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| Section | Objectives |
|---|---|
| Anypoint Platform Architecture | - Deployment models (CloudHub, hybrid, on-premises) - Runtime Fabric architecture overview - Anypoint Platform components and capabilities |
| API Management and Governance | - API lifecycle management - API security policies and enforcement - Governance frameworks and best practices |
| Performance and Scalability | - High availability design patterns - Scaling Mule applications |
| Integration Architecture Strategy | - System, process, and experience APIs - Designing enterprise integration architecture - API-led connectivity principles |
| Security and Compliance | - Secure API exposure and threat protection - Authentication and authorization mechanisms |
| Data Integration and Transformation | - Data mapping and transformation strategies - Batch vs real-time integration patterns |
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NEW QUESTION # 29
How are an API implementation, API client, and API consumer combined to invoke and process an API?
Answer: C
Explanation:
Correct Answe r: 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.
NEW QUESTION # 30
Traffic is routed through an API proxy to an API implementation. The API proxy is managed by API Manager and the API implementation is deployed to a CloudHub VPC using Runtime Manager. API policies have been applied to this API. In this deployment scenario, at what point are the API policies enforced on incoming API client requests?
Answer: A
Explanation:
Correct Answe r: At the API proxy
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>> API Policies can be enforced at two places in Mule platform.
>> One - As an Embedded Policy enforcement in the same Mule Runtime where API implementation is running.
>> Two - On an API Proxy sitting in front of the Mule Runtime where API implementation is running.
>> As the deployment scenario in the question has API Proxy involved, the policies will be enforced at the API Proxy.
NEW QUESTION # 31
What correctly characterizes unit tests of Mule applications?
Answer: A
Explanation:
Correct Answe r: They are typically written using MUnit to run in an embedded Mule runtime that does not require external connectivity.
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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 # 32
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?
Answer: A
Explanation:
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
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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.
NEW QUESTION # 33
What is a key performance indicator (KPI) that measures the success of a typical C4E that is immediately apparent in responses from the Anypoint Platform APIs?
Answer: C
Explanation:
Correct Answe r: The number of API specifications in RAML or OAS format published to Anypoint Exchange
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>> The success of C4E always depends on their contribution to the number of reusable assets that they have helped to build and publish to Anypoint Exchange.
>> It is NOT due to any factors w.r.t # of outages, Manual vs CI/CD deployments or Publicly accessible HTTP endpoints
>> Anypoint Platform APIs helps us to quickly run and get the number of published RAML/OAS assets to Anypoint Exchange. This clearly depicts how successful a C4E team is based on number of returned assets in the response.
NEW QUESTION # 34
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