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Salesforce MuleSoft MuleSoft-Integration-Architect-I Updated Exam

Salesforce Certified MuleSoft Integration Architect 1 (SU24) Exam Questions and Answers

Question 29

An organization has decided on a cloudhub migration strategy that aims to minimize the organizations own IT resources. Currently, the organizational has all of its Mule applications running on its own premises and uses an premises load balancer that exposes all APIs under the base URL

As part of the migration strategy, the organization plans to migrate all of its Mule applications and load balancer to cloudhub

What is the most straight-forward and cost effective approach to the Mule applications deployment and load balancing that preserves the public URLs?

Options:

A.

Deploy the Mule applications to Cloudhub

Update the CNAME record for an api.acme.com in the organizations DNS server pointing to the A record of a cloudhub dedicated load balancer(DLB)

Apply mapping rules in the DLB to map URLs to their corresponding Mule applications

B.

For each migrated Mule application, deploy an API proxy Mule application to Cloudhub with all applications under the control of a dedicated load balancer(CLB)

Update the CNAME record for api.acme.com in the organization DNS server pointing to the A record of a cloudhub dedicated load balancer(DLB)

Apply mapping rules in the DLB to map each API proxy application to its corresponding Mule applications

C.

Deploy the Mule applications to Cloudhub

Create CNAME record for api.acme.com in the Cloudhub Shared load balancer (SLB) pointing to the A record of the on-premise load balancer

Apply mapping rules in the SLB to map URLs to their corresponding Mule applications

D.

Deploy the Mule applications to Cloudhub

Update the CNAME record for api.acme.com in the organization DNS server pointing to the A record of the cloudhub shared load balancer(SLB)

Apply mapping rules in the SLB to map URLs to their corresponding Mule applications.

Question 30

A project team is working on an API implementation using the RAML definition as a starting point. The team has updated the definition to include new operations and has published a new version to exchange. Meanwhile another team is working on a mule application consuming the same API implementation.

During the development what has to be performed by the mule application team to take advantage of the newly added operations?

Options:

A.

Scaffold the client application with the new definition

B.

Scaffold API implementation application with the new definition

C.

Update the REST connector from exchange in the client application

D.

Update the API connector in the API implementation and publish to exchange

Question 31

Insurance organization is planning to deploy Mule application in MuleSoft Hosted runtime plane. As a part of requirement , application should be scalable . highly available. It also has regulatory requirement which demands logs to be retained for at least 2 years. As an Integration Architect what step you will recommend in order to achieve this?

Options:

A.

It is not possible to store logs for 2 years in CloudHub deployment. External log management system is required.

B.

When deploying an application to CloudHub , logs retention period should be selected as 2 years

C.

When deploying an application to CloudHub, worker size should be sufficient to store 2 years data

D.

Logging strategy should be configured accordingly in log4j file deployed with the application.

Question 32

Refer to the exhibit.

One of the backend systems invoked by an API implementation enforces rate limits on the number of requests a particular client can make. Both the backend system and the API implementation are deployed to several non-production environments in addition to production.

Rate limiting of the backend system applies to all non-production environments. The production environment, however, does NOT have any rate limiting.

What is the most effective approach to conduct performance tests of the API implementation in a staging (non-production) environment?

Options:

A.

Create a mocking service that replicates the backend system's production performance characteristics. Then configure the API implementation to use the mocking service and conduct the performance tests

B.

Use MUnit to simulate standard responses from the backend system then conduct performance tests to identify other bottlenecks in the system

C.

Include logic within the API implementation that bypasses invocations of the backend system in a performance test situation. Instead invoking local stubs that replicate typical backend system responses then conduct performance tests using this API Implementation

D.

Conduct scaled-down performance tests in the staging environment against the rate limited backend system then upscale performance results to full production scale