What best explains the use of auto-discovery in API implementations?
A. It makes API Manager aware of API implementations and hence enables it to enforce policies
B. It enables Anypoint Studio to discover API definitions configured in Anypoint Platform
C. It enables Anypoint Exchange to discover assets and makes them available for reuse
D. It enables Anypoint Analytics to gain insight into the usage of APIs
Explanation: Explanation
Correct Answer: It makes API Manager aware of API implementations and hence enables it
to enforce policies.
*****************************************
>> API Autodiscovery is a mechanism that manages an API from API Manager by pairing
the deployed application to an API created on the platform.
>> API Management includes tracking, enforcing policies if you apply any, and reporting
API analytics.
>> Critical to the Autodiscovery process is identifying the API by providing the API name
and version.
References:
https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept
https://docs.mulesoft.com/api-manager/1.x/api-auto-discovery
https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept
Due to a limitation in the backend system, a system API can only handle up to 500
requests per second. What is the best type of API policy to apply to the system API to avoid overloading the backend system?
A.
Rate limiting
B.
HTTP caching
C.
Rate limiting - SLA based
D.
Spike control
Spike control
Explanation: Explanation
Correct Answer: Spike control
*****************************************
>> First things first, HTTP Caching policy is for purposes different than avoiding the
backend system from overloading. So this is OUT.
>> Rate Limiting and Throttling/ Spike Control policies are designed to limit API access, but
have different intentions.
>> Rate limiting protects an API by applying a hard limit on its access.
>> Throttling/ Spike Control shapes API access by smoothing spikes in traffic.
That is why, Spike Control is the right option
An API client calls one method from an existing API implementation. The API
implementation is later updated. What change to the API implementation would require the API client's invocation logic to also be updated?
A.
When the data type of the response is changed for the method called by the API client
B.
When a new method is added to the resource used by the API client
C.
When a new required field is added to the method called by the API client
D.
When a child method is added to the method called by the API client
When a new required field is added to the method called by the API client
Explanation: Explanation
Correct Answer: When a new required field is added to the method called by the API client
*****************************************
>> Generally, the logic on API clients need to be updated when the API contract breaks.
>> When a new method or a child method is added to an API , the API client does not
break as it can still continue to use its existing method. So these two options are out.
>> We are left for two more where "datatype of the response if changed" and "a new
required field is added".
>> Changing the datatype of the response does break the API contract. However, the
question is insisting on the "invocation" logic and not about the response handling logic.
The API client can still invoke the API successfully and receive the response but the
response will have a different datatype for some field.
>> Adding a new required field will break the API's invocation contract. When adding a new
required field, the API contract breaks the RAML or API spec agreement that the API
client/API consumer and API provider has between them. So this requires the API client
invocation logic to also be updated.
An online store's marketing team has noticed an increase in customers leaving online baskets without checking out. They suspect a technology issue is at the root cause of the baskets being left behind. They approach the Center for Enablement to ask for help identifying the issue. Multiple APIs from across all the layers of their application network are involved in the shopping application. Which feature of the Anypoint Platform can be used to view metrics from all involved APIs at the same time?
A. Custom dashboards
B. Built-in dashboards
C. Functional monitoring
D. API Manager
An API implementation is deployed to CloudHub.
What conditions can be alerted on using the default Anypoint Platform functionality, where
the alert conditions depend on the end-to-end request processing of the API
implementation?
A.
When the API is invoked by an unrecognized API client
B.
When a particular API client invokes the API too often within a given time period
C.
When the response time of API invocations exceeds a threshold
D.
When the API receives a very high number of API invocations
When the response time of API invocations exceeds a threshold
Explanation: Explanation
Correct Answer: When the response time of API invocations exceeds a threshold
*****************************************
>> Alerts can be setup for all the given options using the default Anypoint Platform
functionality
>> However, the question insists on an alert whose conditions depend on the end-to-end
request processing of the API implementation.
>> Alert w.r.t "Response Times" is the only one which requires end-to-end request
processing of API implementation in order to determine if the threshold is exceeded or not.
Reference: https://docs.mulesoft.com/api-manager/2.x/using-api-alerts
In which layer of API-led connectivity, does the business logic orchestration reside?
A.
System Layer
B.
Experience Layer
C.
Process Layer
Process Layer
Explanation: Explanation
Correct Answer: Process Layer
*****************************************
>> Experience layer is dedicated for enrichment of end user experience. This layer is to
meet the needs of different API clients/ consumers.
>> System layer is dedicated to APIs which are modular in nature and implement/ expose
various individual functionalities of backend systems
>> Process layer is the place where simple or complex business orchestration logic is
written by invoking one or many System layer modular APIs
So, Process Layer is the right answer.
Refer to the exhibit.
An organization uses one specific CloudHub (AWS) region for all CloudHub deployments.
How are CloudHub workers assigned to availability zones (AZs) when the organization's
Mule applications are deployed to CloudHub in that region?
A.
Workers belonging to a given environment are assigned to the same AZ within that region
B.
AZs are selected as part of the Mule application's deployment configuration
C.
Workers are randomly distributed across available AZs within that region
D.
An AZ is randomly selected for a Mule application, and all the Mule application's CloudHub workers are assigned to that one AZ
An AZ is randomly selected for a Mule application, and all the Mule application's CloudHub workers are assigned to that one AZ
Explanation: Explanation
Correct Answer: Workers are randomly distributed across available AZs within that region.
*****************************************
>> Currently, we only have control to choose which AWS Region to choose but there is no
control at all using any configurations or deployment options to decide what Availability
Zone (AZ) to assign to what worker.
>> There are NO fixed or implicit rules on platform too w.r.t assignment of AZ to workers
based on environment or application.
>> They are completely assigned in random. However, cloudhub definitely ensures that
HA is achieved by assigning the workers to more than on AZ so that all workers are not
assigned to same AZ for same application.
: https://help.mulesoft.com/s/question/0D52T000051rqDj/one-cloudhub-aws-region-howcloudhub-
workers-are-assigned-to-availability-zones-azs-
Graphical user interface, application
Description automatically generated
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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)
*****************************************
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
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