The Line of Business (LoB) of an eCommerce company is requesting a process that sends automated notifications via email every time a new order is processed through the customer's mobile application or through the internal company's web application. In the future, multiple notification channels may be added: for example, text messages and push notifications. What is the most effective API-led connectivity approach for the scenario described above?
A. Create one Experience API for the web application and one for the mobile application.
Create a Process API to orchestrate and retrieve the email template from = database.
Create a System API that sends the email using the Anypoint Connector for Email.
Create one Experience API for the web application and one for the mobile application.
Create a Process API to orchestrate and retrieve the email template from = database.
Create a System API that sends the email using the Anypoint Connector for Email.
B. Create one Experience API for the web application and one for the mobile application
Create a Process API to orchestrate, retrieve the email template from a database, and
send the email using the Anypoint Connector for Email.
C. Create Experience APIs for both the web application and mobile application.
Create a Process API ta orchestrate, retrieve the email template from e database, and
send the email using the Anypoint Connector for Email.
D. Create Experience APIs for both the web application and mobile application.
(Create 3 Process API to orchestrate and retrieve the email template from 2 database.
Create a System API that sends the email using the Anypoint Connector for Email.
Explanation:
In this scenario, the best approach to satisfy the API-led connectivity
principles and support future scalability is:
What should be ensured before sharing an API through a public Anypoint Exchange portal?
A.
The visibility level of the API instances of that API that need to be publicly accessible should be set to public visibility
B.
The users needing access to the API should be added to the appropriate role in
Anypoint Platform
C.
The API should be functional with at least an initial implementation deployed and accessible for users to interact with
D.
The API should be secured using one of the supported authentication/authorization mechanisms to ensure that data is not compromised
The visibility level of the API instances of that API that need to be publicly accessible should be set to public visibility
Explanation: Explanation
What are the major benefits of MuleSoft proposed IT Operating Model?
A.
1. Decrease the IT delivery gap
2. Meet various business demands without increasing the IT capacity
3. Focus on creation of reusable assets first. Upon finishing creation of all the possible
assets then inform the LOBs in the organization to start using them
B.
1. Decrease the IT delivery gap
2. Meet various business demands by increasing the IT capacity and forming various IT
departments
3. Make consumption of assets at the rate of production
C.
1. Decrease the IT delivery gap
2. Meet various business demands without increasing the IT capacity
3. Make consumption of assets at the rate of production
1. Decrease the IT delivery gap
2. Meet various business demands without increasing the IT capacity
3. Make consumption of assets at the rate of production
Explanation: Explanation
Correct Answer:
1. Decrease the IT delivery gap
2. Meet various business demands without increasing the IT capacity
3. Make consumption of assets at the rate of production.
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Reference: https://www.youtube.com/watch?v=U0FpYMnMjmM
A set of tests must be performed prior to deploying API implementations to a staging
environment. Due to data security and access restrictions, untested APIs cannot be
granted access to the backend systems, so instead mocked data must be used for these
tests. The amount of available mocked data and its contents is sufficient to entirely test the
API implementations with no active connections to the backend systems. What type of
tests should be used to incorporate this mocked data?
A.
Integration tests
B.
Performance tests
C.
Functional tests (Blackbox)
D.
Unit tests (Whitebox)
Unit tests (Whitebox)
Explanation: Explanation
Correct Answer: Unit tests (Whitebox)
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Reference: https://docs.mulesoft.com/mule-runtime/3.9/testing-strategies
As per general IT testing practice and MuleSoft recommended practice, Integration and
Performance tests should be done on full end to end setup for right evaluation. Which
means all end systems should be connected while doing the tests. So, these options are
OUT and we are left with Unit Tests and Functional Tests.
As per attached reference documentation from MuleSoft:
Unit Tests - are limited to the code that can be realistically exercised without the need to
run it inside Mule itself. So good candidates are Small pieces of modular code, Sub Flows,
Custom transformers, Custom components, Custom expression evaluators etc.
Functional Tests - are those that most extensively exercise your application configuration.
In these tests, you have the freedom and tools for simulating happy and unhappy paths.
You also have the possibility to create stubs for target services and make them success or
fail to easily simulate happy and unhappy paths respectively.
As the scenario in the question demands for API implementation to be tested before
deployment to Staging and also clearly indicates that there is enough/ sufficient amount of
mock data to test the various components of API implementations with no active
connections to the backend systems, Unit Tests are the one to be used to incorporate this
A team is planning to enhance an Experience API specification, and they are following APIled connectivity design principles. What is their motivation for enhancing the API?
A. The primary API consumer wants certain kinds of endpoints changed from the Center for Enablement standard to the consumer system standard
B. The underlying System API is updated to provide more detailed data for several heavily used resources
C. An IP Allowlist policy is being added to the API instances in the Development and Staging environments
D. A Canonical Data Model is being adopted that impacts several types of data included in the API
Explanation:
In API-led design, an Experience API is enhanced to improve how data is
delivered to end-user applications. One primary reason to enhance an Experience API is
when new data standards, such as a Canonical Data Model, are adopted. Here’s why:
An existing Quoting API is defined in RAML and used by REST clients for interacting with the quoting engine. Currently there is a resource defined in the RAML that allows the creation of quotes; however, a new requirement was just received to allow for the updating of existing quotes. Which two actions need to be taken to facilitate this change so it can be processed? (Choose 2 answers)
A. Update the API implementation to accommodate the new update request
B. B. Remove the old client applications and create new client applications to account for the changes
C. Update the RAML with new method details for the update request
D. Deprecate existing versions of the API in Exchange
E. Add a new API policy to API Manager to allow access to the updated endpoint
Explanation:
To accommodate the new requirement of allowing updates to existing
quotes, the following actions should be taken:
Which of the below, when used together, makes the IT Operational Model effective?
A.
Create reusable assets, Do marketing on the created assets across organization, Arrange time to time LOB reviews to ensure assets are being consumed or not
B.
Create reusable assets, Make them discoverable so that LOB teams can self-serve and browse the APIs, Get active feedback and usage metrics
C.
Create resuable assets, make them discoverable so that LOB teams can self-serve and browse the APIs
Create resuable assets, make them discoverable so that LOB teams can self-serve and browse the APIs
Explanation: Explanation
Correct Answer: Create reusable assets, Make them discoverable so that LOB teams can self-serve and browse the APIs, Get active feedback and usage metrics.
Diagram, arrow
Description automatically generated
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 there is an existing Enterprise Data Model widely used across the organization
B.
When the System API can be assigned to a bounded context with a corresponding data
model
C.
When a pragmatic approach with only limited isolation from the backend system is deemed appropriate
D.
When the corresponding backend system is expected to be replaced in the near future
When a pragmatic approach with only limited isolation from the backend system is deemed appropriate
Explanation: Explanation
Correct Answer: When a pragmatic approach with only limited isolation from the backend
system is deemed appropriate.
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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 system and 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
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