Question # 1 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 organizationB. 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 appropriateD. When the corresponding backend system is expected to be replaced in the near future
Click for Answer
C. When a pragmatic approach with only limited isolation from the backend system is
deemed appropriate
Answer Description 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
implementations of the Process API tier
Question # 2 What is true about where an API policy is defined in Anypoint Platform and how it is then
applied to API instances?
A. The API policy Is defined In Runtime Manager as part of the API deployment to a Mule
runtime, and then ONLY applied to the specific API Instance B. The API policy Is defined In API Manager for a specific API Instance, and then ONLY
applied to the specific API instance C. The API policy Is defined in API Manager and then automatically applied to ALL API
instances D. The API policy is defined in API Manager, and then applied to ALL API instances in the
specified environment
Click for Answer
B. The API policy Is defined In API Manager for a specific API Instance, and then ONLY
applied to the specific API instance
Answer Description Explanation
Correct Answer: The API policy is defined in API Manager for a specific API instance, and
then ONLY applied to the specific API instance.
*****************************************
>> Once our API specifications are ready and published to Exchange, we need to visit API
Manager and register an API instance for each API.
>> API Manager is the place where management of API aspects takes place like
addressing NFRs by enforcing policies on them.
>> We can create multiple instances for a same API and manage them differently for
different purposes.
>> One instance can have a set of API policies applied and another instance of same API
can have different set of policies applied for some other purpose.
>> These APIs and their instances are defined PER environment basis. So, one need to
manage them seperately in each environment.
>> We can ensure that same configuration of API instances (SLAs, Policies etc..) gets
promoted when promoting to higher environments using platform feature. But this is
optional only. Still one can change them per environment basis if they have to.
>> Runtime Manager is the place to manage API Implementations and their Mule Runtimes
but NOT APIs itself. Though API policies gets executed in Mule Runtimes, We CANNOT
enforce API policies in Runtime Manager. We would need to do that via API Manager only
for a cherry picked instance in an environment.
So, based on these facts, right statement in the given choices is - "The API policy is
defined in API Manager for a specific API instance, and then ONLY applied to the specific
API instance".
Reference: https://docs.mulesoft.com/api-manager/2.x/latest-overview-concept
Question # 3 An organization wants to create a Center for Enablement (C4E). The IT director schedules a series of meetings with IT senior managers.
What should be on the agenda of the first meeting?
A. Define C4E objectives, mission statement, guiding principles, aB. Explore API monetization options based on identified use cases through MuleSoftC. A walk through of common-services best practices for logging, auditing, exception handling, caching, security via policy, and rate limiting/throttling via policyD. Specify operating model for the MuleSoft Integrations division
Click for Answer
A. Define C4E objectives, mission statement, guiding principles, a
Question # 4 An API experiences a high rate of client requests (TPS) vwth small message paytoads.
How can usage limits be imposed on the API based on the type of client application? A. Use an SLA-based rate limiting policy and assign a client application to a matching SLA
tier based on its type B. Use a spike control policy that limits the number of requests for each client application
type C. Use a cross-origin resource sharing (CORS) policy to limit resource sharing between
client applications, configured by the client application type D. Use a rate limiting policy and a client ID enforcement policy, each configured by the
client application type
Click for Answer
A. Use an SLA-based rate limiting policy and assign a client application to a matching SLA
tier based on its type
Answer Description Explanation: Correct Answer: Use an SLA-based rate limiting policy and assign a client
application to a matching SLA tier based on its type.
*****************************************
>> SLA tiers will come into play whenever any limits to be imposed on APIs based on client
type
Reference: https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling-slabased-policies
Question # 5 What are 4 important Platform Capabilities offered by Anypoint Platform? A. API Versioning, API Runtime Execution and Hosting, API Invocation, API Consumer EngagementB. API Design and Development, API Runtime Execution and Hosting, API Versioning, API DeprecationC. API Design and Development, API Runtime Execution and Hosting, API Operations and Management, API Consumer EngagementD. API Design and Development, API Deprecation, API Versioning, API Consumer Engagement
Click for Answer
C. API Design and Development, API Runtime Execution and Hosting, API Operations and Management, API Consumer Engagement
Answer Description 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
Question # 6 An established communications company is beginning its API-led connectivity journey, The company has been using a successful Enterprise Data Model for many years. The company has identified a self-service account management app as the first effort for API- led, and it has identified the following APIs.
Experience layer: Mobile Account Management EAPI, Browser Account Management EAPI Process layer: Customer Lookup PAPI, Service Lookup PAPI, Account Lookup PAPI System layer: Customer SAPI, Account SAPI, Product SAPI, Service SAPI
According to MuleSoft's API-led connectivity approach, which API would not be served by the Enterprise Data Model?
A. Customer SAPIB. Customer Lookup PAPIC. Mobile Account Management EAPID. Service SAPI
Click for Answer
C. Mobile Account Management EAPI
Question # 7 A new upstream API Is being designed to offer an SLA of 500 ms median and 800 ms
maximum (99th percentile) response time. The corresponding API implementation needs to
sequentially invoke 3 downstream APIs of very similar complexity.
The first of these downstream APIs offers the following SLA for its response time: median:
100 ms, 80th percentile: 500 ms, 95th percentile: 1000 ms.
If possible, how can a timeout be set in the upstream API for the invocation of the first
downstream API to meet the new upstream API's desired SLA? A. Set a timeout of 50 ms; this times out more invocations of that API but gives additional
room for retries B. Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to
completeC. No timeout is possible to meet the upstream API's desired SLA; a different SLA must be
negotiated with the first downstream API or invoke an alternative API D. Do not set a timeout; the Invocation of this API Is mandatory and so we must wait until it
responds
Click for Answer
B. Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to
complete
Answer Description Explanation
Correct Answer: Set a timeout of 100ms; that leaves 400ms for other two downstream APIs
to complete
Key details to take from the given scenario:
>> Upstream API's designed SLA is 500ms (median). Lets ignore maximum SLA response
times.
>> This API calls 3 downstream APIs sequentially and all these are of similar complexity.
>> The first downstream API is offering median SLA of 100ms, 80th percentile: 500ms;
95th percentile: 1000ms.
Based on the above details:
>> We can rule out the option which is suggesting to set 50ms timeout. Because, if the
median SLA itself being offered is 100ms then most of the calls are going to timeout and
time gets wasted in retried them and eventually gets exhausted with all retries. Even if
some retries gets successful, the remaining time wont leave enough room for 2nd and 3rd
downstream APIs to respond within time.
>> The option suggesting to NOT set a timeout as the invocation of this API is mandatory
and so we must wait until it responds is silly. As not setting time out would go against the
good implementation pattern and moreover if the first API is not responding within its
offered median SLA 100ms then most probably it would either respond in 500ms (80th
percentile) or 1000ms (95th percentile). In BOTH cases, getting a successful response
from 1st downstream API does NO GOOD because already by this time the Upstream API
SLA of 500 ms is breached. There is no time left to call 2nd and 3rd downstream APIs.
>> It is NOT true that no timeout is possible to meet the upstream APIs desired SLA.
As 1st downstream API is offering its median SLA of 100ms, it means MOST of the time we
would get the responses within that time. So, setting a timeout of 100ms would be ideal for
MOST calls as it leaves enough room of 400ms for remaining 2 downstream API calls.
Question # 8 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
B) Use CloudHub-deployed Mule runtimes in the shared worker cloud managed by the MuleSoft-hosted Anypoint Platform control plane
C) Use 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
D) Use a combination of Cloud Hub-deployed and manually provisioned on-premises Mule runtimes managed by the MuleSoft-hosted Anypoint Platform control plane
A. Option AB. Option BC. Option CD. Option D
Click for Answer
B. Option B
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