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

Correct answer is Create WSDL specification using text editor SOAP services are specified using WSDL. A client program connecting to a web service can read the WSDL to determine what functions are available on the server. We can not create WSDL specification in Design Center. We need to use external text editor to create WSDL.

Explanation

Correct answer is Database polling continues Only HTTP requests sent to the remaining node continue to be accepted. Explanation : Architecture descripted in the question could be described as follows.When node 1 is down , DB polling will still continue via node 2 . Also requests which are coming directly to node 2 will also be accepted and processed in BAU fashion. Only thing that wont work is when requests are sent to Node 1 HTTP connector. The flaw with this architecture is HTTP clients are sending HTTP requests directly to individual cluster nodes. By default, clustering Mule runtime engines ensures high system availability. If a Mule runtime engine node becomes unavailable due to failure or planned downtime, another node in the cluster can assume the workload and continue to process existing events and messages

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Explanation

Correct answer is Application A accesses the persistent object store via the Object Store REST API Application B uses the Object Store connector to access a persistent object * Object Store v2 lets CloudHub applications store data and states across batch processes, Mule components and applications, from within an application or by using the Object Store REST API. * On-premise Mule applications cannot use Object Store v2. * You can select Object Store v2 as the implementation for Mule 3 and Mule 4 in CloudHub by checking the Object Store V2 checkbox in Runtime Manager at deployment time. * CloudHub Mule applications can use Object Store connector to write to the object store * The only way on-premises Mule applications can access Object Store v2 is via the Object Store REST API. * You can configure a Mule app to use the Object Store REST API to store and retrieve values from an object store in another Mule app.

Explanation

* Any change in the application will require a restart except when the issue outside the app. For below situations , you would need to redeploy the code after doing necessary changes

-- One of the stored procedures being called by the Mule application has been renamed. In this case, in the Mule application you will have to do changes to accommodate the new stored procedure name.

-- Required redesign of Mule applications to follow microservice architecture principles. As code is changed, deployment is must

-- If the credentials changed and you need to update the connector or the properties.

-- The credentials for accessing the database have been updated and the previous credentials are no longer valid. In this situation you need to restart or redeploy depending on how credentials are configured in Mule application.

* So Correct answer is The database server was unavailable for four hours due to a major outage but is now fully operational again as this is the only external issue to application.

When a batch job instance running on a runtime fabric environment with two cluster replicas encounters an unexpected failure, the following sequence of events occurs:

• Failure Detection: The runtime fabric environment detects the failure of the replica running the batch job.
• Replica Replacement: A new replica is provisioned to replace the failed one.
• Batch Job State Recovery: MuleSoft’s batch processing mechanism ensures that the state of the batch job is periodically saved (checkpointing). This allows the new replica to resume processing from the last saved state.
• Resumption of Processing: The new replica takes over the batch job, continuing from where the previous one left off, thus processing the remaining 99,000 records without starting from scratch or causing duplicate processing.

References:

• MuleSoft Documentation on Batch Processing
• Runtime Fabric Guide

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MuleSoft customers often favor a MuleSoft-hosted Anypoint Platform runtime plane over a customer-hosted runtime for the following reasons:

• Reduced time-to-market for the first application (C): Using a MuleSoft-hosted runtime plane accelerates the deployment process because MuleSoft manages the infrastructure, allowing customers to focus on developing and deploying their applications quickly. This leads to faster time-to-market for the initial application and subsequent updates.
• Reduced IT operations effort (E): By leveraging a MuleSoft-hosted environment, customers offload the operational responsibilities, such as infrastructure maintenance, updates, and scalability management, to MuleSoft. This reduces the IT operations workload and allows internal teams to focus on more strategic initiatives.

In contrast, other options like reduced application latency and increased application throughput are not directly influenced by whether the runtime plane is MuleSoft-hosted or customer-hosted.

References

• MuleSoft Anypoint Platform Documentation
• MuleSoft Hosted vs. Customer Hosted Deployment Guides

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/

MuleSoft's API development best practices emphasize a design-first approach, which starts with writing and approving an API contract before any implementation begins. This approach ensures that the API's interface is agreed upon and understood by all stakeholders before the backend is built. It involves creating an API specification using tools like RAML or OpenAPI, which serves as a blueprint for development. This method promotes better planning, communication, and alignment between different teams and stakeholders, leading to more efficient and predictable API development processes.

References:

• API Design Best Practices
• MuleSoft's Approach to API Development

To meet the requirements of enriching logging with more context and improving throughput while reducing latency, the customer should use an asynchronous logging approach. Here's why option B is correct:

• Async Logger: Asynchronous logging helps in improving the performance by decoupling the logging from the main thread of execution. This reduces the latency of message processing since logging operations are offloaded to a separate thread.
• Logging Level Greater than INFO: Logging at levels such as WARN, ERROR, or FATAL ensures that only essential logs are written asynchronously, further enhancing performance. Avoiding DEBUG or TRACE levels unless necessary reduces the overhead of logging.
• Pattern Layout with [%MDC]: Using the pattern layout with [%MDC] in the log4j2.xml configuration file allows the inclusion of mapped diagnostic context in the logs. MDC is a feature that provides context-specific information, such as transaction IDs or user IDs, which helps in tracing and debugging.

Example configuration in log4j2.xml:

This configuration ensures that the logs are enriched with context information provided by MDC and processed asynchronously to maintain high throughput and low latency.

References

• Log4j2 Asynchronous Logging
• Mapped Diagnostic Context (MDC) in Log4j2

Explanation

* 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.

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* 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.

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* 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