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| Section | Weight | Objectives |
|---|---|---|
| Structuring Mule Applications | 10% | - Use properties and configuration values - Reference external configuration files - Organize applications using modular design patterns |
| Deploying and Managing Applications | 10% | - Deploy applications to CloudHub - Describe monitoring and management capabilities - Explain application deployment models - Configure deployment options |
| MuleSoft Fundamentals | 10% | - Describe the Mule application structure and flow types - Explain what Anypoint Platform is and its components - Describe what Mule applications do and how they are built |
| Designing Mule Applications | 14% | - Describe the role of API Manager - Explain the benefits of API-led connectivity - Define API specs using RAML - Implement an API using APIkit |
| DataWeave Transformation | 14% | - Write DataWeave transformations - Transform complex data structures - Define and use DataWeave variables and functions - Use DataWeave functions and operators |
| Building Mule Applications | 32% | - Create flows using Anypoint Studio - Use the logger component - Use connectors for common operations (Database, HTTP, Salesforce) - Use transformers and DataWeave - Configure properties and parameters - Implement error handling |
| Testing and Debugging | 10% | - Use mock attributes in tests - Write unit tests for Mule applications - Debug Mule applications using Studio |
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NEW QUESTION # 42
What is the output of Dataweave Mapoperator?
Answer: C
Explanation:
Returns an array that is the result of applying a transformation function (lambda) to each of the elements.
MuleSoft Doc Ref : https://docs.mulesoft.com/mule-runtime/4.3/dataweave-cookbook-map Themap operator is a function in Dataweave which iterates over the items in an array and outputs them into a new array. It basically accepts input as a list of items in an array and manipulates the items in the array in order to form a new array as an output.
I have created below chart for your easier understanding:
Table Description automatically generated
NEW QUESTION # 43
Refer to the exhibits.
What payload and variable are logged at the end of the main flow?
Answer: C
Explanation:
Correctanswer is [[5, 10, 15, 20], 5]
Key thing to note here is that any changes made to payload in for each loop are not available outside for each scope where as variable value updated in for each loop is visible out side for each loop too.
In this example , sequence can be described as follows
1) Payload is set to the value [5, 10, 15, 20]
2) Variable is set to the value of 1
3) For each loop is executed four times and in each loop payload value is updated to append "Req" and variable is count is increased by 1
4) Once control comes out of for each , payload changes made within for each are not visible. Hence payload at this point of time is equal to payload available before entering for each loop which was [5, 10, 15, 20].
Similarly variable value updated in for each loop is also available outside hence variable value is 5 as it was updated in loop.
5) Hence correct answer is [[5, 10, 15, 20], 5]
For Each Scope
The For Each scope splits a payload into elements and processes them one by one through the components that you place in the scope. It is similar to a for-each/for loop code block in most programming languages and can process any collection, including lists and arrays. The collection can be any supported content type, such as application/json, application/java, or application/xml.
General considerations about the For Each scope:
By default, For Each tries to split the payload. If the payload is a simple Java collection, the For Each scope can split it without any configuration. The payload inside the For Each scope is each of the split elements.
Attributes within the original message are ignored because they are related to the entire message.
For Each does not modify the current payload. The output payload is the same as the input.
For non-Java collections, such as XML or JSON, use a DataWeave expression to split data. Use the Collection field for this purpose.
NEW QUESTION # 44
What is the minimum Cloudhub worker size that can be specified while deploying muleapplication?
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 # 45
What is the main purpose of flow designer in Design Center?
Answer: D
Explanation:
Its primary function is to design and develop fully functional Mule applications in a hosted development environment.
NEW QUESTION # 46
Refer to the exhibits.
What payload and quantity are togged at the end of the main flow?
Answer: A
NEW QUESTION # 47
......
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