Free Salesforce MuleSoft-Integration-Architect-I Practice Exam with Questions & Answers

Explanation

Correct answer is: Add a Mulesoft hosted Anypoint VPC configured and with VPC Peering to the AWS VPC * Connecting to your Anypoint VPC extends your corporate network and allows CloudHub workers to access resources behind your corporate firewall.

* You can connect on-premises data centers through a secured VPN tunnel, or a private AWS VPC through VPC peering, or by using AWS Direct Connect.

MuleSoft Doc Reference : https://docs.mulesoft.com/runtime-manager/virtual-private-cloud

Requirements:

Asynchronous and Reliable File Processing: The application must process files from an FTPS server to a back-end database using VM intermediary queues for load balancing.

Batch Job Processing: The application must process records from a source to a target system using a Batch Job scope.

Persistent VM Queues:

Reliability: Persistent VM queues ensure that messages are not lost even if there is a system failure or restart. This is critical for reliable file processing and load balancing.

Asynchronous Processing: Persistent queues allow for asynchronous processing, where messages can be stored and processed independently of the producer and consumer lifecycles.

MuleSoft Best Practices:

Persistent VM Queues for Load Balancing: Using persistent VM queues aligns with MuleSoft best practices for ensuring reliable message processing and load balancing between Mule events.

High Availability: With CloudHub 1.0 workers, enabling persistent VM queues helps maintain high availability and reliability of the application.

Batch Job Scope: Ensuring persistence for VM queues also benefits batch processing by maintaining consistency and ensuring all records are processed even in the event of disruptions.

Configuration in Runtime Manager:

Deployment Configuration: When deploying the Mule application in Runtime Manager, check the "Persistent VM queues" checkbox to enable this feature.

Impact: This configuration ensures that the application meets its performance and reliability goals by safeguarding the integrity and continuity of the processing tasks.

MuleSoft Documentation on VM Queues: VM Queues

MuleSoft Best Practices: MuleSoft Best Practices

CloudHub Deployment Guide: CloudHub Deployment

Explanation

* If your API implementation involves putting a load balancer in front of your APIkit application, configure the load balancer to redirect URLs that reference the baseUri of the application directly. If the load balancer does not redirect URLs, any calls that reach the load balancer looking for the application do not reach their destination.

* When you receive incoming traffic through the load balancer, the responses will go out the same way. However, traffic that is originating from your instance will not pass through the load balancer. Instead, it is sent directly from the public IP address of your instance out to the Internet. The ELB is not involved in that scenario.

* The question says “each API is deployed to multiple redundant Mule runtimes”, that seems to be a hint for self hosted Mule runtime cluster. Set Inbound allowed for the LB, outbound allowed for runtime to request out.

* Hence correct way is to enable communication from each API’s Mule Runtimes and Network zone to the load balancer of the other API. Because communication is asynchronous one

The File Transfer Protocol (FTP) uses the Transmission Control Protocol (TCP) for reliable communication. TCP is one of the core protocols of the Internet Protocol Suite and provides reliable, ordered, and error-checked delivery of a stream of data between applications running on hosts communicating via an IP network. FTP relies on TCP to ensure that all data packets are delivered accurately and in the correct sequence, which is essential for the reliable transfer of files between a client and server.

References

IETF RFC 959 - File Transfer Protocol (FTP)

TCP/IP Protocol Suite Documentation

Explanation

* On Error Propagate halts execution and sends error to the client. In this scenario it's mentioned that "processing of other rows must not be affected" so Option B and C are ruled out.

* Scatter gather is used to club multiple responses together before processing. In this scenario, we need sequential processing. So option A is out of choice.

* Correct answer is For Each scope & On Error Continue scope Below requirement can be fulfilled in the below way

1) Using For Each scope , which will send each row from csv file sequentially. each row needs to be sent sequentially as requirement is to send the message in exactly the same way as it is mentioned in the csv file

2) Also other part of requirement is if any processing step for a row fails then it should log an error but should not affect other record processing . This can be achieved using On error Continue scope on these set of activities. so that error will not halt the processing. Also logger needs to be added in error handling section so that it can be logged.

* Attaching diagram for reference. Here it's try scope, but similar would be the case with For Each loop.

To ensure that non-functional requirements, such as rate limiting, are clearly communicated and enforced in the designed API definitions, the project team should use API fragments for the appropriate policy. Here's why option D is correct:

API Governance and Policies: Mulesoft's API governance framework allows the definition and enforcement of policies across APIs to ensure consistency and compliance with organizational standards. These policies can include security, rate limiting, logging, and more.

Policy Fragments: By updating API definitions with policy fragments, the team can encapsulate the non-functional requirements within the API specification itself. This approach ensures that these requirements are an integral part of the API design and are automatically applied whenever the API is deployed.

Publishing to Exchange: Publishing the updated API definitions with the policy fragments to Anypoint Exchange makes them available for reuse and ensures that all stakeholders have access to the latest, compliant API specifications.

Example of adding a rate limiting policy fragment to a RAML file:

#%RAML 1.0 title: Example API version: v1 baseUri: https://api.example.com/v1 ... /* Include the rate limiting policy fragment */ uses: rateLimitPolicy: !include rate-limit-policy.raml

The rate-limit-policy.raml fragment might define the specific rate limiting rules as per the service level agreements.

References

MuleSoft API Manager

Defining and Using API Fragments

Explanation

As the question says that data needs to be sent across multiple sftp serves , we cannot use non-repeatable streams. The non-repeatable strategy disables repeatable streams, which enables you to read an input stream only once.

You cant use in memory storage because with 0.2 vcore you will get only 1 GB of heap memory. Hence application will error out for file more than 1 GB.

Hence the correct option is file base repeatable stream

Explanation

CloudHub supports updating your applications at runtime so end users of your HTTP APIs experience zero downtime. While your application update is deploying, CloudHub keeps the old version of your application running. Your domain points to the old version of your application until the newly uploaded version is fully started. This allows you to keep servicing requests from your old application while the new version of your application is starting.

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.

AWS Transit Gateway Documentation

Anypoint VPN Configuration

In a distributed application architecture, a service mesh typically manages communication between services within the application. A service mesh provides a dedicated infrastructure layer that handles service-to-service communication, including service discovery, load balancing, failure recovery, metrics, and monitoring. This allows developers to offload these operational concerns from individual services, ensuring consistent and reliable inter-service communication.