You need to refactor a traditional EC2-hosted web application into container-based microservices in two separate environments (production and testing). Load varies but you know the minimum and maximum expected load. You want a serverless design that minimizes operational overhead and is most cost-effective. Which solution should you choose?
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Correct answer: Push container images to Amazon ECR. Create two auto-scaled Amazon ECS clusters using the Fargate launch type (one for production and one for testing). Run tasks from the ECR images and place an Application Load Balancer in front of each ECS cluster..
Why this is the answer
The correct solution leverages Amazon ECS with Fargate, providing a serverless container orchestration platform that minimizes operational overhead by eliminating the need to manage EC2 instances. Auto-scaling ECS clusters ensure cost-effectiveness by adjusting resources based on load, paying only for the compute capacity consumed. ECR is the standard for container image storage. An Application Load Balancer efficiently distributes traffic. AWS Lambda container functions are suitable for event-driven, short-lived tasks, but less ideal for traditional web applications with varying, sustained load, and concurrency limits might not effectively handle peak web traffic. Amazon EKS with Fargate offers similar benefits to ECS with Fargate but introduces the complexity of Kubernetes, which is unnecessary given the requirement for minimal operational overhead for a refactored web application. AWS Elastic Beanstalk is a good option for simplified deployments but doesn't inherently offer the same granular serverless control over containerized microservices as ECS Fargate, and it might incur higher costs due to underlying EC2 instance management, even if abstracted.
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