Description: Amazon Elastic Kubernetes Service (EKS) is a managed Kubernetes service that simplifies the deployment, management, and scaling of containerized applications using Kubernetes on the Amazon Web Services (AWS) cloud. EKS allows developers and operations teams to focus on building applications without worrying about the complexity of the underlying infrastructure. This service handles the management of the Kubernetes infrastructure, including node configuration, software updates, and security management. EKS is highly scalable and natively integrates with other AWS services, such as Amazon EC2, Amazon RDS, and Amazon S3, enabling users to leverage a wide range of tools and services offered by the platform. Additionally, EKS is compatible with Fargate, a serverless compute engine that allows running containers without managing servers, further simplifying the process of deploying and scaling containerized applications. In summary, Amazon EKS provides a robust and efficient solution for container orchestration, enabling organizations to effectively adopt DevOps practices and microservices.
History: Amazon EKS was launched in June 2018 as part of Amazon Web Services’ strategy to provide container orchestration solutions. Since its launch, it has evolved to include features such as integration with AWS Fargate, allowing users to run containers without managing the underlying infrastructure. Over the years, EKS has been adopted by numerous companies seeking to simplify the management of their containerized applications and improve scalability.
Uses: Amazon EKS is primarily used to deploy and manage containerized applications in production environments. It enables organizations to adopt microservices architectures, facilitating the scalability and resilience of applications. It is also used to run various workloads, including machine learning, application development and testing, as well as for migrating traditional applications to containers.
Examples: An example of using Amazon EKS is an e-commerce company deploying its sales platform using microservices in containers, allowing for rapid scaling during peak seasons. Another example is a tech startup using EKS to run machine learning models in containers, facilitating the development and deployment of their artificial intelligence solutions.
