Which solution will meet these requirements in the MOST operationally efficient way?
Create a custom Docker image that contains all the dependencies for the legacy application. Store the custom Docker image in a new Amazon Elastic Container Registry (Amazon ECR) repository. Configure a new AWS CodeBuild project to use the custom Docker image to build the deployable artifact and to save the artifact to the S3 bucket.
Launch a new Amazon EC2 instance. Install all the dependencies for the legacy application on the EC2 instance. Use the EC2 instance to build the deployable artifact and to save the artifact to the S3 bucket.
Create a custom EC2 Image Builder image. Install all the dependencies for the legacy application on the image. Launch a new Amazon EC2 instance from the image. Use the new EC2 instance to build the deployable artifact and to save the artifact to the S3 bucket.
Create an Amazon Elastic Kubernetes Service (Amazon EKS) cluster with an AWS Fargate profile that runs in multiple Availability Zones. Create a custom Docker image that contains all the dependencies for the legacy application. Store the custom Docker image in a new Amazon Elastic Container Registry (Amazon ECR) repository. Use the custom Docker image inside the EKS cluster to build the deployable artifact and to save the artifact to the S3 bucket.
Explanations:
This option uses a custom Docker image that contains all dependencies, providing a consistent and reproducible build environment. AWS CodeBuild is a managed service that automatically builds the deployable artifact, ensuring operational efficiency. The artifact is stored directly in the existing S3 bucket, meeting the requirement for future deployments.
While launching an EC2 instance and manually installing dependencies can work, it is not operationally efficient. This approach requires manual management and maintenance of the EC2 instance, leading to higher operational overhead and potential inconsistencies in the build environment.
Although using EC2 Image Builder to create a custom image can automate the installation of dependencies, this option still requires launching an EC2 instance to build the artifact, which is less efficient than using a fully managed service like AWS CodeBuild. It adds complexity and operational overhead without significant benefits over option A.
This option involves creating an EKS cluster and using Fargate, which adds unnecessary complexity for simply building a deployable artifact. While it provides scalability, it is not the most operationally efficient solution for the stated requirements. Using EKS for this task is overkill compared to the simpler and more efficient solution offered by CodeBuild in option A.