MuleSoft-Integration-Architect-I Salesforce Certified MuleSoft Platform Integration Architect (Mule-Arch-202) Free Practice Exam Questions (2025 Updated)

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.

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.

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

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

To close the IT delivery gap, MuleSoft recommends that IT organizations make their technology assets easily discoverable via a central repository. This approach ensures that existing assets, such as APIs, connectors, templates, and other reusable components, are accessible to all teams within the organization. By having a central repository, teams can quickly find and leverage these assets, reducing duplication of effort, speeding up project delivery, and fostering a culture of reuse and collaboration. This strategy aligns with the principles of an API-led connectivity approach, where reusable assets and APIs form the foundation for scalable and efficient IT delivery.

References

MuleSoft Documentation on API-led Connectivity

Anypoint Platform Best Practices for Asset Management

To extend Mule APIs to the EU (Frankfurt) region and minimize latency for European users, follow these steps:

Set Region Property: In Runtime Manager, for each Mule application deployment, set the Region property to EU (Frankfurt). This deploys the application to the desired region, optimizing performance for European users.

Reuse Application Names: Keep the same Mule application names as used in the North American region. This approach maintains consistency and simplifies management.

Communicate New URLs: Inform the consuming API clients in Europe of the new URLs in the format {API-name}—{environment}.de-ci.cloudhub.io. These URLs will direct the clients to the applications deployed in the EU region, ensuring reduced latency and improved performance.

This strategy effectively deploys the same Mule APIs to the CloudHub EU region, leveraging the existing control plane in North America.

Explanation

Correct answer is Use a Batch job scope to bulk insert records into the database

* Batch Job is most efficient way to manage millions of records.

A few points to note here are as follows :

Reliability: If you want reliabilty while processing the records, i.e should the processing survive a runtime crash or other unhappy scenarios, and when restarted process all the remaining records, if yes then go for batch as it uses persistent queues.

Error Handling: In Parallel for each an error in a particular route will stop processing the remaining records in that route and in such case you'd need to handle it using on error continue, batch process does not stop during such error instead you can have a step for failures and have a dedicated handling in it.

Memory footprint: Since question said that there are millions of records to process, parallel for each will aggregate all the processed records at the end and can possibly cause Out Of Memory.

Batch job instead provides a BatchResult in the on complete phase where you can get the count of failures and success. For huge file processing if order is not a concern definitely go ahead with Batch Job

Parallel Execution:

In a Scatter-Gather scope, all routes are executed in parallel. This allows multiple operations to be performed simultaneously, which can improve performance and efficiency when dealing with independent tasks.

Transaction Management:

When Scatter-Gather operates within a local transaction, all database operations performed in parallel routes are part of the same transaction context.

Error Handling and Rollback:

If any error occurs within any of the parallel routes inside the Scatter-Gather scope, it triggers a rollback of all the database operations performed within the transaction. This ensures data consistency and integrity.

Explanation

Context of the question is about managing and governing mule applications deployed on Anypoint platform.

Anypoint API Manager (API Manager) is a component of Anypoint Platform that enables you to manage, govern, and secure APIs. It leverages the runtime capabilities of API Gateway and Anypoint Service Mesh, both of which enforce policies, collect and track analytics data, manage proxies, provide encryption and authentication, and manage applications.

Mule Ref Doc : https://docs.mulesoft.com/api-manager/2.x/getting-started-proxy

When configuring the TLS context for an HTTP request to the Google Maps API, the primary goal is to ensure that the Mule application can establish a secure connection. Here’s a detailed explanation of the necessary steps:

Download Google Public Certificate:

Open a browser and navigate to the Google Maps API URL (e.g., https://maps.googleapis.com).

Click on the lock icon in the address bar and view the certificate details.

Export the certificate, usually in a .cer or .crt format.

Generate JKS File from Certificate:

Use a tool like keytool (which comes with the Java Development Kit) to import the downloaded certificate into a Java KeyStore (JKS) file.

keytool -importcert -file google.cer -keystore truststore.jks -alias google

Add JKS File to Truststore:

In your Mule application, configure the HTTP Request Connector with the generated JKS file as the Truststore in the TLS context.

Configure HTTP Request Connector:

Ensure the HTTP Request Connector references this Truststore configuration.

By completing these steps, your Mule application will trust the Google Maps API server’s certificate, allowing for secure communication.

References

MuleSoft Documentation: Configuring TLS

Google Maps API Documentation

The Salesforce API used to deploy, retrieve, create, update, or delete customization information, such as custom object definitions, using Mule Salesforce Connectors in a Mule application, is the Metadata API. The Metadata API enables programmatic access to the metadata of Salesforce organizations, allowing developers to manage customizations and configurations programmatically.

Using the Metadata API, Mule applications can automate the deployment and management of Salesforce customizations, facilitating continuous integration and deployment processes within Salesforce environments.

References

MuleSoft Documentation on Salesforce Connectors

Salesforce Metadata API Developer Guide

According to MuleSoft, a significant business benefit associated with an API-led connectivity approach using Anypoint Platform is increased developer productivity through self-service of API assets. API-led connectivity promotes the creation of reusable APIs that can be easily discovered and consumed by developers across the organization. This self-service model reduces dependencies, accelerates development, and fosters innovation by enabling teams to quickly build and integrate applications using existing APIs without waiting for central IT to provide access.

Explanation

* 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.

Explanation

When an operation in a Mule application fails to connect to an external server, the default behavior is for the operation to fail immediately and return a connectivity error. You can modify this default behavior by configuring a reconnection strategy for the operation. You can configure a reconnection strategy for an operation either by modifying the operation properties or by modifying the configuration of the global element for the operation. The following are the available reconnection strategies and their behaviors: None Is the default behavior, which immediately returns a connectivity error if the attempt to connect is unsuccessful Standard (reconnect) Sets the number of reconnection attempts and the interval at which to execute them before returning a connectivity error Forever (reconnect-forever) Attempts to reconnect continually at a given interval

Explanation

* The Object Store V2 API enables API access to Anypoint Platform Object Store v2.

* 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. However, Object Store v2 is not designed for app-to-app communication. To share data between two Mule4 apps, use a queue in Anypoint MQ.

* The Object Store v2 APIs enable you to use REST to perform the following:

- Retrieve a list of object stores and keys associated with an application.

- Store and retrieve key-value pairs in an object store.

- Delete key-value pairs from an object store.

- Retrieve Object Store usage statistics for your organization.

- Object Store provides these APIs:

Object Store API

Object Store Stats API

The interaction composition pattern used by the integration architect for the order processing API that coordinates stateful interactions with various microservices is called orchestration. Orchestration involves managing and coordinating multiple services to achieve a specific business process or workflow. In this case, the order processing API is responsible for validating, creating, and fulfilling new product orders by coordinating interactions with different microservices.

Orchestration provides a centralized control mechanism where the order processing API acts as the orchestrator, handling the sequence of service calls, managing state, and ensuring that the business process is executed correctly.

References

MuleSoft API-led Connectivity Approach

Patterns for Microservices and API Design

In an HTTP/1.1-compliant web service, the class of HTTP response status codes that indicates successful client requests is the 2xx class. These status codes signify that the client's request was successfully received, understood, and accepted by the web service. Common 2xx status codes include:

200 OK: The request was successful.

201 Created: The request was successful and a new resource was created.

202 Accepted: The request has been accepted for processing, but the processing is not yet complete.

Other status code classes like 3xx (redirection), 4xx (client errors), and 5xx (server errors) indicate different types of responses and do not signify successful request processing.

References

IETF RFC 2616: HTTP/1.1 Specification

HTTP Status Code Definitions

Explanation

Correct answer is An HTTP Load Balancer.

Key thing to note here is that we are deploying application to customer hosted Mule runtime. This means we will need load balancer to route the requests to different instances of the cluster.

Rest all options are distractors and their requirement depends on project use case.

Scatter-Gather sends a request message to multiple targets concurrently. It collects the responses from all routes, and aggregates them into a single message.

To automate the promotion and deployment of API Manager policies as part of a CI/CD process, an organization can use the Anypoint CLI (Command Line Interface). The Anypoint CLI provides a set of commands to interact with various components of the Anypoint Platform, including API Manager.

Using the Anypoint CLI, you can:

Apply policies to API instances.

Promote APIs and their associated policies across different environments.

Script these actions as part of the CI/CD pipeline to ensure consistency and automation in managing API policies.

Other tools like the MUnit Maven plugin, Mule Maven plugin, and Runtime Manager agent do not provide direct capabilities to manage API Manager policies.

References

MuleSoft Anypoint CLI Documentation

Automating API Management with Anypoint CLI