MuleSoft-Platform-Architect-I Exam Dumps : Salesforce Certified MuleSoft Platform Architect (Mule-Arch-201)

Explanation

Correct Answer: A CloudHub worker fails with an out-of-memory exception.

*****************************************

>> An AWS Region itself going down will definitely result in an outage as it does not matter how many workers are assigned to the Mule App as all of those in that region will go down. This is a complete downtime and outage.

>> Extended outage of API manager during initial deployment of API implementation will of course cause issues in proper application startup itself as the API Autodiscovery might fail or API policy templates and polices may not be downloaded to embed at the time of applicaiton startup etc... there are many reasons that could cause issues.

>> A network outage onpremises would of course cause the Order Management System not accessible and it does not matter how many workers are assigned to the app they all will fail and cause outage for sure.

The only option that does NOT result in a service outage is if a cloudhub worker fails with an out-of-memory exception. Even if a worker fails and goes down, there are still other workers to handle the requests and keep the API UP and Running. So, this is the right answer.

Explanation

Correct Answer: Create a bounded-context model for the system layer to closely match the backend data model, and add an anti-corruption layer to let the different bounded contexts cooperate across the system and process layers

*****************************************

>> Canonical models are not an option here as the organization has already put in efforts and created bounded-context models for Experience and Process APIs.

>> Anti-corruption layers for ALL APIs is unnecessary and invalid because it is mentioned that experience and process APIs share same bounded-context model. It is just the System layer APIs that need to choose their approach now.

>> So, having an anti-corruption layer just between the process and system layers will work well. Also to speed up the approach, system APIs can mimic the backend system data model.

Understanding Coarse-Grained vs. Fine-Grained API Design:

A coarse-grained design consolidates multiple operations within a single API, leading to fewer APIs but with more complex implementations. Conversely, a fine-grained design breaks down functionalities into smaller, more specific APIs, resulting in simpler implementations but a larger number of APIs.

Evaluating the Options:

Option A (Correct Answer): With a coarse-grained design, each API handles more functionalities, increasing the complexity of each API implementation as it needs to manage more use cases and logic.

Option B: A coarse-grained design typically reduces the number of APIs, so fewer discoverable assets are available.

Option C: Fewer APIs generally mean fewer connections between them in the application network.

Option D: Network infrastructure usage may actually decrease with fewer APIs, as there are fewer calls between APIs.

Conclusion:

Option A is the correct answer, as the complexity of each API implementation increases in a coarse-grained design due to the consolidation of multiple functionalities into single APIs.

Refer to MuleSoft’s documentation on API design principles and best practices for coarse-grained vs. fine-grained API implementation.