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One of the backend systems involved by the API implementation enforces rate limits on the...

One of the backend systems involved by the API implementation enforces rate limits on the number of request a particle client can make.

Both the back-end system and API implementation are deployed to several non-production environments including the staging environment and to a particular production environment. Rate limiting of the back-end system applies to all non-production environments.

The production environment however does not have any rate limiting.

What is the cost-effective approach to conduct performance test of the API implementation in the non-production staging environment?

A.

Including logic within the API implementation that bypasses in locations of the back-end system in the staging environment and invoke a Mocking service that replicates typical back-end system responses

Then conduct performance test using this API implementation

B.

Use MUnit to simulate standard responses from the back-end system.

Then conduct performance test to identify other bottlenecks in the system

C.

Create a Mocking service that replicates the back-end system's

production performance characteristics

Then configure the API implementation to use the mocking

service and conduct the performance test

D.

Conduct scaled-down performance tests in the staging environment against rate-limiting back-end system. Then upscale performance results to full production scale

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