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

*****************************************

>> Application Network is a disposable architecture.

>> Which means, it can be altered without disturbing entire architecture and its components.

>> It bends as per requirements or design changes but does not break

Role of Process API in API-led Connectivity:

In MuleSoft’s API-led connectivity approach, a Process API is used to coordinate, aggregate, and orchestrate data from various System APIs. It is primarily responsible for implementing business logic that spans multiple backend systems or entities, transforming and combining data as needed to support business processes.

Process APIs are not directly exposed to end-user clients; rather, they work between System APIs and Experience APIs, providing business logic and orchestration capabilities.

Evaluating the Options:

Option A: Process APIs are not typically responsible for large data dumps or data synchronization. That function would be handled by a System API or a specialized batch process.

Option B: Managing direct, secure communication between back-end systems and end-user clients is typically the role of Experience APIs rather than Process APIs.

Option C (Correct Answer): Process APIs are designed to coordinate and orchestrate calls to multiple other APIs in the network, which supports the automation of business processes.

Option D: Securing and managing communication with end-user clients is typically the role of Experience APIs, not Process APIs.

Conclusion:

Option C is the correct answer, as the main role of a Process API is to coordinate and orchestrate interactions between other APIs, enabling business processes to function seamlessly across multiple systems.

Refer to MuleSoft's API-led connectivity documentation for further explanation of the roles and responsibilities of Process APIs in an application network.

Understanding JSON Threat Protection Policies:

JSON Threat Protection policies are used to protect APIs from attacks that exploit JSON payloads, such as oversized payloads, deeply nested objects, and excessive array elements. This helps prevent Denial of Service (DoS) attacks and other malicious payload-related threats.

These policies are typically applied to safeguard APIs that are directly exposed to external clients, where the risk of receiving malicious payloads is highest.

API-led Connectivity Layers:

Experience Layer: This layer is designed to expose APIs to end-users or external API clients, often acting as the interface that interacts with users or applications.

Process Layer: This layer is used for orchestration and aggregation of data from various System APIs, typically operating within a trusted environment and not directly exposed to external clients.

System Layer: This layer provides access to backend systems and databases, often within the organization’s secure environment and not directly accessible to external clients.

Evaluating the Options:

Option A (All layers): While JSON Threat Protection can technically be applied to all layers, it is most commonly applied at the Experience layer, where APIs are exposed to external traffic and are more vulnerable to attacks.

Option B (System layer): The System layer is generally not exposed to external clients directly, so JSON Threat Protection is less critical here.

Option C (Process layer): Similar to the System layer, the Process layer is typically internal and not exposed directly to external clients, so JSON Threat Protection is less commonly applied.

Option D (Correct Answer): The Experience layer is the correct answer because it is the layer that directly interacts with external clients, making it the primary target for malicious payloads. Applying JSON Threat Protection here effectively protects the application network from external threats.

Conclusion:

Option D is the correct answer, as the Experience layer is the most common layer for applying JSON Threat Protection policies to protect against external attacks.

For further reference, consult MuleSoft's documentation on API security policies and best practices for securing APIs at the Experience layer.

In MuleSoft CloudHub, autoscaling is essential to managing application load efficiently. CloudHub supports horizontal scaling based on CPU usage, which is well-suited to applications experiencing variable demand and needing responsive resource allocation.

Autoscaling on CloudHub:

Horizontal scaling increases the number of workers in response to CPU usage thresholds, allowing the application to handle higher loads dynamically. This approach improves performance without downtime or manual intervention.

Why Option C is Correct:

Setting up autoscaling based on CPU usage aligns with MuleSoft’s best practices for scalable and responsive applications on CloudHub, particularly in an environment with fluctuating load patterns.

Option C correctly leverages CloudHub’s autoscaling features based on resource metrics, which are part of CloudHub’s managed scaling solutions.

Explanation of Incorrect Options:

Option A (based on HTTP request thresholds) and Option B (separate policies for CPU and memory) do not represent CloudHub’s recommended scaling practices.

Option D suggests vertical scaling based on response time, which is not how CloudHub handles autoscaling.

ReferencesFor more on CloudHub’s autoscaling configuration, refer to MuleSoft documentation on CloudHub autoscaling policies​.

Explanation

Correct Answer: They provide an additional layer of resilience on top of the underlying backend system, thereby insulating clients from extended failure of these systems.

*****************************************

In API-led connectivity,

>> Experience APIs - allow for innovation at the user interface level by consuming the underlying assets without being aware of how data is being extracted from backend systems.

>> Process APIs - compose data from various sources and combine them with orchestration logic to create higher level value

>> System APIs - reduce the dependency on the underlying backend systems by helping unlock data from backend systems in a reusable and consumable way.

However, they NEVER promise that they provide an additional layer of resilience on top of the underlying backend system, thereby insulating clients from extended failure of these systems.

https://dzone.com/articles/api-led-connectivity-with-mule

In the API-led connectivity approach, APIs are categorized into Experience, Process, and System layers:

Enterprise Data Model Scope:

The Enterprise Data Model (EDM) generally supports System APIs and some Process APIs by defining standard data structures used across the organization. Experience APIs, however, are tailored to specific applications or interfaces and are less likely to be served directly by the EDM, as they may require customized data representations to meet the unique needs of each user interface.

Why Option C is Correct:

The Mobile Account Management EAPI serves mobile-specific needs and often requires data formatted differently from the standardized data models. Thus, it would be outside the direct scope of the EDM and might employ custom mappings to fit mobile application requirements.

Explanation of Incorrect Options:

Option A (Customer SAPI), Option B (Customer Lookup PAPI), and Option D (Service SAPI) would typically align with the EDM as they are closer to the core data and services the EDM supports.

ReferencesFor additional guidance, review MuleSoft's best practices on API-led connectivity and data modeling​.

Understanding API-led Connectivity Layers:

In MuleSoft’s API-led connectivity approach, APIs are categorized into three layers:

Experience Layer: This layer is responsible for providing data to the end-user applications and is often customized to meet the needs of different user interfaces.

Process Layer: This layer is used to orchestrate and combine data from multiple System APIs. It acts as a mediator and business logic layer without directly interacting with the backend systems.

System Layer: This layer provides direct access to the backend systems (e.g., databases, ERPs) and is usually focused on exposing atomic data operations.

Evaluating the Architectural Constraints:

Option A: Always using a strict tiered approach by creating exactly one API per layer is not necessarily an architectural constraint of API-led connectivity. While a layered approach is recommended, it is common to have multiple APIs in each layer as needed for different functionalities.

Option B (Correct Answer): In API-led connectivity, Process APIs are generally responsible for orchestrating calls to System APIs and should not call other Process APIs. This maintains a clear separation of concerns, ensuring that Process APIs aggregate data from System APIs only and provide it to Experience APIs.

Option C: System APIs are generally designed to provide only the necessary data to meet current business requirements. Allowing them to return extra data that is not needed by Process or Experience APIs is not a best practice, as it can lead to inefficiencies.

Option D: Customizations specific to end-user applications are typically handled at the Experience Layer rather than the Process Layer, as the Experience Layer is intended to tailor the data to fit the needs of each specific client or front-end application.

Conclusion:

Option B is the correct answer as it aligns with the API-led connectivity principles. In this architectural style, Process APIs should orchestrate System APIs but should avoid interacting with other Process APIs to keep a clear separation of responsibilities across the layers.

For additional details, refer to MuleSoft documentation on API-led connectivity best practices, particularly around the roles of each layer in API orchestration and data handling.

Understanding API Autodiscovery in MuleSoft:

API Autodiscovery links an API implementation in Anypoint Platform with its configuration in API Manager. This is controlled by the API ID which is set in the API Autodiscovery element in the Mule application.

The API ID remains consistent across minor updates to the API asset version in Exchange (e.g., from 2.0.0 to 2.0.1) as long as it is the same API.

Effect of Asset Version Update on API Autodiscovery:

When the asset version is updated (e.g., from 2.0.0 to 2.0.1), the API ID remains the same. Therefore, no changes are needed in the Autodiscovery configuration within the Mule application. The Autodiscovery will continue to link the API implementation to the latest version in API Manager.

Evaluating the Options:

Option A: Incorrect, as the API ID does not automatically change with minor asset version updates.

Option B: Incorrect, as the API ID remains the same, so no update is needed in the API implementation.

Option C (Correct Answer): The API ID does not change, so no changes are necessary in the API implementation for the new asset version.

Option D: Incorrect, as there is no need to update the API implementation in the Autodiscovery global element for minor version changes.

Conclusion:

Option C is the correct answer, as the API ID remains unchanged with minor version updates, and no changes are needed in the API Autodiscovery configuration.

Refer to MuleSoft documentation on API Autodiscovery and version management for more details.