Salesforce Updated MuleSoft-Platform-Architect-I Exam Questions and Answers by naya

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

Explanation

Correct Answer: The API policy is defined in API Manager for a specific API instance, and then ONLY applied to the specific API instance.

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>> Once our API specifications are ready and published to Exchange, we need to visit API Manager and register an API instance for each API.

>> API Manager is the place where management of API aspects takes place like addressing NFRs by enforcing policies on them.

>> We can create multiple instances for a same API and manage them differently for different purposes.

>> One instance can have a set of API policies applied and another instance of same API can have different set of policies applied for some other purpose.

>> These APIs and their instances are defined PER environment basis. So, one need to manage them seperately in each environment.

>> We can ensure that same configuration of API instances (SLAs, Policies etc..) gets promoted when promoting to higher environments using platform feature. But this is optional only. Still one can change them per environment basis if they have to.

>> Runtime Manager is the place to manage API Implementations and their Mule Runtimes but NOT APIs itself. Though API policies gets executed in Mule Runtimes, We CANNOT enforce API policies in Runtime Manager. We would need to do that via API Manager only for a cherry picked instance in an environment.

So, based on these facts, right statement in the given choices is - "The API policy is defined in API Manager for a specific API instance, and then ONLY applied to the specific API instance".

Scenario Analysis:

The eCommerce company’s Product Details feature requires low response time and consistent data for a feature where data rarely changes (only once or twice a year).

The database response time is slow due to high volume, so querying the database directly on each request would lead to poor performance and higher response times.

Optimal Solution Requirements:

Low Response Time: Data retrieval should be fast and not depend on database performance.

Fault Tolerance and Data Consistency: Cached or stored data should be consistent and resilient in case of database unavailability, as the product details data changes infrequently.

Evaluating the Options:

Option A: Using a Cache scope would temporarily store the product details in memory, which could improve performance but might not be suitable for infrequent updates (only twice a year), as cache expiration policies typically require shorter durations.

Option B: Storing product details in Anypoint MQ and then retrieving it through a subscriber is not suitable for this use case. Anypoint MQ is better for messaging rather than as a data storage mechanism.

Option C (Correct Answer): Using an object store to store and retrieve product details is ideal. Object stores in MuleSoft are designed for persistent storage of key-value pairs, which allows storing data retrieved from the database initially. This provides quick, consistent access without querying the database on every request, aligning with requirements for low response time, fault tolerance, and data consistency.

Option D: Selecting data directly from the database for each request would not meet the performance requirement due to known slow response times from the database.

Conclusion:

Option C is the best answer, as using an object store allows caching the infrequently updated product details. This approach reduces the dependency on the database, significantly improving response time and ensuring consistent data.

Refer to MuleSoft documentation on Object Store v2 and best practices for data caching to implement this solution effectively.

Explanation

Correct Answer: Bundle properties files for each environment into the Mule API implementation's deployable archive, then promote the Mule API implementation to the Production environment using Anypoint CLI or the Anypoint Platform REST APIs

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>> Anypoint Exchange is for asset discovery and documentation. It has got no provision to modify the properties of Mule API implementations at all.

>> API Manager is for managing API instances, their contracts, policies and SLAs. It has also got no provision to modify the properties of API implementations.

>> API policies are to address Non-functional requirements of APIs and has again got no provision to modify the properties of API implementations.

So, the right way and recommended way to do this as part of development practice is to bundle properties files for each environment into the Mule API implementation and just point and refer to respective file per environment.