Pass the MuleSoft Certified Platform Architect MCPA-Level-1 Questions and answers with ExamsMirror

Explanation

Correct Answer: The API consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation

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Terminology:

>> API Client - It is a piece of code or program the is written to invoke an API

>> API Consumer - An owner/entity who owns the API Client. API Consumers write API clients.

>> API - The provider of the API functionality. Typically an API Instance on API Manager where they are managed and operated.

>> API Implementation - The actual piece of code written by API provider where the functionality of the API is implemented. Typically, these are Mule Applications running on Runtime Manager.

For an organization starting with API-led connectivity to integrate a siloed back-end system with a new CRM, the following approach aligns with best practices and MuleSoft’s Center for Enablement (C4E) guidance:

API-led Connectivity: This model organizes APIs into distinct layers (System, Process, and Experience) to improve reusability, modularity, and manageability.

System APIs are used to expose and unlock data from core systems (such as back-end applications or databases).

Process APIs orchestrate data across multiple systems and transform it as needed.

Experience APIs format the data specifically for consumption by applications or devices, such as the CRM in this case.

Step to Support Application Network:

Create a System API for the back-end system. This API should expose the necessary data to support integration with the CRM.

By creating a System API with a RESTful interface, data can be accessed in a standardized way, making it easier to integrate with other systems and supporting future scalability.

Why Option D is Correct:

Creating a System API aligns with the principle of API-led connectivity, ensuring that data is exposed in a reusable manner. This API can then be orchestrated by Process APIs as needed to meet CRM requirements and can easily be extended to other applications.

Explanation of Incorrect Options:

Option A (creating a business process model) does not directly enable connectivity or expose back-end data through APIs.

Option B is unnecessary at this stage; assessing CRM capabilities like OAuth 2.0 support is not directly related to creating the application network via System APIs.

Option C contradicts API-led best practices by suggesting a point-to-point integration, which API-led connectivity seeks to avoid due to its lack of flexibility and scalability.

ReferencesRefer to MuleSoft’s API-led Connectivity resources for a detailed framework on building scalable integration layers using System, Process, and Experience APIs​​.

Explanation

Correct Answer: The SSL certificates used by the API implementation to expose HTTPS endpoints

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>> The assignment of each HTTP request to a particular CloudHub worker is taken care by Anypoint Platform itself. We need not manage it explicitly in the API implementation and in fact we CANNOT manage it in the API implementation.

>> The logging configuration that enables log entries to be visible in Runtime Manager is ALWAYS managed in the API implementation and NOT just for SLB. So this is not something we do EXCLUSIVELY when using SLB.

>> We DO NOT manage the number of DNS entries allocated to the API implementation inside the code. Anypoint Platform takes care of this.

It is the SSL certificates used by the API implementation to expose HTTPS endpoints that is to be managed EXCLUSIVELY by the API implementation. Anypoint Platform does NOT do this when using SLBs.

Explanation

Correct Answer: When the response time of API invocations exceeds a threshold

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>> Alerts can be setup for all the given options using the default Anypoint Platform functionality

>> However, the question insists on an alert whose conditions depend on the end-to-end request processing of the API implementation.

>> Alert w.r.t "Response Times" is the only one which requires end-to-end request processing of API implementation in order to determine if the threshold is exceeded or not.

Understanding Idempotency:

Idempotency is a concept in APIs where an operation can be performed multiple times without changing the result beyond the initial application. This is particularly important for operations that may be repeated due to network retries or client errors.

When to Consider Idempotency:

Idempotency should be taken into account when there is a risk of duplicate processing due to multiple requests being sent (e.g., retries or errors). This ensures that repeated requests do not result in unintended side effects, such as creating multiple records or processing the same transaction more than once.

Evaluating the Options:

Option A: While locked entities may need special handling, this is not directly related to idempotency.

Option B: Storing results for future responses could be useful but does not relate to idempotent operations.

Option C: Concurrent requests for the same entity might require handling for conflicts, but this scenario is better suited for transaction management or concurrency control.

Option D (Correct Answer): Preventing duplicate processing from multiple requests is a key reason to implement idempotency, ensuring that repeat requests have no adverse effects.

Conclusion:

Option D is the correct answer as idempotency is specifically used to handle scenarios where duplicate requests might be sent, preventing unintended processing.

Refer to MuleSoft's documentation on best practices for idempotency in API design for more details.

In the API-led connectivity approach, each layer (System, Process, and Experience) has a distinct purpose:

System APIs: These APIs connect directly to backend systems to expose and unlock data in a standardized way.

Process APIs: These are responsible for orchestrating and processing data across different systems, combining information where needed.

Experience APIs: These are designed for specific user interfaces or applications, often transforming data formats to fit the needs of each consumer application.

Why Option A is Correct:

Process APIs are designed to combine data from multiple systems, which aligns with the function of aggregating policy information from both the life and general insurance systems. This aggregation logic would ideally reside in the Process layer, separating data retrieval from data orchestration.

Moving this functionality to the Process layer enables reusability and modularity, as other Experience APIs or services could also leverage the combined policy data if needed.

Explanation of Incorrect Options:

Option B (Presenting the SOAP-based response) would be managed by the Experience layer, as this layer adapts data formats for specific interfaces.

Option C (Authenticating and maintaining backend connections) would typically be handled within the System layer, where backend integration and security handling occurs.

Option D (Querying data) is the function of System APIs, which access the backend systems directly and expose the raw data without additional processing.

ReferencesFor further details on API-led architecture and the roles of each layer, refer to MuleSoft’s documentation on API-led connectivity and API layers​​.

Explanation

Correct Answer: Create reusable assets, Make them discoverable so that LOB teams can self-serve and browse the APIs, Get active feedback and usage metrics.

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Diagram, arrow Description automatically generated

Explanation

Correct Answer: Spike control

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>> First things first, HTTP Caching policy is for purposes different than avoiding the backend system from overloading. So this is OUT.

>> Rate Limiting and Throttling/ Spike Control policies are designed to limit API access, but have different intentions.

>> Rate limiting protects an API by applying a hard limit on its access.

>> Throttling/ Spike Control shapes API access by smoothing spikes in traffic.

That is why, Spike Control is the right option.

When a Basic Authentication policy is applied to an API on CloudHub but clients can still access the API without authentication, the likely cause is a missing Autodiscovery element. Here’s how this affects API security:

Autodiscovery in MuleSoft:

The Autodiscovery element is essential for linking an API implementation deployed in CloudHub with its API instance defined in API Manager. This connection allows the policies applied in API Manager, such as Basic Authentication, to be enforced on the deployed API.

Why Option B is Correct:

Without Autodiscovery, the deployed application does not "know" about the policies configured in API Manager, resulting in unrestricted access. Adding Autodiscovery enables the API to enforce the policies correctly.

Explanation of Incorrect Options:

Option A (incorrect Exchange version) would not cause bypassing of security policies.

Option C (missing client applications) does not impact authentication policy enforcement.

Option D (worker restart) is irrelevant to policy enforcement.

ReferencesRefer to MuleSoft documentation on Autodiscovery configuration and linking API Manager policies for additional information on setting up secure API policies​.

Explanation

Correct Answer: Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment

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There is one important consideration to be noted in the question which is - System API in DR environment provides only 20% of the rate limiting offered by the primary environment. So, comparitively, very less calls will be allowed into the DR environment API opposed to its primary environment. With this in mind, lets analyse what is the right and best fault-tolerant invocation strategy.

1. Invoking both the system APIs in parallel is definitely NOT a feasible approach because of the 20% limitation we have on DR environment. Calling in parallel every time would easily and quickly exhaust the rate limits on DR environment and may not give chance to genuine intermittent error scenarios to let in during the time of need.

2. Another option given is suggesting to add timeout and retry logic to process API while invoking primary environment's system API. This is good so far. However, when all retries failed, the option is suggesting to invoke the copy of process API on DR environment which is not right or recommended. Only system API is the one to be considered for fallback and not the whole process API. Process APIs usually have lot of heavy orchestration calling many other APIs which we do not want to repeat again by calling DR's process API. So this option is NOT right.

3. One more option given is suggesting to add the retry (no timeout) logic to process API to directly retry on DR environment's system API instead of retrying the primary environment system API first. This is not at all a proper fallback. A proper fallback should occur only after all retries are performed and exhausted on Primary environment first. But here, the option is suggesting to directly retry fallback API on first failure itself without trying main API. So, this option is NOT right too.

This leaves us one option which is right and best fit.

- Invoke the system API deployed to the primary environment

- Add Timeout and Retry logic on it in process API

- If it fails even after all retries, then invoke the system API deployed to the DR environment.