MCIA-Level-1 Exam Dumps - MuleSoft Certified Architect Questions and Answers

Explanation

Correct answer is Mule correlation ID 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.

• Requirement Analysis: The organization wants to standardize dependencies across all new and ongoing MuleSoft projects to minimize the impact of frequent plugin version upgrades and external plugin project dependencies.
• Solution: Creating a parent POM (Project Object Model) file with all required dependencies and referencing it in each application's POM.xml file is the best practice.
• Implementation Steps:

pom 1.0.0 pom org.mule.runtime mule-core-extensions-maven-plugin 1.0.0

• uk.co.certification.simulator.questionpool.PList@18be4ec0

4.0.0 com.example parent-pom 1.0.0 child-application 1.0.0

• uk.co.certification.simulator.questionpool.PList@18be4f40
• Advantages:

References

• MuleSoft Documentation on Managing dependencies with Maven
• Apache Maven Documentation on POM Reference

According to MuleSoft's surveys of global IT leaders, a common cause of IT project failure is a lack of alignment around business outcomes. When IT projects do not have clear business objectives or fail to align with the strategic goals of the organization, they are more likely to face challenges and fail to deliver value. Ensuring that IT initiatives are closely tied to business goals and have stakeholder buy-in is crucial for their success.

References:

• Why IT Projects Fail
• Aligning IT and Business Strategies

Explanation

* "Create a Mule domain project that maintains the credentials as Mule domain-shared resources" is wrong as domain project is not supported in Cloudhub * We should Avoid Creating duplicates in each Mule application but below two options cause duplication of credentials - Store the credentials in properties files in a shared folder within the organization’s data center. Have the Mule applications load properties files from this shared location at startup - Segregate the credentials for each backend system into environment-specific properties files. Package these properties files in each Mule application, from where they are loaded at startup So these are also wrong choices * Credentials service is the best approach in this scenario. Mule domain projects are not supported on CloudHub. Also its is not recommended to have multiple copies of configuration values as this makes difficult to maintain Use the Mule Credentials Vault to encrypt data in a .properties file. (In the context of this document, we refer to the .properties file simply as the properties file.) The properties file in Mule stores data as key-value pairs which may contain information such as usernames, first and last names, and credit card numbers. A Mule application may access this data as it processes messages, for example, to acquire login credentials for an external Web service. However, though this sensitive, private data must be stored in a properties file for Mule to access, it must also be protected against unauthorized – and potentially malicious – use by anyone with access to the Mule application

Explanation

Types of logging:

A) Synchronous: The execution of thread that is processing messages is interrupted to wait for the log message to be fully handled before it can continue.

● The execution of the thread that is processing your message is interrupted to wait for the log message to be fully output before it can continue

● Performance degrades because of synchronous logging

● Used when the log is used as an audit trail or when logging ERROR/CRITICAL messages

● If the logger fails to write to disk, the exception would raise on the same thread that's currently processing the Mule event. If logging is critical for you, then you can rollback the transaction.

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B) Asynchronous:

● The logging operation occurs in a separate thread, so the actual processing of your message won’t be delayed to wait for the logging to complete

● Substantial improvement in throughput and latency of message processing

● Mule runtime engine (Mule) 4 uses Log4j 2 asynchronous logging by default

● The disadvantage of asynchronous logging is error handling.

● If the logger fails to write to disk, the thread doing the processing won't be aware of any issues writing to the disk, so you won't be able to rollback anything. Because the actual writing of the log gets differed, there's a chance that log messages might never make it to disk and get lost, if Mule were to crash before the buffers are flushed.

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So Correct answer is: Asynchronous logging can improve Mule event processing throughput while also reducing the processing time for each Mule event

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

In a microservices architecture, a service mesh manages the communication between microservices. This involves handling service discovery, load balancing, failure recovery, metrics, and monitoring. Service meshes also provide more complex operational requirements like A/B testing, canary releases, rate limiting, access control, and end-to-end authentication. By abstracting these functionalities away from individual microservices, a service mesh allows developers to focus on business logic while ensuring reliable and secure inter-service communication.

References:

• Understanding Service Mesh
• Service Mesh for Microservices

To ensure that data is encrypted both in-transit and at-rest, and to validate incoming requests to the Payment Processing API, the following approach is recommended:

• TLS Inbound Policy: Apply a Transport Layer Security (TLS) - Inbound policy in API Manager. This policy ensures that the data is encrypted during transmission and can be decrypted by the API Manager before it reaches the Mule application.
• Decryption: With the TLS policy applied, the message payload is decrypted when it is received by the API Manager.
• JSON Validation: After decryption, the Mule application can use the JSON Validation module to validate the structure and content of the JSON data. This ensures that the payload conforms to the specified format and contains valid data.

This approach ensures that data is securely transmitted and properly validated upon receipt.

References:

• Transport Layer Security (TLS) Policies
• JSON Validation Module