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Question 147 - Certified MuleSoft Integration Architect I discussion

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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
Answers
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
Answers
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
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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
Answers
D.
Conduct scaled-down performance tests in the staging environment against rate-limiting back-end system. Then upscale performance results to full production scale
Suggested answer: C
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asked 23/09/2024
Samori Augusto
43 questions
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