Free PDF Salesforce - Trustable Mule-Dev-301 - Salesforce Certified MuleSoft Developer II Free Test Questions

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Salesforce Mule-Dev-301 Exam Syllabus Topics:

SectionWeightObjectives
Design and Implement API-led Connectivity13%- Implement HTTP callbacks/webhooks
- Implement server-side caching
- Implement API autodiscovery
Implement Monitorable Mule Applications15%- Implement message correlation
- Expose health check endpoints
- Monitor applications and runtimes
- Implement logging and log management
Implement Performant and Reliable Mule Applications27%- Optimize performance and throughput
- Validate messages and payloads
- Handle HTTP API invocations and errors
- Use ObjectStore for persistence
- Implement reliable messaging patterns
Implement Maintainable and Modular Mule Applications and Maven Builds25%- Create reusable libraries
- Implement automated deployment
- Modularize applications and builds
- Execute tests with Maven
- Build custom policies and processors
Secure Data at Rest and in Transit20%- Manage keys and certificates
- Manage secure environment properties
- Implement security policies
- Expose and invoke APIs over HTTPS

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Exam Sample Mule-Dev-301 Questions, Standard Mule-Dev-301 Answers

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Salesforce Certified MuleSoft Developer II Sample Questions (Q26-Q31):

NEW QUESTION # 26
Refer to the exhibit.

Based on the code snippet, schema,json file, and payload below, what is the outcome of the given code snippet when a request is sent with the payload?

Answer: C

Explanation:
Based on the code snippet, schema.json file, and payload below, the outcome of the given code snippet when a request is sent with the payload is that the Mule flow will throw the exception 'JSON:SCHEMA_NOT_HONOURED'. This is because the payload does not conform to the schema.json file, which specifies that age must be a number greater than or equal to zero. The payload has age as a string with a negative value, which violates the schema. Therefore, the validate-schema operation throws an error with type 'JSON:SCHEMA_NOT_HONOURED'. Reference: https://docs.mulesoft.com/json-module/1.1/json-validate-schema


NEW QUESTION # 27
A Mule application deployed to a standardalone Mule runtime uses VM queues to publish messages to be consumed asynchronously by another flow.
In the case of a system failure, what will happen to in-flight messages in the VM queues that have been consumed?

Answer: D

Explanation:
In case of a system failure, in-flight messages in persistent VM queues that have been consumed will be processed after the system comes online. This is because persistent VM queues store messages on disk and guarantee delivery even if there is a system crash or restart. Therefore, any in-flight messages that have been consumed but not processed will be recovered from disk and processed when the system is back online. Reference: https://docs.mulesoft.com/mule-runtime/4.3/vm-connector#persistent-queues


NEW QUESTION # 28
Refer to the exhibit.
An API has been built to enable scheduling emails for a healthcare provider. The front-end system does very little data entry validation, and problems have started to appear in the emails that go out to patients. A
"validate-customer" flow is added to validate the data.
What is the expected behavior of the "validate-customer" flow?
Exhibit:

Answer: D

Explanation:
The three validation operations are nested inside a validation:all scope. The defining behavior of this scope is that it executes every nested validation even if one or more earlier validations fail. Consequently, an invalid email does not immediately terminate validation processing. Mule continues to evaluate the appointment-date regular expression and the customer-name null check.
MuleSoft explicitly documents that all validations inside the All scope are executed even if all of them fail. If one or more nested validations fail, the All validator produces a consolidated VALIDATION:MULTIPLE error describing the failures rather than simply throwing the first or final validation error.
The flow does contain error mappings for individual validators-for example mapping VALIDATION:
INVALID_EMAIL to SCHEDULE:INVALID_EMAIL_ADDRESS. However, those mappings do not change the central behavioral point being tested: the All scope evaluates the entire set rather than short- circuiting after the first failed validator.
Thus, if the email address is invalid, the remaining appointment-date and customer-name validations are still evaluated. This makes C the only option accurately describing the scope's execution behavior.
Reference topics: Validation Module; validation:all; validation aggregation; VALIDATION:MULTIPLE; error mappings.
Official documentation: https://docs.mulesoft.com/validation-connector/latest/validation-examples


NEW QUESTION # 29
Which pattern can a web API use to notify its client of state changes as soon as they occur?

Answer: C

Explanation:
An HTTP webhook provides event-driven notification from an API or service to a client-controlled HTTP endpoint. Instead of requiring the client to repeatedly poll the API for changes, the client registers or supplies a callback URL. When the relevant state transition occurs, the service immediately issues an HTTP request- commonly POST-to that endpoint.
This architecture closely matches the requirement to notify the client as soon as the state change occurs.
MuleSoft-supported connectors expose the same webhook model. For example, MuleSoft's connector documentation describes webhook endpoints as URLs that receive notifications about configured events, demonstrating the callback-based semantics of the pattern.
An ETL load is primarily designed for batch-oriented movement and transformation of data and would introduce unnecessary latency. A scheduled event publisher is still time based, meaning notification occurs according to a schedule rather than directly in response to the state transition. A shared database trigger tightly couples applications through the persistence tier and does not constitute an API notification mechanism.
A webhook therefore creates a clean event-driven API contract: the producing service detects the event and actively notifies the registered consumer endpoint.
Reference topics: HTTP webhooks; event-driven API integration; callback endpoints; asynchronous notifications; API consumer decoupling.
Official documentation: https://docs.mulesoft.com/stripe-connector/latest/stripe-connector-reference


NEW QUESTION # 30
A Mule application for processing orders must log the order ID for every log message output.
What is a best practice to enrich every log message with the order ID?

Answer: B

Explanation:
To enrich every log message with the order ID, the developer should use the Tracing module to set logging variables with a Mapped Diagnostic Context (MDC). The Tracing module allows adding custom key-value pairs to log messages using MDC variables. The developer can use Set Logging Variables operation to set the order ID as an MDC variable and then use it in any logger processor within the same thread or event. Reference: https://docs.mulesoft.com/tracing-module/1.0/tracing-module-reference#set-logging-variables


NEW QUESTION # 31
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