Which solution will meet these requirements MOST cost-effectively?
Upload the container images to AWS Lambda as functions. Configure a concurrency limit for the associated Lambda functions to handle the expected peak load. Configure two separate Lambda integrations within Amazon API Gateway: one for production and one for testing.
Upload the container images to Amazon Elastic Container Registry (Amazon ECR). Configure two auto scaled Amazon Elastic Container Service (Amazon ECS) clusters with the Fargate launch type to handle the expected load. Deploy tasks from the ECR images. Configure two separate Application Load Balancers to direct traffic to the ECS clusters.
Upload the container images to Amazon Elastic Container Registry (Amazon ECR). Configure two auto scaled Amazon Elastic Kubernetes Service (Amazon EKS) clusters with the Fargate launch type to handle the expected load. Deploy tasks from the ECR images. Configure two separate Application Load Balancers to direct traffic to the EKS clusters.
Upload the container images to AWS Elastic Beanstalk. In Elastic Beanstalk, create separate environments and deployments for production and testing. Configure two separate Application Load Balancers to direct traffic to the Elastic Beanstalk deployments.
Explanations:
AWS Lambda is not ideal for running container images directly as it is primarily designed for short-lived functions. While Lambda supports container images, it does not provide the operational flexibility needed for managing two distinct environments (production and testing) efficiently. Additionally, it may not handle variable loads as effectively as other options.
Using Amazon ECR with auto-scaled Amazon ECS clusters leveraging the Fargate launch type is a cost-effective solution for running microservices. This setup allows for managing variable loads efficiently with minimal operational complexity. Separate Application Load Balancers can be configured for production and testing, meeting the requirement of distinct environments.
While using Amazon EKS with Fargate provides flexibility, it introduces more operational complexity compared to ECS, particularly in managing Kubernetes configurations and scaling. For the requirements given, ECS with Fargate is a more straightforward and cost-effective solution for managing microservices in this scenario.
AWS Elastic Beanstalk simplifies application deployment but is not as cost-effective for running containerized microservices as ECS with Fargate. Additionally, it doesn’t align with a serverless architecture as effectively as the other solutions, potentially leading to higher operational overhead.