MULESOFT MCPA-LEVEL-1 MARVELOUS REAL QUESTION

MuleSoft MCPA-Level-1 Marvelous Real Question

MuleSoft MCPA-Level-1 Marvelous Real Question

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MuleSoft MCPA-Level-1 Certification Exam is a valuable certification for IT professionals who want to showcase their expertise in designing and building integration solutions using MuleSoft's Anypoint Platform. MuleSoft Certified Platform Architect - Level 1 certification exam is comprehensive and covers a wide range of topics, making it an excellent way for IT professionals to advance their careers and increase their earning potential.

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MuleSoft Certified Platform Architect - Level 1 Sample Questions (Q32-Q37):

NEW QUESTION # 32
Refer to the exhibit.

What is a valid API in the sense of API-led connectivity and application networks?
A) Java RMI over TCP

B) Java RMI over TCP

C) CORBA over HOP

D) XML over UDP

  • A. Option A
  • B. Option C
  • C. Option D
  • D. Option B

Answer: D


NEW QUESTION # 33
Which APIs can be used with DataGraph to create a unified schema?

  • A. APIs 1, 2, 3, 4
  • B. APIs 1, 3, 5
  • C. APIs 2, 4 ,6
  • D. APIs 1, 2, s5, 6

Answer: A

Explanation:
To create a unified schema in MuleSoft's DataGraph, APIs must be exposed in a way that allows DataGraph to pull and consolidate data from these APIs into a single schema accessible to consumers. DataGraph provides a federated approach, combining multiple APIs to form a single, unified API endpoint.
In this setup:
* APIs 1, 2, 3, and 4 are suitable candidates for DataGraph because they are hosted within the Customer VPC on CloudHub and are accessible either through a Shared Load Balancer (LB) or a Dedicated Load Balancer (DLB). Both of these load balancers provide public access, which is a necessary condition for DataGraph as it must access the APIs to aggregate data.
* APIs 5 and 6 are hosted on Customer Hosted Server 2, which is explicitly marked as "Not public".
Since DataGraph requires API access through a publicly reachable endpoint to aggregate them into a unified schema, APIs 5 and 6 cannot be used with DataGraph in this configuration.
* APIs 3 and 4 on Customer Hosted Server 1 appear accessible through a Shared LB, implying public accessibility that meets DataGraph's requirements.
By combining APIs 1, 2, 3, and 4 within DataGraph, you can create a unified schema that enables clients to query data seamlessly from all these APIs as if it were from a single source.
This setup allows for efficient data retrieval and can simplify API consumption by reducing the need to call multiple APIs individually, thus optimizing performance and developer experience.
ReferencesFor more detailed information on setting up and managing unified schemas in DataGraph, refer to the DataWeave documentation and MuleSoft DataGraph resources which provide in-depth guidelines on schema aggregation and API federation.


NEW QUESTION # 34
What correctly characterizes unit tests of Mule applications?

  • A. They are typically written using MUnit to run in an embedded Mule runtime that does not require external connectivity
  • B. They must be run in a unit testing environment with dedicated Mule runtimes for the environment
  • C. They test the validity of input and output of source and target systems
  • D. They must be triggered by an external client tool or event source

Answer: A

Explanation:
They are typically written using MUnit to run in an embedded Mule runtime that does not require external connectivity.
*****************************************
Below TWO are characteristics of Integration Tests but NOT unit tests:
>> They test the validity of input and output of source and target systems.
>> They must be triggered by an external client tool or event source.
It is NOT TRUE that Unit Tests must be run in a unit testing environment with dedicated Mule runtimes for the environment.
MuleSoft offers MUnit for writing Unit Tests and they run in an embedded Mule Runtime without needing any separate/ dedicated Runtimes to execute them. They also do NOT need any external connectivity as MUnit supports mocking via stubs.
https://dzone.com/articles/munit-framework


NEW QUESTION # 35
What CANNOT be effectively enforced using an API policy in Anypoint Platform?

  • A. Guarding against Denial of Service attacks
  • B. Backend system overloading
  • C. Logging HTTP requests and responses
  • D. Maintaining tamper-proof credentials between APIs

Answer: C


NEW QUESTION # 36
When could the API data model of a System API reasonably mimic the data model exposed by the corresponding backend system, with minimal improvements over the backend system's data model?

  • A. When the System API can be assigned to a bounded context with a corresponding data model
  • B. When the corresponding backend system is expected to be replaced in the near future
  • C. When a pragmatic approach with only limited isolation from the backend system is deemed appropriate
  • D. When there is an existing Enterprise Data Model widely used across the organization

Answer: C

Explanation:
When a pragmatic approach with only limited isolation from the backend system is deemed appropriate.
*****************************************
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 systemand 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


NEW QUESTION # 37
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