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Salesforce Certified MuleSoft Platform Architect I Sample Questions (Q46-Q51):
NEW QUESTION # 46
What is a best practice when building System APIs?
- A. Build an Enterprise Data Model (Canonical Data Model) for each backend system and apply it to System APIs
- B. Document the API using an easily consumable asset like a RAML definition
- C. Expose to API clients all technical details of the API implementation's interaction wifch the backend system
- D. Model all API resources and methods to closely mimic the operations of the backend system
Answer: D
Explanation:
Correct Answer : Model all API resources and methods to closely mimic the operations of the backend system.
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>> There are NO fixed and straight best practices while opting data models for APIs. They are completly contextual and depends on number of factors. Based upon those factors, an enterprise can choose if they have to go with Enterprise Canonical Data Model or Bounded Context Model etc.
>> One should NEVER expose the technical details of API implementation to their API clients. Only the API interface/ RAML is exposed to API clients.
>> It is true that the RAML definitions of APIs should be as detailed as possible and should reflect most of the documentation. However, just that is NOT enough to call your API as best documented API. There should be even more documentation on Anypoint Exchange with API Notebooks etc. to make and create a developer friendly API and repository..
>> The best practice always when creating System APIs is to create their API interfaces by modeling their resources and methods to closely reflect the operations and functionalities of that backend system.
NEW QUESTION # 47
A business process is being implemented within an organization's application network. The architecture group proposes using a more coarse-grained application network design with relatively fewer APIs deployed to the application network compared to a more fine-grained design.
Overall, which factor typically increases with a more coarse-grained design for this business process implementation and deployment compared with using a more fine-grained design?
- A. The number of discoverable assets related to APIs deployed in the application network
- B. The usage of network infrastructure resources by the application network
- C. The number of possible connections between API implementations in the application network
- D. The complexity of each API implementation
Answer: D
Explanation:
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.
NEW QUESTION # 48
An API implementation is being designed that must invoke an Order API, which is known to repeatedly experience downtime.
For this reason, a fallback API is to be called when the Order API is unavailable.
What approach to designing the invocation of the fallback API provides the best resilience?
- A. Redirect client requests through an HTTP 307 Temporary Redirect status code to the fallback API whenever the Order API is unavailable
- B. Create a separate entry for the Order API in API Manager, and then invoke this API as a fallback API if the primary Order API is unavailable
- C. Set an option in the HTTP Requester component that invokes the Order API to instead invoke a fallback API whenever an HTTP 4xx or 5xx response status code is returned from the Order API
- D. Search Anypoint Exchange for a suitable existing fallback API, and then implement invocations to this fallback API in addition to the Order API
Answer: D
Explanation:
Correct Answer : Search Anypoint exchange for a suitable existing fallback API, and then implement invocations to this fallback API in addition to the order API
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>> It is not ideal and good approach, until unless there is a pre-approved agreement with the API clients that they will receive a HTTP 3xx temporary redirect status code and they have to implement fallback logic their side to call another API.
>> Creating separate entry of same Order API in API manager would just create an another instance of it on top of same API implementation. So, it does NO GOOD by using clone od same API as a fallback API. Fallback API should be ideally a different API implementation that is not same as primary one.
>> There is NO option currently provided by Anypoint HTTP Connector that allows us to invoke a fallback API when we receive certain HTTP status codes in response.
The only statement TRUE in the given options is to Search Anypoint exchange for a suitable existing fallback API, and then implement invocations to this fallback API in addition to the order API.
NEW QUESTION # 49
A system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. A process API is a client to the system API and is being rate limited by the system API, with different limits in each of the environments. The system API's DR environment provides only 20% of the rate limiting offered by the primary environment. What is the best API fault-tolerant invocation strategy to reduce overall errors in the process API, given these conditions and constraints?
- A. Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke a copy of the process API deployed to the DR environment
- B. Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment
- C. In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment; add timeout and retry logic to the process API to avoid intermittent failures; add logic to the process API to combine the results
- D. Invoke the system API deployed to the primary environment; add retry logic to the process API to handle intermittent failures by invoking the system API deployed to the DR environment
Answer: B
Explanation:
Correct Answer : Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment
*****************************************
There is one important consideration to be noted in the question which is - System API in DR environment provides only 20% of the rate limiting offered by the primary environment. So, comparitively, very less calls will be allowed into the DR environment API opposed to its primary environment. With this in mind, lets analyse what is the right and best fault-tolerant invocation strategy.
1. Invoking both the system APIs in parallel is definitely NOT a feasible approach because of the 20% limitation we have on DR environment. Calling in parallel every time would easily and quickly exhaust the rate limits on DR environment and may not give chance to genuine intermittent error scenarios to let in during the time of need.
2. Another option given is suggesting to add timeout and retry logic to process API while invoking primary environment's system API. This is good so far. However, when all retries failed, the option is suggesting to invoke the copy of process API on DR environment which is not right or recommended. Only system API is the one to be considered for fallback and not the whole process API. Process APIs usually have lot of heavy orchestration calling many other APIs which we do not want to repeat again by calling DR's process API. So this option is NOT right.
3. One more option given is suggesting to add the retry (no timeout) logic to process API to directly retry on DR environment's system API instead of retrying the primary environment system API first. This is not at all a proper fallback. A proper fallback should occur only after all retries are performed and exhausted on Primary environment first. But here, the option is suggesting to directly retry fallback API on first failure itself without trying main API. So, this option is NOT right too.
This leaves us one option which is right and best fit.
- Invoke the system API deployed to the primary environment
- Add Timeout and Retry logic on it in process API
- If it fails even after all retries, then invoke the system API deployed to the DR environment.
NEW QUESTION # 50
A large organization with an experienced central IT department is getting started using MuleSoft. There is a project to connect a siloed back-end system to a new Customer Relationship Management (CRM) system. The Center for Enablement is coaching them to use API-led connectivity.
What action would support the creation of an application network using API-led connectivity?
- A. Create a System API to unlock the data on the back-end system using a REST API
- B. Determine if the new CRM system supports the creation of custom: REST APIs, establishes 4 private network with CloudHub, and supports GAuth 2.0 authentication
- C. Invite the business analyst to create a business process model to specify the canonical data model between the two systems
- D. To expedite this project, central IT should extend the CRM system and back-end systems to connect to one another using built in integration interfaces
Answer: A
Explanation:
For an organization starting with API-led connectivity to integrate a siloed back-end system with a new CRM, the following approach aligns with best practices and MuleSoft's Center for Enablement (C4E) guidance:
API-led Connectivity: This model organizes APIs into distinct layers (System, Process, and Experience) to improve reusability, modularity, and manageability.
System APIs are used to expose and unlock data from core systems (such as back-end applications or databases).
Process APIs orchestrate data across multiple systems and transform it as needed.
Experience APIs format the data specifically for consumption by applications or devices, such as the CRM in this case.
Step to Support Application Network:
Create a System API for the back-end system. This API should expose the necessary data to support integration with the CRM.
By creating a System API with a RESTful interface, data can be accessed in a standardized way, making it easier to integrate with other systems and supporting future scalability.
Why Option D is Correct:
Creating a System API aligns with the principle of API-led connectivity, ensuring that data is exposed in a reusable manner. This API can then be orchestrated by Process APIs as needed to meet CRM requirements and can easily be extended to other applications.
of Incorrect Options:
Option A (creating a business process model) does not directly enable connectivity or expose back-end data through APIs.
Option B is unnecessary at this stage; assessing CRM capabilities like OAuth 2.0 support is not directly related to creating the application network via System APIs.
Option C contradicts API-led best practices by suggesting a point-to-point integration, which API-led connectivity seeks to avoid due to its lack of flexibility and scalability.
Reference
Refer to MuleSoft's API-led Connectivity resources for a detailed framework on building scalable integration layers using System, Process, and Experience APIs.
NEW QUESTION # 51
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