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Answer: Utilize your existing CI/CD pipeline to deploy the Docker images to Cloud Run, adjusting configurations and access points as necessary.
Option A is correct because it leverages the existing CI/CD pipeline for deploying Docker images to Cloud Run, facilitating a smooth transition to a serverless environment in Google Cloud with minimal code alterations. Adjustments to configurations and endpoints are straightforward in this scenario. Option B is incorrect as Cloud Functions are tailored for event-driven functions, not for hosting complex microservices like those in the described e-commerce platform. Moreover, replicating on-premises configurations may not be feasible in a serverless setup. Option C is also incorrect for similar reasons; Cloud Functions are unsuitable for complex microservices, and managing each service as a separate function could complicate scalability and administration. Option D is incorrect because while Cloud Run is appropriate for containerized applications, maintaining on-premises configurations without modifications might not be compatible with the serverless environment.
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You are managing an e-commerce platform hosted in your on-premises data center. This platform is built using multiple Python-based microservices, each running in its own Docker container, and utilizes environment variables for configuration management. What is the most efficient way to deploy this application on a serverless solution in Google Cloud with minimal code changes?
A
Utilize your existing CI/CD pipeline to deploy the Docker images to Cloud Run, adjusting configurations and access points as necessary.
B
Deploy the Docker images to Cloud Functions using your current CI/CD process, ensuring the configuration matches the on-premises setup.
C
Directly deploy each microservice as a separate Cloud Function from your current codebase, modifying configurations and interfaces where needed.
D
Deploy each microservice individually on Cloud Run from your existing codebase, keeping the on-premises configurations unchanged.