Mule-Arch-201 Zertifizierungsfragen, Salesforce Mule-Arch-201 PrüfungFragen

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Salesforce Mule-Arch-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Meeting API Quality Goals	8%	- Resilience & Reliability Patterns - API Performance Optimization - Unit & Integration Testing
Topic 2: Understanding the MuleSoft Platform & Application Networks	11%	- C4E (Center for Enablement) Definition - MuleSoft Anypoint Platform Core Concepts - Application Network Fundamentals
Topic 3: Deploying API Implementations to CloudHub	11%	- CloudHub 2.0 & Runtime Fabric - CloudHub Architecture - Deployment Strategies
Topic 4: Architecting and Deploying API Implementations	11%	- Mule Runtime Architecture - High Availability (HA) Design - Disaster Recovery (DR) Strategies
Topic 5: Managing APIs	12%	- API Lifecycle Management - API Security (Policies, SLAs) - API Versioning
Topic 6: Monitoring and Analyzing Application Networks	8%	- Alerting & Auditing - Anypoint Monitoring Tools - Analytics & Business Insights
Topic 7: Applying Integration Patterns	11%	- Event-Driven Architecture (EDA) - Batch Processing - Integration Scenarios & Patterns
Topic 8: Designing and Sharing APIs	11%	- Anypoint Exchange for Sharing Assets - API Design Best Practices - API-Led Connectivity Approach
Topic 9: Establishing Organizational and Platform Foundations	17%	- Governance and Compliance Framework - IT Delivery & C4E Operating Model - Platform Foundation Setup

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Salesforce Certified MuleSoft Platform Architect Mule-Arch-201 Prüfungsfragen mit Lösungen (Q45-Q50):

45. Frage
4A developer for a transportation organization is implementing exactly one processing functionality in a Reservation Mule application to process and store passenger records. This Reservation application will be deployed to multiple CloudHub workers/replicas. It is possible that several external systems could send duplicate passenger records to the Reservation application.
An appropriate storage mechanism must be selected to help the Reservation application process each passenger record exactly once as much as possible. The selected storage mechanism must be shared by all the CloudHub workers/replicas in order to synchronize the state information to assist attempting exactly once processing of each passenger record by the deployed Reservation Mule application.
Which type of simple storage mechanism in Anypoint Platform allows the Reservation Mule application to update and share data between the CloudHub workers/replicas exactly once, with minimal development effort?

A. Runtime Fabric Object Store
B. Non-persistent Object Store
C. Persistent Object Store
D. In-memory Mule Object Store

Antwort: C

Begründung:
Processing Requirements and Storage Mechanism:
The Reservation Mule application will be deployed to multiple CloudHub workers/replicas, meaning that each worker must share state information to handle records exactly once. This requires a shared storage mechanism where state can be stored and accessed by multiple instances to avoid duplicate processing of the same records.
A Persistent Object Store in Anypoint Platform can be used to store records in a way that is accessible across multiple workers, providing a reliable mechanism for "exactly once" processing.
Evaluating the Options:
Option A (Correct Answer): A Persistent Object Store is designed to retain data across different application instances and can be shared by all workers on CloudHub. It helps achieve idempotency by ensuring that a record is processed exactly once.
Option B: Runtime Fabric Object Store is used for applications deployed in Anypoint Runtime Fabric, not CloudHub. This option would not be compatible with the CloudHub deployment.
Option C: A Non-persistent Object Store does not retain data across application restarts or different instances, making it unsuitable for the requirement of synchronized storage for exactly-once processing.
Option D: An In-memory Mule Object Store is local to each worker and is not shared across instances, so it does not meet the requirement for a shared storage mechanism accessible to all CloudHub workers.
Conclusion:
Option A is the correct answer, as a Persistent Object Store allows data sharing across multiple CloudHub workers, enabling them to synchronize and achieve "exactly once" processing of passenger records with minimal development effort.
Refer to MuleSoft's documentation on Object Store configurations and usage for best practices on handling state across distributed instances.

46. Frage
An organization has created an API-led architecture that uses various API layers to integrate mobile clients with a backend system. The backend system consists of a number of specialized components and can be accessed via a REST API. The process and experience APIs share the same bounded-context model that is different from the backend data model. What additional canonical models, bounded-context models, or anti-corruption layers are best added to this architecture to help process data consumed from the backend system?

A. Create a canonical model that combines the backend and API-led models to simplify and unify data models, and minimize data transformations.
B. Create an anti-corruption layer for every API to perform transformation for every data model to match each other, and let data simply travel between APIs to avoid the complexity and overhead of building canonical models
C. 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
D. Create a bounded-context model for every layer and overlap them when the boundary contexts overlap, letting API developers know about the differences between upstream and downstream data models

Antwort: C

Begründung:
Correct Answe r: 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
*****************************************
>> 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.

47. Frage
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 APIs public portal. The API endpoint does NOT change in the new version. How should the developer of an API client respond to this change?

A. The API producer should be requested to run the old version in parallel with the new one
B. The API clients need to update the code on their side and need to do full regression
C. The API producer should be contacted to understand the change to existing functionality
D. The API client code only needs to be changed if it needs to take advantage of the new features

Antwort: D

48. Frage
What is a typical result of using a fine-grained rather than a coarse-grained API deployment model to implement a given business process?

A. A decrease in the number of connections within the application network supporting the business process
B. A better response time for the end user as a result of the APIs being smaller in scope and complexity
C. A higher number of discoverable API-related assets in the application network
D. An overall tower usage of resources because each fine-grained API consumes less resources

Antwort: C

Begründung:
Correct Answe r: A higher number of discoverable API-related assets in the application network.
*****************************************
>> 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.

49. Frage
A developer from the Central IT team has created an initial version of the RAML definition in Design Center for an OAuth 2.0-protected System API and published it to Exchange. Another developer from LoB IT discovered the System API in Exchange and would like to leverage it in the Process API.
What is the MuleSoft-recommended approach for Process API to invoke the System API?

A. The Process API needs to import an CAuth 2.0 module from Exchange first and update it with OAuth 2.0 credentials before the System API can be invoked
B. The Process APL uses the REST Connect Connector autogenerated in Exchange for the System API
C. The Process API manually updates the Process API POM file to include the System API as a dependency
D. The Process API uses property YAML files to store the System API URLs and uses the HTTP Request Connector to invoke the Systerm API

Antwort: B

Begründung:
In MuleSoft's ecosystem, when a Process API needs to consume a System API (published to Exchange and protected by OAuth 2.0), the recommended approach is to utilize the REST Connect Connector. Here's how it aligns with best practices:
Automated Connector Generation:
When a RAML or OAS specification is published in Exchange, MuleSoft automatically generates a REST Connect Connector for that API. This connector simplifies integration as it abstracts the complexity of making HTTP requests and handling OAuth authentication.
Streamlined Integration:
The Process API can import this generated connector from Exchange and configure OAuth credentials, streamlining secure access to the System API without manual HTTP setup.
Why Option C is Correct:
Using the REST Connect Connector directly leverages MuleSoft's automated tooling, minimizing manual configurations and ensuring a more maintainable integration.
of Incorrect Options:
Option A (importing an OAuth module) is unnecessary; OAuth is handled within the connector's configuration.
Option B (property YAML files with HTTP requests) involves manual setup, which is more error-prone and not recommended.
Option D (manually updating POM file) does not directly aid in invoking an API through Exchange.
Reference
For more information on using REST Connect Connectors and OAuth integration in MuleSoft, refer to the MuleSoft documentation on API Management and Connectors.

50. Frage
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