If a DevOps team adopts AWS CloudFormation as their standardized method for provisioning public cloud resources, which scenario poses a challenge?

If a DevOps team adopts AWS CloudFormation as their standardized method for provisioning public cloud resources, which scenario poses a challenge?

• A. The team is asked to build a reusable code base that can deploy resources into any AWS region
• B. The team is asked to manage a new application stack built on AWS-native services
• C. The organization decides to expand into Azure and wishes to deploy new infrastructure using their existing codebase
• D. The DevOps team is tasked with automating a manual provisioning process

Answer: (C)

Relying on a single provisioning tool across multiple clouds creates portability challenges. CloudFormation is AWS-specific, understanding and provisioning AWS resources only. Trying to apply the same codebase to Azure would not work out of the box because Azure uses different resource types and deployment mechanisms (like ARM templates or Azure Resource Manager tooling). So expanding into Azure with the existing CloudFormation templates would require rewriting or swapping to a multi-cloud tool, which is why this scenario is the tricky one. The other scenarios fit well with CloudFormation. Templates can be reused across AWS regions to deploy the same stack in different geographic locations, as long as the resources are available in those regions. AWS-native services are exactly what CloudFormation is designed to provision, so building a new stack on AWS services aligns with the tool. Automating a manual provisioning process is a direct use case for CloudFormation, converting ad-hoc steps into repeatable infrastructure as code.

Relying on a single provisioning tool across multiple clouds creates portability challenges. CloudFormation is AWS-specific, understanding and provisioning AWS resources only. Trying to apply the same codebase to Azure would not work out of the box because Azure uses different resource types and deployment mechanisms (like ARM templates or Azure Resource Manager tooling). So expanding into Azure with the existing CloudFormation templates would require rewriting or swapping to a multi-cloud tool, which is why this scenario is the tricky one.

The other scenarios fit well with CloudFormation. Templates can be reused across AWS regions to deploy the same stack in different geographic locations, as long as the resources are available in those regions. AWS-native services are exactly what CloudFormation is designed to provision, so building a new stack on AWS services aligns with the tool. Automating a manual provisioning process is a direct use case for CloudFormation, converting ad-hoc steps into repeatable infrastructure as code.