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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Structuring Mule Applications | 10% | - Organize configurations and properties - Manage error handling and scopes - Use flows, subflows and flow references |
| Topic 2: Data Transformation with DataWeave | 10% | - Handle different data formats - Transform complex data structures - Write expressions and functions |
| Topic 3: Building API Implementations | 10% | - Implement routing and transformation logic - Implement APIs from specifications - Use connectors to integrate systems |
| Topic 4: Security and Governance | 7% | - Manage access and authentication - Apply security policies - Enforce governance standards |
| Topic 5: Designing APIs | 8% | - Define parameters, responses and data types - Use REST API methods and resources - Define API specifications with RAML |
| Topic 6: Error Handling and Transactions | 8% | - Handle retries and dead-letter queues - Implement transaction management - Configure error handlers |
| Topic 7: Testing and Debugging | 10% | - Debug applications using Anypoint Studio - Use mocking and test doubles - Write unit tests with MUnit |
| Topic 8: Creating Application Networks | 7% | - Describe Anypoint Platform components - Explain API-led connectivity principles - Identify application network concepts |
| Topic 9: Deploying and Managing Applications | 10% | - Monitor and manage applications - Explain deployment models - Deploy to CloudHub and on-premises |
| Topic 10: Accessing and Modifying Mule Events | 10% | - Access and modify payload, attributes and variables - Enrich events using connectors - Use DataWeave for transformation |
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NEW QUESTION # 45
WhichMule component provides a real-time, graphical representation of the APIs and mule applications that are running and discoverable?
Answer: C
Explanation:
Correct answer is Anypoint Visualizer
MuleSoft Doc Ref : https://docs.mulesoft.com/visualizer/
Anypoint Visualizer provides a real-time, graphical representation of the APIs, and Mule applications that are running and discoverable. It also displays third-party systems that are invoked by a Mule API, proxy, or application within your application network. The data displayed in the graph is dynamically updated and does not require prior configuration. Additionally, the data displayed is secure, as only users with the proper permissions can view the application network graph.
Diagram Description automatically generated
NEW QUESTION # 46
A Utlility.dwl is located in a Mule project at src/main/resources/modules. The Utility.dwl file defines a function named encryptString that encrypts a String What is thecorrect DataWeave to call the encryptString function in a Transform Message component?
Answer: C
Explanation:
Correct answer is
%dw 2.0
output application/json
import modules::Utility
---
Utility::encryptString( "John Smith" )
DataWeave 2.0 functions are packaged in modules. Before you begin, note that DataWeave 2.0 is for Mule
4apps. For Mule 3 apps, refer to DataWeave Operators in the Mule 3.9 documentation. For other Mule versions, you can use the version selector for the Mule Runtime table of contents.
Functions in the Core (dw::Core) module are imported automatically into your DataWeave scripts. To use other modules, you need to import the module or functions you want to use by adding the import directive to the head of your DataWeave script, for example:
import dw::core::Strings
import camelize, capitalize from dw::core::Strings
import * from dw::core::Strings
The way you import a module impacts the way you need to call its functions from a DataWeave script. If the directive does not list specific functions to import or use * from to import all functions from a function module, you need to specify the module when you call the function from your script. For example, this import directive does not identify any functions to import from the String module, so it calls the pluralize function like this: Strings::pluralize("box").
Transform
%dw 2.0
import dw::core::Strings
output application/json
---
{ 'plural': Strings::pluralize("box") }
NEW QUESTION # 47
Following Mulesoft's recommended API-ledconnectivity approach , an organization has created an application network. The organization now needs to create API's to transform , orchestrate and aggregate the data provided by the other API's in the application network. This API should be flexible enought ot handle the data from additional API's in future.
According to Mulesoft's recommended API-led connectivity approach , what is the best layer for this new API?
Answer: A
Explanation:
Correct answer is process layer as all the orchestration and transformation logic should be in process layer as per Mulesoft's recommended approach for API led connectivity.
API-led connectivity is a methodical way to connect data to applications through reusableand purposeful APIs. These APIs are developed to play a specific role - unlocking data from systems, composing data into processes, or delivering an experience.
What are the APIs that enable API-led connectivity?
API-led connectivity provides an approach for connecting and exposing assets. With this approach, rather than connecting things point-to-point, every asset becomes a managed API - a modern API, which makes it discoverable through self-service without losing control.
The APIs used in an API-ledapproach to connectivity fall into three categories:
System APIs - these usually access the core systems of record and provide a means of insulating the user from the complexity or any changes to the underlying systems. Once built, many users, can access data without any need to learn the underlying systems and can reuse these APIs in multiple projects.
Process APIs - These APIs interact with and shape data within a single system or across systems (breaking down data silos) and are created here without a dependence on the source systems from which that data originates, as well as the target channels through which that data is delivered.
Experience APIs - Experience APIs are the means by which data can be reconfigured so that it is most easily consumed by itsintended audience, all from a common data source, rather than setting up separate point-to- point integrations for each channel. An Experience API is usually created with API-first design principles where the API is designed for the specific user experience in mind.
NEW QUESTION # 48
Which out of below is not an asset?
Answer: A
Explanation:
Exchange is the odd man out here. Rest all are type of asset
Graphical user interface, application Description automatically generated
NEW QUESTION # 49
What is the output of Dataweave Mapoperator?
Answer: D
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 # 50
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