MuleSoft MCPA-Level-1 - MuleSoft Certified Platform Architect - Level 1

When defining data models for System APIs without an established Enterprise Data Model, MuleSoft recommends mirroring the back-end systems' data types to achieve quick and effective integration without adding complexity. This approach has several benefits:

Alignment with Backend Systems:

Mirroring data types ensures consistency with backend data sources, which simplifies integration, reduces mapping requirements, and minimizes potential data transformation issues.

Flexibility for Future Enhancements:

By retaining close alignment with backend data structures, System APIs can evolve to support an Enterprise Data Model in the future without immediate restructuring.

Explanation of Incorrect Options:

Option A (exposing misspellings) is not recommended as System APIs should still ensure a professional and coherent interface.

Option C (custom naming) complicates the API structure without adding immediate value in the absence of a clear data model.

Option D (exposing all fields) is unnecessary and can reduce performance and add complexity.

ReferencesRefer to MuleSoft best practices for data modeling in System APIs for additional information on mirroring backend systems​.

To achieve the goal of exposing financial data to a new mobile application while following MuleSoft’s best practices, the company should follow an API-led connectivity approach. This approach ensures minimal disruption to existing clients, maximizes reusability, and respects the separation of concerns across API layers.

Explanation of Solution:

Experience APIs for Client-Specific Requirements:

Create two new Experience APIs (EAPI-1 and EAPI-2) for the mobile application, tailored to meet the specific data and format requirements of the mobile application. These APIs encapsulate the client-specific needs and provide a custom interface without impacting other clients.

Process API Layer for Data Transformation:

By adding Mobile PAPI-2, we allow the mobile application to access the required subset of data, formatted according to the mobile application’s requirements. This approach ensures that data transformation and aggregation are handled in the Process layer, maintaining consistency and reusability across different applications.

Reuse of System APIs:

Both the new Mobile PAPI-2 and existing PAPI-1 access data from System APIs (SAPI-1 and SAPI-2), which continue to expose data from each legacy system in a consistent, reusable manner. This avoids duplicating logic and ensures that data access remains centralized and manageable.

Why Option A is Correct:

Option A aligns with MuleSoft’s best practices by isolating client-specific requirements in the Experience layer, utilizing Process APIs for data orchestration and transformation, and maintaining reusable System APIs for backend access.

This approach also ensures that the current API clients are not impacted, as new clients (e.g., the mobile app) interact with newly defined Experience APIs without modifying the existing API setup.

Explanation of Incorrect Options:

Option B: This option seems similar but lacks clarity on the separation of mobile-specific requirements and does not explicitly mention data transformation, which is essential in this scenario.

Option C: Creating a single mobile Experience API that exposes a subset of PAPI endpoints directly adds unnecessary complexity and may violate the separation of concerns, as transformation logic should not be in the Experience layer.

Option D: Deploying a new PAPI and using an API Proxy to redirect existing endpoints would add unnecessary complexity, disrupt the current API clients, and increase maintenance efforts.

ReferencesFor additional guidance, refer to MuleSoft documentation on API-led connectivity best practices and best practices for structuring Experience, Process, and System APIs​​.

Explanation

Correct Answer: Create a bounded-context model for the system layer to closely match the backend data model, and add an anti-corruption layer to let the different bounded contexts cooperate across the system and process layers

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>> Canonical models are not an option here as the organization has already put in efforts and created bounded-context models for Experience and Process APIs.

>> Anti-corruption layers for ALL APIs is unnecessary and invalid because it is mentioned that experience and process APIs share same bounded-context model. It is just the System layer APIs that need to choose their approach now.

>> So, having an anti-corruption layer just between the process and system layers will work well. Also to speed up the approach, system APIs can mimic the backend system data model.

Explanation

Correct Answer: A higher number of discoverable API-related assets in the application network.

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>> We do NOT get faster response times in fine-grained approach when compared to coarse-grained approach.

>> In fact, we get faster response times from a network having coarse-grained APIs compared to a network having fine-grained APIs model. The reasons are below.

Fine-grained approach:

1. will have more APIs compared to coarse-grained

2. So, more orchestration needs to be done to achieve a functionality in business process.

3. Which means, lots of API calls to be made. So, more connections will needs to be established. So, obviously more hops, more network i/o, more number of integration points compared to coarse-grained approach where fewer APIs with bulk functionality embedded in them.

4. That is why, because of all these extra hops and added latencies, fine-grained approach will have bit more response times compared to coarse-grained.

5. Not only added latencies and connections, there will be more resources used up in fine-grained approach due to more number of APIs.

That's why, fine-grained APIs are good in a way to expose more number of resuable assets in your network and make them discoverable. However, needs more maintenance, taking care of integration points, connections, resources with a little compromise w.r.t network hops and response times.

For a European company with requirements such as zero-downtime redeployment, deployment to multiple runtime versions, secure and fast performance, and the use of Anypoint MQ without additional network configuration, CloudHub is the best choice for the following reasons:

Zero-Downtime Redeployment: CloudHub supports zero-downtime deployment, which allows seamless redeployment of applications without impacting availability.

Support for Multiple Runtime Versions: CloudHub allows deploying applications across different Mule runtime versions, giving flexibility to test and migrate applications as needed.

Integrated Anypoint MQ: Anypoint MQ, which is fully integrated with CloudHub, provides reliable messaging across applications. Choosing CloudHub removes the need for additional network configurations, as Anypoint MQ can be directly accessed in this hosted environment.

Security and Performance: CloudHub offers secure networking, automatic scaling, and optimized performance without requiring a complex setup. This is managed by MuleSoft’s infrastructure, meeting the speed and security requirements with minimal overhead.

Explanation of Incorrect Options:

Option A and D (Runtime Fabric on VMs or Self-Managed Kubernetes): While Runtime Fabric offers flexibility, it requires more complex network and infrastructure configurations, which is not ideal if the company seeks simplicity.

Option B (Customer-hosted): This would require additional network and security configuration, which does not align with the requirement of minimizing setup complexity.

ReferencesFor more information on CloudHub’s capabilities regarding zero-downtime deployments and integration with Anypoint MQ, refer to MuleSoft documentation on CloudHub​​.

Explanation

Correct Answer: Traffic between Mule applications deployed to an Anypoint VPC and on-premises systems can stay within a private network

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>> The private IP address range of an Anypoint VPC is NOT automatically chosen by CloudHub. It is chosen by us at the time of creating VPC using thr CIDR blocks.

CIDR Block: The size of the Anypoint VPC in Classless Inter-Domain Routing (CIDR) notation.

For example, if you set it to 10.111.0.0/24, the Anypoint VPC is granted 256 IP addresses from 10.111.0.0 to 10.111.0.255.

Ideally, the CIDR Blocks you choose for the Anypoint VPC come from a private IP space, and should not overlap with any other Anypoint VPC’s CIDR Blocks, or any CIDR Blocks in use in your corporate network.

that each CloudHub environment requires a separate Anypoint VPC. Once an Anypoint VPC is created, we can choose a same VPC by multiple environments. However, it is generally a best and recommended practice to always have seperate Anypoint VPCs for Non-Prod and Prod environments.

>> We use Anypoint VPN to link the underlying AWS VPC to an on-premises (non AWS) private network. NOT VPC Peering.

In the initial meeting for establishing a Center for Enablement (C4E), it’s essential to lay the foundational vision, objectives, and guiding principles for the team. Here’s why this is crucial:

Clear Vision and Mission:

Defining the mission statement and objectives at the start ensures alignment within the organization and clarifies the C4E’s role in supporting API-led development and integration practices.

Guiding Principles:

Establishing guiding principles will help the C4E maintain consistent practices and strategies across projects. This serves as a framework for decisions and fosters shared understanding among IT leaders and stakeholders.

Explanation of Correct Answer (A):

By prioritizing the C4E’s objectives and mission, the organization builds a solid foundation, paving the way for subsequent meetings focused on technical standards, processes, and operating models.

Explanation of Incorrect Options:

Option B (API monetization) and Option C (common services best practices) are specific topics better suited for later discussions.

Option D (specifying the operating model) is an important step but typically follows the establishment of the C4E’s objectives and vision.

ReferencesFor more on C4E objectives and foundational setup, refer to MuleSoft’s documentation on establishing a C4E and the roles and mission statements recommended for such initiatives​.

Explanation

Correct Answer: Implement different system APIs named createCustomer, amendCustomer, retrieveCustomer and suspendCustomer as they are modular and has seperation of concerns

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>> It is quite normal to have a single API and different Verb + Resource combinations. However, this fits well for an Experience API or a Process API but not a best architecture style for System APIs. So, option with just one customerManagement API is not the best choice here.

>> The option with APIs in createCustomerInCRMZ format is next close choice w.r.t modularization and less maintenance but the naming of APIs is directly coupled with the legacy system. A better foreseen approach would be to name your APIs by abstracting the backend system names as it allows seamless replacement/migration of any backend system anytime. So, this is not the correct choice too.

>> createCustomer, amendCustomer, retrieveCustomer and suspendCustomer is the right approach and is the best fit compared to other options as they are both modular and same time got the names decoupled from backend system and it has covered all requirements a System API needs.

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.