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>> MuleSoft-Integration-Architect-I Exam Assessment <<
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NEW QUESTION # 121
What aspects of a CI/CD pipeline for Mule applications can be automated using MuleSoft-provided Maven plugins?
Answer: B
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 # 122
A company is designing an integration Mule application to process orders by submitting them to a back-end system for offline processing. Each order will be received by the Mule application through an HTTP5 POST and must be acknowledged immediately.
Once acknowledged the order will be submitted to a back-end system. Orders that cannot be successfully submitted due to the rejections from the back-end system will need to be processed manually (outside the banking system).
The mule application will be deployed to a customer hosted runtime and will be able to use an existing ActiveMQ broker if needed. The ActiveMQ broker is located inside the organization's firewall. The back-end system has a track record of unreliability due to both minor network connectivity issues and longer outages.
Which combination of Mule application components and ActiveMQ queues are required to ensure automatic submission of orders to the back-end system while supporting but minimizing manual order processing?
Answer: D
NEW QUESTION # 123
Which of the below requirements prevent the usage of Anypoint MQ in a company's network? (Choose two answers)
Answer: C,D
Explanation:
Anypoint MQ is a cloud-based messaging service provided by MuleSoft. It is designed to work within MuleSoft's cloud ecosystem, which can impose certain limitations that might prevent its use in some scenarios:
* Message Broker Must Be Hosted On-Premises:
* Anypoint MQ is a cloud service and cannot be hosted on-premises. If a company requires its message broker to be hosted within its own data center for security, compliance, or other reasons, Anypoint MQ would not be suitable.
* Ability for a Third Party Outside the Company's Network to Consume Events from the Queue:
* Anypoint MQ is designed to work primarily within the Anypoint Platform ecosystem. While it does support external consumers, it requires proper security configurations, and there may be limitations or additional steps needed to securely expose queues to third-party systems outside the company's network.
References
* MuleSoft Documentation: Anypoint MQ
* MuleSoft Anypoint MQ Overview
NEW QUESTION # 124
An organization is designing an integration solution to replicate financial transaction data from a legacy system into a data warehouse (DWH).
The DWH must contain a daily snapshot of financial transactions, to be delivered as a CSV file. Daily transaction volume exceeds tens of millions of records, with significant spikes in volume during popular shopping periods.
What is the most appropriate integration style for an integration solution that meets the organization's current requirements?
Answer: D
Explanation:
Correct answer is Batch-triggered ETL Within a Mule application, batch processing provides a construct for asynchronously processing larger-than-memory data sets that are split into individual records. Batch jobs allow for the description of a reliable process that automatically splits up source data and stores it into persistent queues, which makes it possible to process large data sets while providing reliability. In the event that the application is redeployed or Mule crashes, the job execution is able to resume at the point it stopped.
NEW QUESTION # 125
A new Mule application under development must implement extensive data transformation logic. Some of the data transformation functionality is already available as external transformation services that are mature and widely used across the organization; the rest is highly specific to the new Mule application.
The organization follows a rigorous testing approach, where every service and application must be extensively acceptance tested before it is allowed to go into production.
What is the best way to implement the data transformation logic for this new Mule application while minimizing the overall testing effort?
Answer: A
Explanation:
Correct answer is Implement transformation logic in the new Mule application using DataWeave, invoking existing transformation services when possible. * The key here minimal testing effort, "Extend existing transformation logic" is not a feasible option because additional functionality is highly specific to the new Mule application so it should not be a part of commonly used functionality. So this option is ruled out. * "Implement transformation logic in the new Mule application using DataWeave, replicating the transformation logic of existing transformation services" Replicating the transformation logic of existing transformation services will cause duplicity of code. So this option is ruled out. * "Implement and expose all transformation logic as microservices using DataWeave, so it can be reused by any application component that needs it, including the new Mule application" as question specifies that the transformation is app specific and wont be used outside
NEW QUESTION # 126
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