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

Topic
Details

Topic 1

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 2

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 3

Designing Automated Tests for Mule Applications: This topic covers unit test suites, and scenarios for integration and performance testing.

Topic 4

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 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

Designing for the Runtime Plane Technology Architecture: It includes analyzing Mule runtime clusters, designing solutions for CloudHub, choosing Mule runtime domains, leveraging Mule 4 class loader isolation, and understanding the reactive event processing model.

Salesforce Certified MuleSoft Integration Architect I Sample Questions (Q256-Q261):

NEW QUESTION # 256
An Order microservice and a Fulfillment microservice are being designed to communicate with their dients through message-based integration (and NOT through API invocations).
The Order microservice publishes an Order message (a kind of command message) containing the details of an order to be fulfilled. The intention is that Order messages are only consumed by one Mute application, the Fulfillment microservice.
The Fulfilment microservice consumes Order messages, fulfills the order described therein, and then publishes an OrderFulfilted message (a kind of event message). Each OrderFulfilted message can be consumed by any interested Mule application, and the Order microservice is one such Mute application.
What is the most appropriate choice of message broker(s) and message destination(s) in this scenario?

A. Order messages are sent directly to the Fulfillment microservices. OrderFulfilled messages are sent directly to the Order microservice The Order microservice interacts with one AMQP-compatible message broker and the Fulfillment microservice interacts with a different AMQP-compatible message broker, so that both message brokers can be chosen and scaled to best support the load of each microservice
B. Order messages are sent to an Anypoint MQ exchange OrderFulfilled messages are sent to an Anypoint MQ queue Both microservices interact with Anypoint MQ as the message broker, which must therefore scale to support the load of both microservices
C. Order messages are sent to a JMS queue. OrderFulfilled messages are sent to a JMS topic Both microservices interact with the same JMS provider (message broker) instance, which must therefore scale to support the load of both microservices
D. Order messages are sent to a JMS queue. OrderFulfilled messages are sent to a JMS topic The Order microservice interacts with one JMS provider (message broker) and the Fulfillment microservice interacts with a different JMS provider, so that both message brokers can be chosen and scaled to best support the load of each microservice

Answer: C

Explanation:
* If you need to scale a JMS provider/ message broker, - add nodes to scale it horizontally or - add memory to scale it vertically * Cons of adding another JMS provider/ message broker: - adds cost. - adds complexity to use two JMS brokers - adds Operational overhead if we use two brokers, say, ActiveMQ and IBM MQ * So Two options that mention to use two brokers are not best choice. * It's mentioned that "The Fulfillment microservice consumes Order messages, fulfills the order described therein, and then publishes an OrderFulfilled message. Each OrderFulfilled message can be consumed by any interested Mule application." - When you publish a message on a topic, it goes to all the subscribers who are interested - so zero to many subscribers will receive a copy of the message. - When you send a message on a queue, it will be received by exactly one consumer. * As we need multiple consumers to consume the message below option is not valid choice: "Order messages are sent to an Anypoint MQ exchange. OrderFulfilled messages are sent to an Anypoint MQ queue. Both microservices interact with Anypoint MQ as the message broker, which must therefore scale to support the load of both microservices" * Order messages are only consumed by one Mule application, the Fulfillment microservice, so we will publish it on queue and OrderFulfilled message can be consumed by any interested Mule application so it need to be published on Topic using same broker. * answer: Best choice in this scenario is: "Order messages are sent to a JMS queue. OrderFulfilled messages are sent to a JMS topic. Both microservices interact with the same JMS provider (message broker) instance, which must therefore scale to support the load of both microservices" Tried to depict scenario in diagram:
Diagram Description automatically generated

NEW QUESTION # 257
An API implementation is being developed to expose data from a production database via HTTP requests.
The API implementation executes a database SELECT statement that is dynamically created based upon data received from each incoming HTTP request. The developers are planning to use various types of testing to make sure the Mule application works as expected, can handle specific workloads, and behaves correctly from an API consumer perspective. What type of testing would typically mock the results from each SELECT statement rather than actually execute it in the production database?

A. Unit testing (white box)
B. Performance testing
C. Integration testing
D. Functional testing (black box)

Answer: A

Explanation:
In Unit testing instead of using actual backends, stubs are used for the backend services. This ensures that developers are not blocked and have no dependency on other systems.
In Unit testing instead of using actual backends, stubs are used for the backend services. This ensures that developers are not blocked and have no dependency on other systems.
Below are the typical characteristics of unit testing.
-- Unit tests do not require deployment into any special environment, such as a staging environment
-- Unit tests san be run from within an embedded Mule runtime
-- Unit tests can/should be implemented using MUnit
-- For read-only interactions to any dependencies (such as other APIs): allowed to invoke production endpoints
-- For write interactions: developers must implement mocks using MUnit
-- Require knowledge of the implementation details of the API implementation under test

NEW QUESTION # 258
A Mule application currently writes to two separate SQL Server database instances across the internet using a single XA transaction. It is 58. proposed to split this one transaction into two separate non-XA transactions with no other changes to the Mule application.
What non-functional requirement can be expected to be negatively affected when implementing this change?

A. Availability
B. Response time
C. Throughput
D. Consistency

Answer: D

Explanation:
Correct answer is Consistency as XA transactions are implemented to achieve this. XA transactions are added in the implementation to achieve goal of ACID properties. In the context of transaction processing, the acronym ACID refers to the four key properties of a transaction: atomicity, consistency, isolation, and durability. Atomicity : All changes to data are performed as if they are a single operation. That is, all the changes are performed, or none of them are. For example, in an application that transfers funds from one account to another, the atomicity property ensures that, if a debit is made successfully from one account, the corresponding credit is made to the other account. Consistency : Data is in a consistent state when a transaction starts and when it ends.For example, in an application that transfers funds from one account to another, the consistency property ensures that the total value of funds in both the accounts is the same at the start and end of each transaction. Isolation : The intermediate state of a transaction is invisible to other transactions. As a result, transactions that run concurrently appear to be serialized. For example, in an application that transfers funds from one account to another, the isolation property ensures that another transaction sees the transferred funds in one account or the other, but not in both, nor in neither. Durability : After a transaction successfully completes, changes to data persist and are not undone, even in the event of a system failure. For example, in an application that transfers funds from one account to another, the durability property ensures that the changes made to each account will not be reversed. MuleSoft reference: https://docs.mulesoft.com/mule-runtime/4.3/xa-transactions

NEW QUESTION # 259
What aspects of a CI/CD pipeline for Mule applications can be automated using MuleSoft-provided Maven plugins?

A. Compile, package, unit test, deploy, integration test (Incorrect)
B. Import from API designer, compile, package, unit test, deploy, publish to Anypoint Exchange
C. Compile, package, unit test, deploy, create associated API instances in API Manager
D. Compile, package, unit test, validate unit test coverage, deploy

Answer: D

Explanation:
Correct answer is "Compile, package, unit test, validate unit test coverage, deploy" Explanation : Anypoint Platform supports continuous integration and continuous delivery using industry standard tools Mule Maven Plugin The Mule Maven plugin can automate building, packaging and deployment of Mule applications from source projects Using the Mule Maven plugin, you can automate your Mule application deployment to CloudHub, to Anypoint Runtime Fabric, or on-premises, using any of the following deployment strategies * CloudHub deployment * Runtime Fabric deployment * Runtime Manager REST API deployment * Runtime Manager agent deployment MUnit Maven Plugin The MUnit Maven plugin can automate test execution, and ties in with the Mule Maven plugin. It provides a full suite of integration and unit test capabilities, and is fully integrated with Maven and Surefire for integration with your continuous deployment environment. Since MUnit 2.x, the coverage report goal is integrated with the maven reporting section. Coverage Reports are generated during Maven's site lifecycle, during the coverage-report goal. One of the features of MUnit Coverage is to fail the build if a certain coverage level is not reached. MUnit is not used for integration testing Also publishing to Anypoint Exchange or to create associated API instances in API Manager is not a part of CICD pipeline which can ne achieved using mulesoft provided maven plugin Explanation:
Architecture mentioned in the question can be diagrammatically put as below. Persistent Object Store is the correct answer .
* Mule Object Stores: An object store is a facility for storing objects in or across Mule applications. Mule uses object stores to persist data for eventual retrieval.
Mule provides two types of object stores:
1) In-memory store - stores objects in local Mule runtime memory. Objects are lost on shutdown of the Mule runtime. So we cant use in memory store in our scenario as we want to share watermark within all cloudhub workers
2) Persistent store - Mule persists data when an object store is explicitly configured to be persistent. Hence this watermark will be available even any of the worker goes down Diagram Description automatically generated

NEW QUESTION # 260
An organization uses Mule runtimes which are managed by Anypoint Platform - Private Cloud Edition. What MuleSoft component is responsible for feeding analytics data to non-MuleSoft analytics platforms?

A. Anypoint API Manager
B. Anypoint Runtime Manager
C. Anypoint Exchange
D. The Mule runtimes

Answer: B

Explanation:
Correct answer is Anypoint Runtime Manager
MuleSoft Anypoint Runtime Manager (ARM) provides connectivity to Mule Runtime engines deployed across your organization to provide centralized management, monitoring and analytics reporting. However, most enterprise customers find it necessary for these on-premises runtimes to integrate with their existing non MuleSoft analytics / monitoring systems such as Splunk and ELK to support a single pane of glass view across the infrastructure.
* You can configure the Runtime Manager agent to export data to external analytics tools.
Using either the Runtime Manager cloud console or Anypoint Platform Private Cloud Edition, you can:
--> Send Mule event notifications, including flow executions and exceptions, to Splunk or ELK.
--> Send API Analytics to Splunk or ELK. Sending data to third-party tools is not supported for applications deployed on CloudHub.
You can use the CloudHub custom log appender to integrate with your logging system. Reference:
https://docs.mulesoft.com/runtime-manager/ https://docs.mulesoft.com/release-notes/runtime-manager-agent
/runtime-manager-agent-release-notes
Additional Info:
It can be achieved in 3 steps:
1) register an agent to a runtime manager,
2) configure a gateway to enable API analytics to be sent to non MuleSoft analytics platform (Splunk for ex.)
- as highlighted in the following diagram and
3) setup dashboards.

NEW QUESTION # 261
......

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