Mule-Dev-301 Zertifizierungsantworten, Mule-Dev-301 Musterprüfungsfragen

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Salesforce Mule-Dev-301 Exam Syllabus Topics:

Section	Weight	Objectives
Secure Data at Rest and in Transit	20%	- Implement security best practices 1. Expose APIs over HTTPS 2. Implement secure property management 3. Implement TLS mutual authentication 4. Create and distribute certificates and keys 5. Secure sensitive data in Mule applications
Expose Production-Ready Anypoint Platform Managed APIs	13%	- Manage APIs with Anypoint Platform 1. Implement API versioning 2. Configure API policies 3. Implement HTTP callbacks 4. Request and manage API access 5. Implement server-side API caching
Implement Maintainable and Modular Mule Applications and Their Maven Builds	25%	- Implement modular Mule application structures 1. Optimize Maven build configurations 2. Execute MUnit tests with Maven 3. Create custom API rules 4. Implement Maven-based automated deployments 5. Implement unit testing with MUnit framework
Implement Monitorable Mule Applications	15%	- Implement monitoring and logging 1. Implement monitoring dashboards and alerts 2. Expose health check endpoints 3. Change log levels dynamically 4. Configure and evaluate application logs
Implement Performant and Reliable Mule Applications	27%	- Optimize reliability and performance 1. Build fault-tolerant message processing 2. Implement performant API invocations 3. Implement ObjectStore persistence 4. Validate assertions using validation modules 5. Implement asynchronous processing

>> Mule-Dev-301 Zertifizierungsantworten <<

Mule-Dev-301 PrüfungGuide, Salesforce Mule-Dev-301 Zertifikat - Salesforce Certified MuleSoft Developer II

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Salesforce Certified MuleSoft Developer II Mule-Dev-301 Prüfungsfragen mit Lösungen (Q25-Q30):

25. Frage
A company deploys 10 public APIs to CloudHub. Each API has its own individual health endpoint defined.
The platform operation team wants to configure API Functional Monitoring to monitor the health of the APIs periodically while minimizing operational overhead and cost.
How should API Functional Monitoring be configured?

A. From one public location with all 10 APIs in a single schedule
B. From one private location with all 10 APIs in a single schedule
C. From 10 public locations with each API in its own schedule
D. From one public location with each API in its own schedule

Antwort: A

Begründung:
API Functional Monitoring permits a monitor to contain tests against one or more endpoints, including endpoints belonging to multiple public APIs. A schedule determines where and how frequently the monitor executes. Consequently, there is no technical requirement to create ten independent schedules simply because ten APIs have individual health endpoints.
Because all ten APIs are public and accessible from the internet, a public location is sufficient. A private location is primarily useful when the monitored endpoints are accessible only through a private network or when specific private-network connectivity requirements exist. Creating a private location would introduce unnecessary deployment and operational overhead in this scenario.
The most efficient design is therefore to place the ten health checks in a single monitor/test suite and associate that monitor with one schedule running from one public location. MuleSoft documentation explicitly shows that a single monitor can test endpoints belonging to multiple public APIs, while a single schedule is associated with a location and execution interval. This reduces schedule consumption and management complexity.
Reference topics: API Functional Monitoring; Public Locations; Monitor Tests and Schedules; Monitoring Public APIs.
Official documentation: https://docs.mulesoft.com/api-functional-monitoring/afm-monitoring-public-apis

26. Frage
A Mule application uses API autodiscovery to access and enforce policies for a RESTful implementation.

A. The name of the flow that has APlkit Console to receive all incoming RESTful operation requests.
B. The name of the flow that has HTTP listener to receive all incoming RESTful operation requests
C. Northing because flowRef is an optional attribute which can be passed runtime
D. Any of the APIkit generate implement flows

Antwort: B

Begründung:
To use API autodiscovery to access and enforce policies for a RESTful implementation, flowRef must be set to the name of the flow that has HTTP listener to receive all incoming RESTful operation requests. This way, API autodiscovery can identify the API implementation and associate it with the corresponding API specification and policies in API Manager. The flow that has HTTP listener is usually the main flow that contains the APIKit Router. Reference: https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept#flowref

27. Frage
A Mule API receives a JSON payload and updates the target system with the payload. The developer uses JSON schemas to ensure the data is valid.
How can the data be validated before posting to the target system?

A. Use a DataWeave 2.0 transform operation, and at the top of the DataWeave script, add: %dw 2.0 / import json-module
B. Add the JSON module dependency and add the validate schema operation in the flow, configured to reference the schema
C. Apply the JSON Schema policy in API Manager and reference the correct schema in the policy configuration
D. Using the DataWeave If Else condition, test the values of the payload against the examples included in the schema

Antwort: B

Begründung:
MuleSoft provides the JSON Module specifically for operations such as JSON validation. The application should include the JSON Module as a Mule dependency and place its Validate schema operation before the connector or operation that posts the data to the target system.
The Validate schema operation receives the JSON document and evaluates it against the configured JSON Schema. When validation succeeds, processing continues to the next processor. If the payload does not conform, Mule raises JSON:SCHEMA_NOT_HONOURED, allowing the flow's error-handling strategy to reject or transform the invalid request before the target system is modified.
MuleSoft also documents that modules/connectors added manually to an application are declared in pom.xml as dependencies with the mule-plugin classifier; the JSON Module follows this standard pattern.
DataWeave conditional validation would unnecessarily reimplement schema semantics and would not automatically interpret a JSON Schema. API Manager does not provide the application-level JSON Module operation described by this requirement, and import json-module is not a valid mechanism for invoking the Mule JSON Module from DataWeave.
Reference topics: JSON Module; Validate Schema; JSON Schema; JSON:SCHEMA_NOT_HONOURED; Maven module dependency.
Official documentation: https://docs.mulesoft.com/json-module/latest/json-schema-validation Official documentation: https://docs.mulesoft.com/json-module/latest/json-xml-maven

28. Frage
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:

A. If the email address is invalid, processing continues to see if the appointment date and customer name are also invalid
B. If all of the values are invalid, the last validation error is raised: SCHEDULE:INVALID_CUSTOMER_NAME
C. If only the email address is invalid, a VALIDATION:INVALID_EMAIL error is raised
D. If the appointment date and customer name are invalid, a SCHEDULE:
INVALID_APPOINTMENT_DATE error is raised

Antwort: A

Begründung:
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

29. Frage
A Mule application defines as SSL/TLS keystore properly 'tis,keystore.keyPassword'' as secure.
How can this property be referenced to access its value within the application?

A. p{secure::tiskeystore,keyPassowrd}
B. ${secure::tiskeystore,keyPassowrd}
C. ${secure::tiskeystore,keyPassowrd}
D. #{secure::tiskeystore,keyPassowrd}

Antwort: B

Begründung:
secure::tiskeystore,keyPassowrd∗∗ShortExplanationofCorrectAnswerOnly:Toreferenceasecurepropertyvaluewithintheapplication,thedeveloperneedstousethesyntax{secure::}. In this case, the property name is tiskeystore,keyPassword, so the correct syntax is ${secure::tiskeystore,keyPassowrd}. Reference: https://docs.mulesoft.com/mule-runtime/4.3/secure-configuration-properties#referencing-secure-properties

30. Frage
......

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