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MuleSoft MCD-Level-1 Exam Syllabus Topics:

SectionObjectives
Topic 1: Error Handling and Debugging- Error types and strategies
- Debugging Mule applications
Topic 2: Anypoint Platform Fundamentals- Anypoint Platform components
- API-led connectivity concepts
Topic 3: Deployment and Operations- CloudHub deployment
- Monitoring and logging
Topic 4: Designing APIs- RAML basics
- API design best practices
Topic 5: Implementing Mule Applications- Connectors and components
- Mule flows and event processing
Topic 6: DataWeave- Mapping and functions
- Data transformation basics

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MuleSoft Certified Developer - Level 1 (Mule 4) Sample Questions (Q223-Q228):

NEW QUESTION # 223
How are query parameters dynamically passed to an outbound REST request using an HTTP Request operation?

Answer: B

Explanation:
In General > Request > Query Parameters, click the plus icon (+) to add a parameter to a request. Type a name and value for the parameter or use a DataWeave expression to define the name and value.


NEW QUESTION # 224
Refer to the exhibits.

In the requestFlow an HTTP Request operation is configured to send an HTTP request with an XML payload.
The request is sent to the HTTP Listener in the transform Flow.
That flow transforms the incoming payload into JSON format and returns the response to the HTTP request.
The response of the request is stored in a target variable named the Result.
What is the payload at the Logger component after the HTTP Request?

Answer: D


NEW QUESTION # 225
Refer to the exhibit.

How many private flows does APIKIT generate from the RAML specification?

Answer: C


NEW QUESTION # 226
A flow needs to combine and return data from two different data sources. It contains a Database SELECT operation followed by an HTTP Request operation.
What is the method to capture both payloads so the payload from the second request does not overwrite that from the first?

Answer: D


NEW QUESTION # 227
What is the minimum Cloudhub worker size that can be specified while deploying mule application?

Answer: D

Explanation:
Correct answer is 0.1 vCores
MuleSoft Doc Ref : https://docs.mulesoft.com/runtime-manager/cloudhub-architecture#cloudhub-workers CloudHub Workers Workers are dedicated instances of Mule runtime engine that run your integration applications on CloudHub.
The memory capacity and processing power of a worker depends on how you configure it at the application level.
Worker sizes have different compute, memory, and storage capacities. You can scale workers vertically by selecting one of the available worker sizes:
Table Description automatically generated


NEW QUESTION # 228
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