of platforms and allows them to be easily moved between different Cloud providers or data centers.
- Big Data: Kubernetes is also suitable for projects of Big Data and of Machine Learningwhere many ephemeral containers operate in parallel.
- Large platforms: For platforms with a large number of users, Kubernetes is essential to automatically absorb traffic peaks and ensure service resilience.
