QUESTION: 37

An API has been updated in Anypoint Exchange by its API producer from version 3.1.1 to 3.2.0 following accepted semantic versioning practices and the changes have been communicated via the API's public portal.
The API endpoint does NOT change in the new version.
How should the developer of an API client respond to this change?

The update should be identified as a project risk and full regression testing of the functionality that uses this API should be run
The API producer should be contacted to understand the change to existing functionality
The API producer should be requested to run the old version in parallel with the new one
The API client code ONLY needs to be changed if it needs to take advantage of new features

Answer(s): D

Reference:

https://docs.mulesoft.com/exchange/to-change-raml-version

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QUESTION: 38

Mule applications that implement a number of REST APIs are deployed to their own subnet that is inaccessible from outside the organization.
External business-partners need to access these APIs, which are only allowed to be invoked from a separate subnet dedicated to partners - called Partner-subnet. This subnet is accessible from the public internet, which allows these external partners to reach it.

Anypoint Platform and Mule runtimes are already deployed in Partner-subnet. These Mule runtimes can already access the APIs.
What is the most resource-efficient solution to comply with these requirements, while having the least impact on other applications that are currently using the APIs?

Implement (or generate) an API proxy Mule application for each of the APIs, then deploy the API proxies to the Mule runtimes
Redeploy the API implementations to the same servers running the Mule runtimes
Add an additional endpoint to each API for partner-enablement consumption
Duplicate the APIs as Mule applications, then deploy them to the Mule runtimes

Answer(s): A

Explanation:

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QUESTION: 39

When could the API data model of a System API reasonably mimic the data model exposed by the corresponding backend system, with minimal improvements over the backend system's data model?

When there is an existing Enterprise Data Model widely used across the organization
When the System API can be assigned to a bounded context with a corresponding data model
When a pragmatic approach with only limited isolation from the backend system is deemed appropriate
When the corresponding backend system is expected to be replaced in the near future

Answer(s): C

Explanation:

Correct Answer: When a pragmatic approach with only limited isolation from the backend system is deemed appropriate.
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General guidance w.r.t choosing Data Models:
>> If an Enterprise Data Model is in use then the API data model of System APIs should make use of data types from that Enterprise Data Model and the corresponding API implementation should translate between these data types from the Enterprise Data Model and the native data model of the backend system.
>> If no Enterprise Data Model is in use then each System API should be assigned to a Bounded Context, the API data model of System APIs should make use of data types from the corresponding Bounded Context Data Model and the corresponding API implementation should translate between these data types from the Bounded Context Data Model and the native data model of the backend system. In this scenario, the data types in the Bounded Context Data Model are defined purely in terms of their business characteristics and are typically not related to the native data model of the backend system. In other words, the translation effort may be significant. >> If no Enterprise Data Model is in use, and the definition of a clean Bounded Context Data Model is considered too much effort, then the API data model of System APIs should make use of data types that approximately mirror those from the backend system, same semantics and naming as backend system, lightly sanitized, expose all fields needed for the given System API's functionality, but not significantly more and making good use of REST conventions. The latter approach, i.e., exposing in System APIs an API data model that basically mirrors that of the backend system, does not provide satisfactory isolation from backend systems through the System API tier on its own. In particular, it will typically not be possible to "swap out" a backend system without significantly changing all System APIs in front of that backend system and therefore the API implementations of all Process APIs that depend on those System APIs! This is so because it is not desirable to prolong the life of a previous backend system's data model in the form of the API data model of System APIs that now front a new backend system. The API data models of System APIs following this approach must therefore change when the backend system is replaced.
On the other hand:
>> It is a very pragmatic approach that adds comparatively little overhead over accessing the backend system directly
>> Isolates API clients from intricacies of the backend system outside the data model (protocol, authentication, connection pooling, network address, ...)
>> Allows the usual API policies to be applied to System APIs
>> Makes the API data model for interacting with the backend system explicit and visible, by exposing it in the RAML definitions of the System APIs
>> Further isolation from the backend system data model does occur in the API implementations of the Process API tier

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QUESTION: 40

Refer to the exhibit.

An organization uses one specific CloudHub (AWS) region for all CloudHub deployments. How are CloudHub workers assigned to availability zones (AZs) when the organization's Mule applications are deployed to CloudHub in that region?

Workers belonging to a given environment are assigned to the same AZ within that region
AZs are selected as part of the Mule application's deployment configuration
Workers are randomly distributed across available AZs within that region
An AZ is randomly selected for a Mule application, and all the Mule application's CloudHub workers are assigned to that one AZ

Answer(s): D

Explanation:

Correct Answer: Workers are randomly distributed across available AZs within that region.
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>> Currently, we only have control to choose which AWS Region to choose but there is no control at all using any configurations or deployment options to decide what Availability Zone (AZ) to assign to what worker.
>> There are NO fixed or implicit rules on platform too w.r.t assignment of AZ to workers based on environment or application.
>> They are completely assigned in random. However, cloudhub definitely ensures that HA is achieved by assigning the workers to more than on AZ so that all workers are not assigned to same AZ for same application.

Reference:

https://help.mulesoft.com/s/question/0D52T000051rqDj/one-cloudhub-aws-region-how- cloudhub-workers-are-assigned-to-availability-zones-azs-

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QUESTION: 37

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QUESTION: 40

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