MuleSoft-Integration-Architect-I Exam Dumps - Salesforce MuleSoft Questions and Answers

For integrating flight data into an online aggregation website with secure, high-performance, and asynchronous message exchange, the most suitable interface technologies supported by MuleSoft are:

AsyncAPI over HTTPS: AsyncAPI is a specification for asynchronous APIs, which is ideal for high-performance, event-driven communication. Using HTTPS ensures secure communication.

AMQP with RabbitMQ: AMQP (Advanced Message Queuing Protocol) is a protocol for message-oriented middleware. RabbitMQ is a popular message broker that supports AMQP, allowing for reliable and asynchronous message exchange.

JSON/REST over HTTPS: JSON is a lightweight data-interchange format, and REST (Representational State Transfer) is an architectural style for designing networked applications. Using HTTPS ensures secure communication.

Implementation Steps:

Define the AsyncAPI specification for the flight data events and set up the infrastructure to handle these events over HTTPS.

Set up RabbitMQ and configure AMQP for message queuing. Ensure that your MuleSoft application is capable of consuming and producing messages using the RabbitMQ connector.

Implement RESTful APIs using JSON over HTTPS to expose the flight data securely.

These technologies collectively ensure secure, asynchronous, and high-performance integration.

Try-Catch Scope for Data Fetching:

Implement a try-catch scope to handle any errors that may occur while fetching account balances from the backend application. This ensures that the main process flow can handle exceptions gracefully without failing entirely.

Async Scope for Inserting Records into Audit Database:

Use the Async scope within the try-catch block to insert records into the audit database. The Async scope allows operations to be performed asynchronously, ensuring that the insertion process does not block the main thread of execution.

By doing this, the primary flow of fetching account balances remains unaffected and can achieve higher throughput as the auditing process runs concurrently.

Ensuring Better Throughput:

The async processing ensures that the time-consuming database insertion for auditing purposes does not impede the performance of the main flow, which is crucial for real-time or near-real-time systems.

When a RAML definition is updated and a new version is published to Anypoint Exchange, the client applications that consume the API need to be updated to utilize the new operations. Here’s how the Mule application team can achieve this:

Access Anypoint Exchange:

Go to Anypoint Exchange and find the updated RAML definition of the API.

Update the REST Connector:

In the Mule application, locate the existing REST connector that was generated from the previous version of the API.

Update this connector to the latest version by reimporting the RAML definition.

This can be done via the Anypoint Studio by navigating to the Mule Palette, finding the REST connector, and updating it with the new RAML.

Regenerate Client Code (If Necessary):

Sometimes, updating the connector may require regenerating the client code to include new operations.

Ensure that all new methods and endpoints are available in your Mule application after the update.

Test New Operations:

Incorporate and test the new operations in the Mule application to ensure they function correctly with the updated API implementation.

References

MuleSoft Documentation: API Development

Anypoint Studio Documentation: Using Connectors

Explanation

As the stakeholders are semitechnical users , preferred option is Create Anypoint Exchange entries with pages elaborating the integration design, including API notebooks (where applicable) to help the stakeholders understand and interact with the Mule applications and APIs at various levels of technical depth

* Each Batch Job uses SEVERAL THREADS for the Batch Steps

* Each Batch Step instance receives ONE record at a time as the payload. It's not received in a block, as it does not wait for multiple records to be completed before moving to next batch step. (So Option D is out of choice)

* RECORDS are processed IN PARALLEL within and between the two Batch Steps.

* RECORDS are not processed in order. Let's say if second record completes batch_step_1 before record 1, then it moves to batch_step_2 before record 1. (So option C and D are out of choice)

* A batch job is the scope element in an application in which Mule processes a message payload as a batch of records. The term batch job is inclusive of all three phases of processing: Load and Dispatch, Process, and On Complete.

* A batch job instance is an occurrence in a Mule application whenever a Mule flow executes a batch job. Mule creates the batch job instance in the Load and Dispatch phase. Every batch job instance is identified internally using a unique String known as batch job instance id.

The Salesforce API used to deploy, retrieve, create, update, or delete customization information, such as custom object definitions, using Mule Salesforce Connectors in a Mule application, is the Metadata API. The Metadata API enables programmatic access to the metadata of Salesforce organizations, allowing developers to manage customizations and configurations programmatically.

Using the Metadata API, Mule applications can automate the deployment and management of Salesforce customizations, facilitating continuous integration and deployment processes within Salesforce environments.

References

MuleSoft Documentation on Salesforce Connectors

Salesforce Metadata API Developer Guide

Explanation

Correct answer is "The web store backend generates a new correlation ID value at the start of checkout and sets it on the X¬CORRELATION-ID HTTP request header in each API invocation belonging to that checkout No special code or configuration is included in the Experience API and Process API implementations to generate and manage the correlation ID" Explanation : By design, Correlation Ids cannot be changed within a flow in Mule 4 applications and can be set only at source. This ID is part of the Event Context and is generated as soon as the message is received by the application. When a HTTP Request is received, the request is inspected for "X-Correlation-Id" header. If "X-Correlation-Id" header is present, HTTP connector uses this as the Correlation Id. If "X-Correlation-Id" header is NOT present, a Correlation Id is randomly generated. For Incoming HTTP Requests: In order to set a custom Correlation Id, the client invoking the HTTP request must set "X-Correlation-Id" header. This will ensure that the Mule Flow uses this Correlation Id. For Outgoing HTTP Requests: You can also propagate the existing Correlation Id to downstream APIs. By default, all outgoing HTTP Requests send "X-Correlation-Id" header. However, you can choose to set a different value to "X-Correlation-Id" header or set "Send Correlation Id" to NEVER.

Mulesoft Reference: https://help.mulesoft.com/s/article/How-to-Set-Custom-Correlation-Id-for-Flows-with-HTTP-Endpoint-in-Mule-4

Explanation

CloudHub object store should be in same region where the Mule application is deployed. This will give optimal performance.

Before learning about Cache scope and object store in Mule 4 we understand what is in general Caching is and other related things.

WHAT DOES “CACHING” MEAN?

Caching is the process of storing frequently used data in memory, file system or database which saves processing time and load if it would have to be accessed from original source location every time.

In computing, a cache is a high-speed data storage layer which stores a subset of data, so that future requests for that data are served up faster than is possible by accessing the data’s primary storage location. Caching allows you to efficiently reuse previously retrieved or computed data.

How does Caching work?

The data in a cache is generally stored in fast access hardware such as RAM (Random-access memory) and may also be used in correlation with a software component. A cache’s primary purpose is to increase data retrieval performance by reducing the need to access the underlying slower storage layer.

Caching in MULE 4

In Mule 4 caching can be achieved in mule using cache scope and/or object-store. Cache scope internally uses Object Store to store the data.

What is Object Store

Object Store lets applications store data and states across batch processes, Mule components, and applications, from within an application. If used on cloud hub, the object store is shared between applications deployed on Cluster.

Cache Scope is used in below-mentioned cases:

● Need to store the whole response from the outbound processor

● Data returned from the outbound processor does not change very frequently

● As Cache scope internally handle the cache hit and cache miss scenarios it is more readable

Object Store is used in below-mentioned cases:

● Need to store custom/intermediary data

● To store watermarks

● Sharing the data/stage across applications, schedulers, batch.

If CloudHub object store is in same region where the Mule application is deployed it will aid in fast access of data and give optimal performance.

Explanation

Correct answer is Untill Successful scope can be implemented while calling backend API's The Until Successful scope repeatedly triggers the scope's components (including flow references) until they all succeed or until a maximum number of retries is exceeded The scope provides option to control the max number of retries and the interval between retries The scope can execute any sequence of processors that may fail for whatever reason and may succeed upon retry

Explanation

When an operation in a Mule application fails to connect to an external server, the default behavior is for the operation to fail immediately and return a connectivity error. You can modify this default behavior by configuring a reconnection strategy for the operation. You can configure a reconnection strategy for an operation either by modifying the operation properties or by modifying the configuration of the global element for the operation. The following are the available reconnection strategies and their behaviors: None Is the default behavior, which immediately returns a connectivity error if the attempt to connect is unsuccessful Standard (reconnect) Sets the number of reconnection attempts and the interval at which to execute them before returning a connectivity error Forever (reconnect-forever) Attempts to reconnect continually at a given interval