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Salesforce MuleSoft-Integration-Architect-I Exam Syllabus Topics:

Topic	Details
Topic 1	Designing and Developing Mule Applications: It includes selecting application properties, using fundamental features, designing with core routers, understanding the Salesforce Connector, and leveraging core connectors.
Topic 2	Designing Architecture Using Integration Paradigms: This topic focuses on creating high-level integration architectures using various paradigms. It includes API-led connectivity, web APIs and HTTP, event-driven APIs, and message brokers, and designing Mule application using messaging patterns and technologies.
Topic 3	Designing Integration Solutions to Meet Performance Requirements: This topic covers meeting performance and capacity goals, using streaming features, and processing large message sequences.
Topic 4	Initiating Integration Solutions on Anypoint Platform: Summarizing MuleSoft Catalyst and Catalyst Knowledge Hub, differentiating between functional and non-functional requirements, selecting features for designing and managing APIs, and choosing deployment options are its sub-topics.
Topic 5	Designing Integration Solutions to Meet Persistence Requirements: It addresses the usage of VM queues and connectors, object stores and services, and stateful components configured with object stores.
Topic 6	Applying DevOps Practices and Operating Integration Solutions: Its sub-topics are related to designing CI CD pipelines with MuleSoft plugins, automating interactions with Anypoint Platform, designing logging configurations, and identifying Anypoint Monitoring features.
Topic 7	Designing Integration Solutions to Meet Security Requirements: This topic emphasizes securing access to the Anypoint Platform and APIs, using Anypoint Security, counteracting security vulnerabilities, and understanding audit logging capabilities.
Topic 8	Designing Integration Solutions to Meet Reliability Requirements: It includes selecting alternatives to traditional transactions, recognizing the purpose of various scopes and strategies, differentiating disaster recovery and high availability, and using local and XA transactions.
Topic 9	Designing Automated Tests for Mule Applications: This topic covers unit test suites, and scenarios for integration and performance testing.

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Salesforce Certified MuleSoft Integration Architect I Sample Questions (Q128-Q133):

NEW QUESTION # 128
In Anypoint Platform, a company wants to configure multiple identity providers (IdPs) for multiple lines of business (LOBs). Multiple business groups, teams, and environments have been defined for these LOBs.
What Anypoint Platform feature can use multiple IdPs across the company's business groups, teams, and environments?

A. Virtual private clouds
B. MuleSoft-hosted (CloudHub) dedicated load balancers
C. Permissions
D. Client (application) management

Answer: B

Explanation:
To use a dedicated load balancer in your environment, you must first create an Anypoint VPC. Because you can associate multiple environments with the same Anypoint VPC, you can use the same dedicated load balancer for your different environments.

NEW QUESTION # 129
Which Salesforce API is invoked to deploy, retrieve, create, update, or delete customization information, such as custom object definitions using Mule Salesforce Connectors in a Mule application?

A. sObject Platform Action API
B. User Interface API
C. Metadata API
D. Process Rules API

Answer: C

Explanation:
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

NEW QUESTION # 130
An integration Mute application is being designed to process orders by submitting them to a backend system for offline processing. Each order will be received by the Mute application through an HTTPS POST and must be acknowledged immediately. Once acknowledged, the order will be submitted to a backend system.
Orders that cannot be successfully submitted due to rejections from the backend system will need to be processed manually (outside the backend system).
The Mule application will be deployed to a customer-hosted runtime and is able to use an existing ActiveMQ broker if needed.
The backend system has a track record of unreliability both due to minor network connectivity issues and longer outages.
What idiomatic (used for their intended purposes) combination of Mule application components and ActiveMQ queues are required to ensure automatic submission of orders to the backend system, while minimizing manual order processing?

A. Until Successful component MuleSoft Object Store ActiveMQ is NOT needed or used
B. An On Error scope MuleSoft Object Store ActiveMQ Dead Letter Queue for manual processing
C. Until Successful component ActiveMQ long retry Queue ActiveMQ Dead Letter Queue for manual processing
D. An On Error scope Non-persistent VM ActiveMQ Dead Letter Queue for manual processing

Answer: C

Explanation:
Correct answer is using below set of activities Until Successful component ActiveMQ long retry Queue ActiveMQ Dead Letter Queue for manual processing We will see why this is correct answer but before that lets understand few of the concepts which we need to know. Until Successful Scope The Until Successful scope processes messages through its processors until the entire operation succeeds. Until Successful repeatedly retries to process a message that is attempting to complete an activity such as: - Dispatching to outbound endpoints, for example, when calling a remote web service that may have availability issues. - Executing a component method, for example, when executing on a Spring bean that may depend on unreliable resources. - A sub-flow execution, to keep re-executing several actions until they all succeed, - Any other message processor execution, to allow more complex scenarios. How this will help requirement : Using Until Successful Scope we can retry sending the order to backend systems in case of error to avoid manual processing later. Retry values can be configured in Until Successful Scope Apache ActiveMQ It is an open source message broker written in Java together with a full Java Message Service client ActiveMQ has the ability to deliver messages with delays thanks to its scheduler. This functionality is the base for the broker redelivery plug-in. The redelivery plug-in can intercept dead letter processing and reschedule the failing messages for redelivery. Rather than being delivered to a DLQ, a failing message is scheduled to go to the tail of the original queue and redelivered to a message consumer. How this will help requirement : If backend application is down for a longer duration where Until Successful Scope wont work, then we can make use of ActiveMQ long retry Queue. The redelivery plug-in can intercept dead letter processing and reschedule the failing messages for redelivery. Mule Reference: https://docs.mulesoft.com/mule-runtime/4.3/migration-core- until-successful

NEW QUESTION # 131
A mule application must periodically process a large dataset which varies from 6 GB lo 8 GB from a back- end database and write transform data lo an FTPS server using a properly configured bad job scope.
The performance requirements of an application are approved to run in the cloud hub 0.2 vCore with 8 GB storage capacity and currency requirements are met.
How can the high rate of records be effectively managed in this application?

A. Use streaming with an in-memory reputable store strategy for reading records from the database and batch aggregator with streaming to write to FTPS
B. Use streaming with a file store repeatable strategy for reading records from the database and batch aggregator with an optimal size
C. Use streaming with a file store repeatable strategy reading records from the database and batch aggregator without any required configuration
D. Use streaming with a file storage repeatable strategy for reading records from the database and batch aggregator with streaming to write to FTPS

Answer: D

Explanation:
For handling large datasets in a Mule application, streaming is an effective strategy. Streaming allows the application to process large amounts of data in chunks, reducing memory usage and improving performance.
Using a file storage repeatable strategy for reading records from the database ensures that the data is read in manageable chunks and stored temporarily in files, which can be re-read if necessary, enhancing reliability.
The batch aggregator with streaming to write to an FTPS server ensures that data is written in chunks, aligning with the processing capabilities of the application running in CloudHub with 0.2 vCore and 8 GB storage. This configuration optimizes performance by balancing the load and managing the dataset size effectively, ensuring that the high rate of records can be processed and written to the FTPS server without overwhelming the system.
References:
* MuleSoft Documentation on Streaming
* MuleSoft Documentation on Batch Processing

NEW QUESTION # 132
A Mule application is built to support a local transaction for a series of operations on a single database. The mule application has a Scatter-Gather scope that participates in the local transaction.
What is the behavior of the Scatter-Gather when running within this local transaction?

A. Execution of all routes within Scatter-Gather occurs in parallel Any error that occurs inside Scatter- Gather will be handled by error handler and will not result in roll back
B. Execution of all routes within Scatter-Gather occurs in parallel Any error that occurs inside Scatter- Gather will result in a roll back of all the database operations
C. Execution of all routes within Scatter-Gather occurs sequentially Any error that occurs inside Scatter- Gather will result in a roll back of all the database operations
D. Execution of all routes within Scatter-Gather occurs sequentially Any error that occurs inside Scatter- Gather will be handled by error handler and will not result in roll back

Answer: B

Explanation:
* Parallel Execution:
* In a Scatter-Gather scope, all routes are executed in parallel. This allows multiple operations to be performed simultaneously, which can improve performance and efficiency when dealing with independent tasks.
* Transaction Management:
* When Scatter-Gather operates within a local transaction, all database operations performed in parallel routes are part of the same transaction context.
* Error Handling and Rollback:
* If any error occurs within any of the parallel routes inside the Scatter-Gather scope, it triggers a rollback of all the database operations performed within the transaction. This ensures data consistency and integrity.
References:
* MuleSoft Documentation on Scatter-Gather
* Transaction management in MuleSoft

NEW QUESTION # 133
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