A company uses a hybrid Anypoint Platform deployment model that combines the EU
control plane with customer-hosted Mule runtimes. After successfully testing a Mule API
implementation in the Staging environment, the Mule API implementation is set with
environment-specific properties and must be promoted to the Production environment.
What is a way that MuleSoft recommends to configure the Mule API implementation and
automate its promotion to the Production environment?
A.
Bundle properties files for each environment into the Mule API implementation's deployable
archive, then promote the Mule API implementation to the Production environment using
Anypoint CLI or the Anypoint Platform REST APIsB.
B.
Modify the Mule API implementation's properties in the API Manager Properties tab, then
promote the Mule API implementation to the Production environment using API Manager
C.
Modify the Mule API implementation's properties in Anypoint Exchange, then promote the
Mule API implementation to the Production environment using Runtime Manager
D.
Use an API policy to change properties in the Mule API implementation deployed to the
Staging environment and another API policy to deploy the Mule API implementation to the
Production environment
Bundle properties files for each environment into the Mule API implementation's deployable
archive, then promote the Mule API implementation to the Production environment using
Anypoint CLI or the Anypoint Platform REST APIsB.
Explanation: Explanation
Correct Answer: Bundle properties files for each environment into the Mule API
implementation's deployable archive, then promote the Mule API implementation to the
Production environment using Anypoint CLI or the Anypoint Platform REST APIs
*****************************************
>> Anypoint Exchange is for asset discovery and documentation. It has got no provision to
modify the properties of Mule API implementations at all.
>> API Manager is for managing API instances, their contracts, policies and SLAs. It has
also got no provision to modify the properties of API implementations.
>> API policies are to address Non-functional requirements of APIs and has again got no
provision to modify the properties of API implementations.
So, the right way and recommended way to do this as part of development practice is to
bundle properties files for each environment into the Mule API implementation and just
point and refer to respective file per environment.
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 producer should be contacted to understand the change to existing functionality
C.
The API client code only needs to be changed if it needs to take advantage of the new features
D.
The API clients need to update the code on their side and need to do full regression
The API client code only needs to be changed if it needs to take advantage of the new features
What is most likely NOT a characteristic of an integration test for a REST API
implementation?
A.
The test needs all source and/or target systems configured and accessible
B.
The test runs immediately after the Mule application has been compiled and packaged
C.
The test is triggered by an external HTTP request
D.
The test prepares a known request payload and validates the response payload
The test runs immediately after the Mule application has been compiled and packaged
Explanation: Explanation
Correct Answer: The test runs immediately after the Mule application has been compiled
and packaged
*****************************************
>> Integration tests are the last layer of tests we need to add to be fully covered.
>> These tests actually run against Mule running with your full configuration in place and are tested from external source as they work in PROD.
>> These tests exercise the application as a whole with actual transports enabled. So,
external systems are affected when these tests run.
So, these tests do NOT run immediately after the Mule application has been compiled and
packaged.
FYI... Unit Tests are the one that run immediately after the Mule application has been
compiled and packaged.
Reference: https://docs.mulesoft.com/mule-runtime/3.9/testing-strategies#integrationtesting
The application network is recomposable: it is built for change because it "bends but does
not break"
A.
TRUE
B.
FALSE
TRUE
Explanation: *****************************************
>> Application Network is a disposable architecture.
>> Which means, it can be altered without disturbing entire architecture and its
components.
>> It bends as per requirements or design changes but does not break
Reference: https://www.mulesoft.com/resources/api/what-is-an-application-network
What are 4 important Platform Capabilities offered by Anypoint Platform?
A.
API Versioning, API Runtime Execution and Hosting, API Invocation, API Consumer Engagement
B.
API Design and Development, API Runtime Execution and Hosting, API Versioning, API
Deprecation
C.
API Design and Development, API Runtime Execution and Hosting, API Operations and
Management, API Consumer Engagement
D.
API Design and Development, API Deprecation, API Versioning, API Consumer
Engagement
API Design and Development, API Runtime Execution and Hosting, API Operations and
Management, API Consumer Engagement
Explanation: Explanation
Correct Answer: API Design and Development, API Runtime Execution and Hosting, API
Operations and Management, API Consumer Engagement
*****************************************
>> API Design and Development - Anypoint Studio, Anypoint Design Center, Anypoint
Connectors
>> API Runtime Execution and Hosting - Mule Runtimes, CloudHub, Runtime Services
>> API Operations and Management - Anypoint API Manager, Anypoint Exchange
>> API Consumer Management - API Contracts, Public Portals, Anypoint Exchange, API
Notebooks
An organization uses various cloud-based SaaS systems and multiple on-premises
systems. The on-premises systems are an important part of the organization's application
network and can only be accessed from within the organization's intranet.
What is the best way to configure and use Anypoint Platform to support integrations with
both the cloud-based SaaS systems and on-premises systems?
A) Use CloudHub-deployed Mule runtimes in an Anypoint VPC managed by Anypoint
Platform Private Cloud Edition control plane
A.
Option A
B.
Option B
C.
Option C
D.
Option D
Option B
Explanation: •Explanation
Correct Answer: Use a combination of CloudHub-deployed and manually provisioned onpremises
Mule runtimes managed by the MuleSoft-hosted Platform control plane.
*****************************************
Key details to be taken from the given scenario:
>> Organization uses BOTH cloud-based and on-premises systems
>> On-premises systems can only be accessed from within the organization's intranet
Let us evaluate the given choices based on above key details:
>> CloudHub-deployed Mule runtimes can ONLY be controlled using MuleSoft-hosted
control plane. We CANNOT use Private Cloud Edition's control plane to control CloudHub
Mule Runtimes. So, option suggesting this is INVALID
>> Using CloudHub-deployed Mule runtimes in the shared worker cloud managed by the
MuleSoft-hosted Anypoint Platform is completely IRRELEVANT to given scenario and silly
choice. So, option suggesting this is INVALID
>> Using an on-premises installation of Mule runtimes that are completely isolated with NO
external network access, managed by the Anypoint Platform Private Cloud Edition control
plane would work for On-premises integrations. However, with NO external access,
integrations cannot be done to SaaS-based apps. Moreover CloudHub-hosted apps are
best-fit for integrating with SaaS-based applications. So, option suggesting this is BEST
WAY.
The best way to configure and use Anypoint Platform to support these mixed/hybrid
integrations is to use a combination of CloudHub-deployed and manually provisioned onpremises
Mule runtimes managed by the MuleSoft-hosted Platform control plane.
An operations team is analyzing the effort needed to set up monitoring of their application network. They are looking at which API invocation metrics can be used to identify and predict trouble without having to write custom scripts or install additional analytics software or tools. Which type of metrics can satisfy this goal of directly identifying and predicting failures?
A. The number and types of API policy violations per day
B. The effectiveness of the application network based on the level of reuse
C. The number and types of past API invocations across the application network
D. The ROI from each APT invocation
Explanation:
To monitor an application network and predict issues without custom scripts,
policy violation metrics are critical. They provide insights into potential problems by
tracking instances where API usage does not conform to defined policies. Here’s why this
approach is suitable:
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.
*****************************************
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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