Salesforce MULESOFT-INTEGRATION-ARCHITECT-I Online Practice Questions and Exam Preparation

Salesforce MULESOFT-INTEGRATION-ARCHITECT-I Online Questions & Answers

• Question 11:

  An organization is not meeting its growth and innovation objectives because IT cannot deliver projects last enough to keep up with the pace of change required by the business.

  According to MuleSoft's IT delivery and operating model, which step should the organization lake to solve this problem?

  A. Modify IT governance and security controls so that line of business developers can have direct access to the organization's systems of record
  B. Switch from a design-first to a code-first approach for IT development
  C. Adopt a new approach that decouples core IT projects from the innovation that happens within each line of business
  D. Hire more |T developers, architects, and project managers to increase IT delivery
  C. Adopt a new approach that decouples core IT projects from the innovation that happens within each line of business

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  Explanation/Reference:

  MuleSoft's IT delivery and operating model suggests adopting an approach that decouples core IT projects from the innovation within each line of business. This approach, often referred to as API-led connectivity, allows different lines of business to innovate and deliver projects independently by using reusable APIs that provide access to core systems and data. This decoupling enhances agility, speeds up delivery, and ensures that core IT maintains control over critical systems and data while enabling rapid innovation. References: API-led Connectivity: Build Your Digital Platform for Change MuleSoft's API-led Connectivity Approach

• Question 12:

  What aspect of logging is only possible for Mule applications deployed to customer-hosted Mule runtimes, but NOT for Mule applications deployed to CloudHub?

  A. To send Mule application log entries to Splunk
  B. To change tog4j2 tog levels in Anypoint Runtime Manager without having to restart the Mule application
  C. To log certain messages to a custom log category
  D. To directly reference one shared and customized log4j2.xml file from multiple Mule applications
  D. To directly reference one shared and customized log4j2.xml file from multiple Mule applications

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  Explanation/Reference:

  *

  Correct answer is To directly reference one shared and customized log4j2.xml file from multiple Mule applications. Key word to note in the answer is directly.

  *

  By default, CloudHub replaces a Mule application's log4j2.xml file with a CloudHub log4j2.xml file. This specifies the CloudHub appender to write logs to the CloudHub logging service.

  *

  You cannot modify CloudHub log4j2.xml file to add any custom appender. But there is a process in order to achieve this. You need to raise a request on support portal to disable CloudHub provided Mule application log4j2 file.

  *

  Once this is done , Mule application's log4j2.xml file is used which you can use to send/export application logs to other log4j2 appenders, such as a custom logging system MuleSoft does not own any responsibility for lost logging data due to misconfiguration of your own log4j appender if it happens by any chance.

  *

  One more difference between customer-hosted Mule runtimes and CloudHub deployed mule instance is that -CloudHub system log messages cannot be sent to external log management system without installing custom CH logging configuration through support -where as Customer-hosted runtime can send system and application log to external log management system MuleSoft Reference: https://docs.mulesoft.com/runtime-manager/viewing-log-data https://docs.mulesoft.com/runtime-manager/custom-log-appender

  

  

• Question 13:

  Which Anypoint Platform component helps integration developers discovers and share reusable APIs, connectors, and templates?

  A. Anypoint Exchange
  B. API Manager
  C. Anypoint Studio
  D. Design Center
  A. Anypoint Exchange

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  Explanation/Reference:

  Anypoint Exchange is the Anypoint Platform component that helps integration developers discover and share reusable APIs, connectors, and templates. It acts as a central repository where developers can publish and access various assets, facilitating reuse and collaboration within the organization. By using Anypoint Exchange, developers can reduce duplication of effort, speed up development processes, and ensure consistency across integrations. Other components like API Manager, Anypoint Studio, and Design Center serve different purposes, such as managing APIs, developing Mule applications, and designing API specifications, but they are not specifically focused on discovering and sharing reusable assets. References: MuleSoft Documentation on Anypoint Exchange Best Practices for Asset Reuse on Anypoint Platform

• Question 14:

  A company is modernizing its legal systems lo accelerate access lo applications and data while supporting the adoption of new technologies. The key to achieving this business goal is unlocking the companies' key systems and dala including

  microservices miming under Docker and kubernetes containers using apis.

  Considering the current aggressive backlog and project delivery requirements the company wants to take a strategic approach in the first phase of its transformation projects by quickly deploying API's in mule runtime that are able lo scale,

  connect to on premises systems and migrate as needed.

  Which runtime deployment option supports company's goals?

  A. Customer hosted self provisioned runtimes
  B. Cloudhub runtimes
  C. Runtime fabric on self managed Kubernetes
  D. Runtime fabric on Vmware metal
  C. Runtime fabric on self managed Kubernetes

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  Explanation/Reference:

  To support the company's goals of unlocking key systems and data, quickly deploying scalable APIs, and connecting to on-premises systems, while also preparing for future migrations, the best runtime deployment option is using Runtime

  Fabric on self-managed Kubernetes. Here's why:

  Scalability: Kubernetes is designed to scale applications easily and efficiently. By deploying Mule runtimes on a self-managed Kubernetes cluster, the company can dynamically scale its APIs based on demand, ensuring performance and

  reliability. Flexibility: Running on self-managed Kubernetes allows the company to have control over the infrastructure. They can customize the environment to meet their specific needs, integrate with existing on-premises systems, and

  support their microservices architecture running in Docker containers.

  Future-Proofing: Kubernetes supports hybrid and multi-cloud deployments, making it easier to migrate workloads between different environments as needed. This aligns with the company's goal of being able to migrate their systems as part of

  their strategic approach.

  Efficiency: By leveraging Kubernetes, the company can automate deployment, scaling, and management of containerized applications, reducing the burden on IT and DevOps teams.

  References:

  MuleSoft Documentation on Runtime Fabric: https://docs.mulesoft.com/runtime-fabric/1.9/

  Kubernetes Documentation: https://kubernetes.io/docs/home/

• Question 15:

  An architect is designing a Mule application to meet the following two requirements:

  1.

  The application must process files asynchronously and reliably from an FTPS server to a back-end database using VM intermediary queues for load-balancing Mule events.

  2.

  The application must process a medium rate of records from a source to a target system using a Batch Job scope.

  To make the Mule application more reliable, the Mule application will be deployed to two CloudHub 1.0 workers.

  Following MuleSoft-recommended best practices, how should the Mule application deployment typically be configured in Runtime Manger to best support the performance and reliability goals of both the Batch Job scope and the file processing VM queues?

  A. Check the Persistent VM queues checkbox in the application deployment configuration
  B. Check the Non-persistent VM queues checkbox in the application deployment configuration
  C. In the Runtime Manager Properties tab, disable persistent VM queues for Batch Job scopes
  D. In the Runtime Manager Properties tab, enable persistent VM queues for the FTPS connector
  A. Check the Persistent VM queues checkbox in the application deployment configuration

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  Explanation/Reference:

  Requirements:

  Persistent VM Queues:

  MuleSoft Best Practices:

  Configuration in Runtime Manager:

  References:

  MuleSoft Documentation on VM Queues: VM Queues

  MuleSoft Best Practices: MuleSoft Best Practices

  CloudHub Deployment Guide: CloudHub Deployment

• Question 16:

  Additional nodes are being added to an existing customer-hosted Mule runtime cluster to improve performance. Mule applications deployed to this cluster are invoked by API clients through a load balancer.

  What is also required to carry out this change?

  A. A new load balancer must be provisioned to allow traffic to the new nodes in a round-robin fashion
  B. External monitoring tools or log aggregators must be configured to recognize the new nodes
  C. API implementations using an object store must be adjusted to recognize the new nodes and persist to them
  D. New firewall rules must be configured to accommodate communication between API clients and the new nodes
  B. External monitoring tools or log aggregators must be configured to recognize the new nodes

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  Explanation/Reference:

  *

  Clustering is a group of servers or mule runtime which acts as a single unit.

  *

  Mulesoft Enterprise Edition supports scalable clustering to provide high availability for the Mulesoft application.

  *

  In simple terms, virtual servers composed of multiple nodes and they communicate and share information through a distributed shared memory grid.

  *

  By default, Mulesoft ensures the High availability of applications if clustering implemented.

  *

  Let's consider the scenario one of the nodes in cluster crashed or goes down and under maintenance. In such cases, Mulesoft will ensure that requests are processed by other nodes in the cluster. Mulesoft clustering also ensures that the request is load balanced between all the nodes in a cluster.

  *

  Clustering is only supported by on-premise Mule runtime and it is not supported in Cloudhub. Correct answer is External monitoring tools or log aggregators must be configured to recognize the new nodes

  *

  Rest of the options are automatically taken care of when a new node is added in cluster.

  Reference: https://docs.mulesoft.com/runtime-manager/cluster-about

• Question 17:

  A gaming company has implemented an API as a Mule application and deployed the API implementation to a CloudHub 2.0 private space. The API implementation must connect to a mainframe application running in the customer's on-premises corporate data center and also to a Kafka cluster running in an Amazon AWS VPC.

  What is the most efficient way to enable the API to securely connect from its private space to the mainframe application and Kafka cluster?

  

  

  

  

  A. In Runtime Manager, set up VPC peering between the CloudHub 2.0 private network and the on-premises data center. In the AWS account, set up VPC peering between the AWS VPC and the CloudHub 2.0 private network.
  B. In the AWS account, attach the CloudHub 2.0 private space to an AWS transit gateway that routes from the CloudHub 2.0 private space to the on-premises data center. In Runtime Manager, configure an Anypoint VPN to route from the CloudHub 2.0 private space to the AWS VPC.
  C. In Runtime Manager, configure an Anypoint VPN to route from the CloudHub 2.0 private space to the on-premises data center. In the AWS account, attach the private.
  D. In the AWS account, attach the private space directly to the AWS VPC, In the AWS account, use an AWS transit gateway to route from the AWS VPC to the on-premises data center.
  B. In the AWS account, attach the CloudHub 2.0 private space to an AWS transit gateway that routes from the CloudHub 2.0 private space to the on-premises data center. In Runtime Manager, configure an Anypoint VPN to route from the CloudHub 2.0 private space to the AWS VPC.

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  Explanation/Reference:

  To enable the API to securely connect from its CloudHub 2.0 private space to both the on-premises mainframe application and the Kafka cluster in an Amazon AWS VPC, the following approach is recommended:

  AWS Transit Gateway: In the AWS account, attach the CloudHub 2.0 private space to an AWS Transit Gateway. This gateway facilitates routing between the CloudHub private space and the on-premises data center. Routing to On-Premises:

  The AWS Transit Gateway will route traffic from the CloudHub 2.0 private space to the on-premises data center, enabling secure and efficient communication. Anypoint VPN: In MuleSoft Runtime Manager, configure an Anypoint VPN to

  establish a secure connection from the CloudHub 2.0 private space to the AWS VPC where the Kafka cluster is hosted. This VPN ensures encrypted and secure communication between CloudHub and AWS VPC.

  This method uses both AWS Transit Gateway and Anypoint VPN to create a secure and efficient network setup, allowing the API to connect to both on-premises and AWS resources.

  References:

  AWS Transit Gateway Documentation

  Anypoint VPN Configuration

• Question 18:

  An organization has defined a common object model in Java to mediate the communication between different Mule applications in a consistent way. A Mule application is being built to use this common object model to process responses from a SOAP API and a REST API and then write the processed results to an order management system.

  The developers want Anypoint Studio to utilize these common objects to assist in creating mappings for various transformation steps in the Mule application. What is the most idiomatic (used for its intended purpose) and performant way to utilize these common objects to map between the inbound and outbound systems in the Mule application?

  A. Use JAXB (XML) and Jackson (JSON) data bindings
  B. Use the WSS module
  C. Use the Java module
  D. Use the Transform Message component
  A. Use JAXB (XML) and Jackson (JSON) data bindings

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  Explanation/Reference:

  Reference: https://docs.mulesoft.com/mule-runtime/3.9/understanding-mule-configuration

• Question 19:

  A system administrator needs to determine when permissions were last changed for an Anypoint Platform user. Which Anypoint Platform component should the administrator use to obtain this information?

  A. Audit Logging
  B. Anypoint Monitoring
  C. Anypiont Studio
  D. Mule Stack Traces
  A. Audit Logging

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  Explanation/Reference:

  To determine when permissions were last changed for an Anypoint Platform user, the system administrator should use the Audit Logging component. Audit Logging in Anypoint Platform captures detailed logs of various activities, including changes to user permissions, login attempts, and other significant actions. These logs provide a historical record that administrators can review to track changes and ensure compliance with security policies. Other components like Anypoint

  Monitoring, Anypoint Studio, and Mule Stack Traces are used for monitoring application performance, development, and debugging, respectively, but they do not provide specific information about user permission changes.

  References:

  MuleSoft Documentation on Audit Logging

  Anypoint Platform User Management

• Question 20:

  One of the backend systems involved by the API implementation enforces rate limits on the number of request a particle client can make.

  Both the back-end system and API implementation are deployed to several non-production environments including the staging environment and to a particular production environment. Rate limiting of the back-end system applies to all non-production environments.

  The production environment however does not have any rate limiting.

  What is the cost-effective approach to conduct performance test of the API implementation in the non-production staging environment?

  A. Including logic within the API implementation that bypasses in locations of the back-end system in the staging environment and invoke a Mocking service that replicates typical back-end system responses Then conduct performance test using this API implementation
  B. Use MUnit to simulate standard responses from the back-end system. Then conduct performance test to identify other bottlenecks in the system
  C. Create a Mocking service that replicates the back-end system's production performance characteristics Then configure the API implementation to use the mocking service and conduct the performance test
  D. Conduct scaled-down performance tests in the staging environment against rate-limiting back-end system. Then upscale performance results to full production scale
  C. Create a Mocking service that replicates the back-end system's production performance characteristics Then configure the API implementation to use the mocking service and conduct the performance test

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  Explanation/Reference:

  To conduct performance testing in a non-production environment where rate limits are enforced, the most cost-effective approach is:

  C. Create a Mocking service that replicates the back-end system's production performance characteristics. Then configure the API implementation to use the mocking service and conduct the performance test.

  Mocking Service: Develop a mock service that emulates the performance characteristics of the production back-end system. This service should mimic the response times, data formats, and any relevant behavior of the actual back-end

  system without imposing rate limits.

  Configuration: Modify the API implementation to route requests to the mocking service instead of the actual back-end system. This ensures that the performance tests are not impacted by the rate limits imposed in the non-production

  environment.

  Performance Testing: Conduct the performance tests using the API implementation configured with the mocking service. This approach allows you to assess the performance under expected production load conditions without being

  constrained by non-production rate limits.

  This method ensures that performance testing is accurate and reflective of the production environment without additional costs or constraints due to rate limiting in staging environments.

  References:

  MuleSoft Documentation: Mocking Services

  MuleSoft Documentation: Performance Testing