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 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?
A.
The number of production outage incidents reported in the last 24 hours
B.
The number of API implementations that have a publicly accessible HTTP endpoint and are being managed by Anypoint Platform
C.
The fraction of API implementations deployed manually relative to those deployed using a CI/CD tool
D.
The number of API specifications in RAML or OAS format published to Anypoint
Exchange
The number of API specifications in RAML or OAS format published to Anypoint
Exchange
Explanation: Explanation
Correct Answer: The number of API specifications in RAML or OAS format published to
Anypoint Exchange
*****************************************
>> 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.
Reference: https://help.mulesoft.com/s/question/0D52T00004mXSTUSA4/how-should-acompany-
measure-c4e-success
An Order API must be designed that contains significant amounts of integration logic and
involves the invocation of the Product API.
The power relationship between Order API and Product API is one of "Customer/Supplier",
because the Product API is used heavily throughout the organization and is developed by a
dedicated development team located in the office of the CTO.
What strategy should be used to deal with the API data model of the Product API within the
Order API?
A.
Convince the development team of the Product API to adopt the API data model of the Order API such that the integration logic of the Order API can work with one consistent internal data model
B.
Work with the API data types of the Product API directly when implementing the integration logic of the Order API such that the Order API uses the same (unchanged) data types as the Product API
C.
Implement an anti-corruption layer in the Order API that transforms the Product API data
model into internal data types of the Order API
D.
Start an organization-wide data modeling initiative that will result in an Enterprise Data
Model that will then be used in both the Product API and the Order API
Implement an anti-corruption layer in the Order API that transforms the Product API data
model into internal data types of the Order API
Explanation: Explanation
Correct Answer: Convince the development team of the product API to adopt the API data
model of the Order API such that integration logic of the Order API can work with one
consistent internal data model
*****************************************
Key details to note from the given scenario:
>> Power relationship between Order API and Product API is customer/supplier
So, as per below rules of "Power Relationships", the caller (in this case Order API) would
request for features to the called (Product API team) and the Product API team would need
to accomodate those requests.
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
Use an SLA-based rate limiting policy and assign a client application to a matching SLA
tier based on its type
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
Say, there is a legacy CRM system called CRM-Z which is offering below functions:
1. Customer creation
2. Amend details of an existing customer
3. Retrieve details of a customer
4. Suspend a customer
A.
Implement a system API named customerManagement which has all the functionalities
wrapped in it as various operations/resources
B.
Implement different system APIs named createCustomer, amendCustomer,
retrieveCustomer and suspendCustomer as they are modular and has seperation of concerns
C.
Implement different system APIs named createCustomerInCRMZ,
amendCustomerInCRMZ, retrieveCustomerFromCRMZ and suspendCustomerInCRMZ as
they are modular and has seperation of concerns
Implement different system APIs named createCustomer, amendCustomer,
retrieveCustomer and suspendCustomer as they are modular and has seperation of concerns
Correct Answer: Implement different system APIs named createCustomer,
amendCustomer, retrieveCustomer and suspendCustomer as they are modular and has
seperation of concerns
*****************************************
>> It is quite normal to have a single API and different Verb + Resource combinations.
However, this fits well for an Experience API or a Process API but not a best architecture
style for System APIs. So, option with just one customerManagement API is not the best
choice here.
>> The option with APIs in createCustomerInCRMZ format is next close choice w.r.t
modularization and less maintenance but the naming of APIs is directly coupled with the
legacy system. A better foreseen approach would be to name your APIs by abstracting the
backend system names as it allows seamless replacement/migration of any backend
system anytime. So, this is not the correct choice too.
>> createCustomer, amendCustomer, retrieveCustomer and suspendCustomer is the right
approach and is the best fit compared to other options as they are both modular and same
time got the names decoupled from backend system and it has covered all requirements a
System API needs.
What is a best practice when building System APIs?
A.
Document the API using an easily consumable asset like a RAML definition
B.
Model all API resources and methods to closely mimic the operations of the backend system
C.
Build an Enterprise Data Model (Canonical Data Model) for each backend system and apply it to System APIs
D.
Expose to API clients all technical details of the API implementation's interaction wifch
the backend system
Model all API resources and methods to closely mimic the operations of the backend system
Explanation: Explanation
Correct Answer: Model all API resources and methods to closely mimic the operations of
the backend system.
*****************************************
>> There are NO fixed and straight best practices while opting data models for APIs. They
are completly contextual and depends on number of factors. Based upon those factors, an
enterprise can choose if they have to go with Enterprise Canonical Data Model or Bounded
Context Model etc.
>> One should NEVER expose the technical details of API implementation to their API
clients. Only the API interface/ RAML is exposed to API clients.
>> It is true that the RAML definitions of APIs should be as detailed as possible and should
reflect most of the documentation. However, just that is NOT enough to call your API as
best documented API. There should be even more documentation on Anypoint Exchange
with API Notebooks etc. to make and create a developer friendly API and repository..
>> The best practice always when creating System APIs is to create their API interfaces by
modeling their resources and methods to closely reflect the operations and functionalities
of that backend system.
Which out-of-the-box key performance indicator measures the success of a typical Center for Enablement and is immediately available in responses from Anypoint Platform APIs?
A. Per business group, the ratio of the number of production APT implementations deployed using a C1/CD pipeline to the number of production API implementations deployed manually
B. Per deployed API implementation, the amount of bandwidth consumed each day
C. Per published API, the number of developers that downloaded s version of the API specification
D. Per published API, the number of consumers that requested access to the API and have been approved in the Production environment
What is the most performant out-of-the-box solution in Anypoint Platform to track
transaction state in an asynchronously executing long-running process implemented as a
Mule application deployed to multiple CloudHub workers?
A.
Redis distributed cache
B.
java.util.WeakHashMap
C.
Persistent Object Store
D.
File-based storage
Persistent Object Store
Explanation: Correct Answer: Persistent Object Store
*****************************************
>> Redis distributed cache is performant but NOT out-of-the-box solution in Anypoint
Platform
>> File-storage is neither performant nor out-of-the-box solution in Anypoint Platform
>> java.util.WeakHashMap needs a completely custom implementation of cache from
scratch using Java code and is limited to the JVM where it is running. Which means the
state in the cache is not worker aware when running on multiple workers. This type of
cache is local to the worker. So, this is neither out-of-the-box nor worker-aware among
multiple workers on cloudhub. https://www.baeldung.com/java-weakhashmap
>> Persistent Object Store is an out-of-the-box solution provided by Anypoint Platform
which is performant as well as worker aware among multiple workers running on
CloudHub. https://docs.mulesoft.com/object-store/
So, Persistent Object Store is the right answer.
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