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copyright copyright-MuleSoft-Developer-I copyright copyright Topics:

TopicDetails
Topic 1
  • Debugging and Troubleshooting Mule Applications: Using breakpoints to inspect a Mule event during runtime, installing missing Maven dependencies, and reading and deciphering Mule log error messages are sub-topics of this topic.
Topic 2
  • Transforming Data with DataWeave: It involves writing DataWeave scripts and using DataWeave functions. This topic also includes defining and using DataWeave variables, functions, and modules, and applying correct syntax.
Topic 3
  • Structuring Mule Applications: Structuring Mule applications covers parameterizing an application and defining and reusing global configurations. It includes breaking an application into multiple flows using private flows, subflows, and the Flow Reference component.
Topic 4
  • Building API Implementation Interfaces: This topic involves manually creating a RESTful interface for a Mule application and generating a REST Connector from a RAML specification. It also includes describing the features and benefits of APIkit.
Topic 5
  • Deploying and Managing APIs and Integrations: It includes packaging Mule applications for deployment and deploying them to CloudHub. This topic also involves using CloudHub properties, creating and deploying API proxies, connecting an API implementation to API Manager, and applying policies to secure an API.
Topic 6
  • Routing Events: It focuses on using the Choice router for conditional logic and the Scatter-Gather router to multicast events. This topic also involves validating data by using the Validation module.
Topic 7
  • Handling Errors: Handling errors includes describing default error handling in Mule applications and defining custom global default error handlers. It involves comparing On Error Continue and On Error Propagate scopes, creating error handlers for a flow, using the Try scope, and mapping errors to custom application errors.
Topic 8
  • Accessing and Modifying Mule Events: It describes the Mule event data structure. Moreover, the topic focuses on usage of transformers and enriching Mule events.
Topic 9
  • Designing APIs: Designing APIs involves describing the lifecycle of the modern API and using RAML to define various aspects of an API. It includes identifying when to use query parameters vs URI parameters, and defining API parameters.

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copyright Certified MuleSoft Developer (Mule-Dev-201) Sample Questions (Q202-Q207):

NEW QUESTION # 202
Refer to theexhibits The Mule application does NOT define any global error handlers.
A web client sends a POST request to the Multi application with this input payload The File Write operation throws a FILECONNECTIVITY error What response message is returned to the web client?

Answer: B


NEW QUESTION # 203
Refer to the exhibits. The Set Payload transformer in the addltem child flow uses DataWeave to create an order object.
What is the correct DataWeave code for the Set Payload transformer in the createOrder flow to use the addltem child flow to add a router call with the price of 100 to the order?

Answer: C


NEW QUESTION # 204
Refer to the exhibits. In the choice router, the When expression for the domestic shipping route is set to "#[payload= "FR"]".
What is the output of logger after the execution of choice router is completed?

Answer: B

Explanation:
To compare, DataWeave syntax is #[payload == "FR"].
In this case only one = is used so it will give syntax error.
Hence the correct answer is A dataweave syntax error


NEW QUESTION # 205
Following Mulesoft's recommended API-led connectivity 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 reusable and 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-led approach 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 its intended 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 # 206
Which of the below activity doesn't support parallel execution?

Answer: B

Explanation:
The First Successful router iterates through a list of configured processing routes until one of the routes executes successfully. This is sequential execution. In all other options mentioned in the question ,we can achieve parallel execution.


NEW QUESTION # 207
......

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