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Salesforce Certified MuleSoft Platform Architect Sample Questions (Q145-Q150):

NEW QUESTION # 145
A system API has a guaranteed SLA of 100 ms per request. The system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. An upstream process API invokes the system API and the main goal of this process API is to respond to client requests in the least possible time. In what order should the system APIs be invoked, and what changes should be made in order to speed up the response time for requests from the process API?

Answer: D

Explanation:
Correct Answe r: In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment, and ONLY use the first response.
*****************************************
>> The API requirement in the given scenario is to respond in least possible time.
>> The option that is suggesting to first try the API in primary environment and then fallback to API in DR environment would result in successful response but NOT in least possible time. So, this is NOT a right choice of implementation for given requirement.
>> Another option that is suggesting to ONLY invoke API in primary environment and to add timeout and retries may also result in successful response upon retries but NOT in least possible time. So, this is also NOT a right choice of implementation for given requirement.
>> One more option that is suggesting to invoke API in primary environment and API in DR environment in parallel using Scatter-Gather would result in wrong API response as it would return merged results and moreover, Scatter-Gather does things in parallel which is true but still completes its scope only on finishing all routes inside it. So again, NOT a right choice of implementation for given requirement The Correct choice is to invoke the API in primary environment and the API in DR environment parallelly, and using ONLY the first response received from one of them.


NEW QUESTION # 146
An IT Security Compliance Auditor is assessing which nonfunctional requirements (NFRs) are already being implemented to meet security measures.
* The Web API has Rate-Limiting SLA
* Basic Authentication - LDAP
* JSON Threat Protection
* TP Allowlist policies applied
Which two NFRs-are enforced?

Answer: A,B

Explanation:
Understanding Nonfunctional Requirements (NFRs):
The NFRs in this context are related to security measures implemented for the Web API, such as rate limiting, LDAP-based authentication, JSON threat protection, and IP allowlist policies.
Evaluating the Options:
Option A (Correct Answer): The IP allowlist policy restricts access to known subnets, ensuring that API invocations come from a defined range of IPs.
Option B (Correct Answer): Basic Authentication with LDAP enforces a username/password validation, satisfying an NFR for identity verification.
Option C: Masking sensitive data is not part of the listed NFRs, as none of the mentioned policies address data masking.
Option D: XML threat protection is not mentioned, so this option is incorrect.
Option E: While rate-limiting implies performance control, it does not directly enforce a specific performance expectation.
Conclusion:
Options A and B are correct as they directly address the implemented security measures related to IP range restrictions and username/password authentication.
Refer to MuleSoft's documentation on API security policies for details on LDAP, rate limiting, and allowlist policies.


NEW QUESTION # 147
When should idempotency be taken into account?

Answer: C

Explanation:
Understanding Idempotency:
Idempotency is a concept in APIs where an operation can be performed multiple times without changing the result beyond the initial application. This is particularly important for operations that may be repeated due to network retries or client errors.
When to Consider Idempotency:
Idempotency should be taken into account when there is a risk of duplicate processing due to multiple requests being sent (e.g., retries or errors). This ensures that repeated requests do not result in unintended side effects, such as creating multiple records or processing the same transaction more than once.
Evaluating the Options:
Option A: While locked entities may need special handling, this is not directly related to idempotency.
Option B: Storing results for future responses could be useful but does not relate to idempotent operations.
Option C: Concurrent requests for the same entity might require handling for conflicts, but this scenario is better suited for transaction management or concurrency control.
Option D (Correct Answer): Preventing duplicate processing from multiple requests is a key reason to implement idempotency, ensuring that repeat requests have no adverse effects.
Conclusion:
Option D is the correct answer as idempotency is specifically used to handle scenarios where duplicate requests might be sent, preventing unintended processing.
Refer to MuleSoft's documentation on best practices for idempotency in API design for more details.


NEW QUESTION # 148
A company uses a hybrid Anypoint Platform deployment model that combines the EU control plane with customer-hosted Mule runtimes. After successfully testing a Mule API implementation in the Staging environment, the Mule API implementation is set with environment-specific properties and must be promoted to the Production environment. What is a way that MuleSoft recommends to configure the Mule API implementation and automate its promotion to the Production environment?

Answer: D


NEW QUESTION # 149
What is the most performant out-of-the-box solution in Anypoint Platform to track transaction state in an asynchronously executing long-running process implemented as a Mule application deployed to multiple CloudHub workers?

Answer: C

Explanation:
Correct Answe r: Persistent Object Store
*****************************************
>> Redis distributed cache is performant but NOT out-of-the-box solution in Anypoint Platform
>> File-storage is neither performant nor out-of-the-box solution in Anypoint Platform
>> java.util.WeakHashMap needs a completely custom implementation of cache from scratch using Java code and is limited to the JVM where it is running. Which means the state in the cache is not worker aware when running on multiple workers. This type of cache is local to the worker. So, this is neither out-of-the-box nor worker-aware among multiple workers on cloudhub. https://www.baeldung.com/java-weakhashmap
>> Persistent Object Store is an out-of-the-box solution provided by Anypoint Platform which is performant as well as worker aware among multiple workers running on CloudHub. https://docs.mulesoft.com/object-store/ So, Persistent Object Store is the right answer.


NEW QUESTION # 150
......

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