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.
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
Which component monitors APIs and endpoints at scheduled intervals, receives reports about whether tests pass or fail, and displays statistics about API and endpoint performance?
A. API Analytics
B. Anypoint Monitoring dashboards
C. APT Functional Monitoring
D. Anypoint Runtime Manager alerts
Explanation:
To minimize operation costs, a customer wants to use a CloudHub 1.0 solution. The
customer's requirements are:
A. One production and one non-production Virtual Private Cloud (VPC).
Use availability zones to differentiate between Business groups.
Allocate maximum CIDR per VPCs to ensure HA across availability zones
B. One production and one non-production Virtual Private Cloud (VPC) per Business
group.
Minimize CIDR aligning with projected application total.
Choose a MuleSoft CloudHub 1.0 region with multiple availability zones.
Deploy multiple workers for HA,
C. One production and one non-production Virtual Private Cloud (VPC) per Business
group.
Minimize CIDR aligning with projected application total.
Divide availability zones during deployment of APIs for HA.
D. One production and one non-production Virtual Private Claud (VPC).
Configure subnet to differentiate between business groups.
Allocate maximum CIDR per VPCs to make it easier to add Child groups.
Span VPC to cover three availability zones.
Once an API Implementation is ready and the API is registered on API Manager, who should request the access to the API on Anypoint Exchange?
A.
None
B.
Both
C.
API Client
D.
API Consumer
API Consumer
Explanation: Explanation
Correct Answer: API Consumer
*****************************************
>> API clients are piece of code or programs that use the client credentials of API
consumer but does not directly interact with Anypoint Exchange to get the access
>> API consumer is the one who should get registered and request access to API and then
API client needs to use those client credentials to hit the APIs
So, API consumer is the one who needs to request access on the API from Anypoint
Exchange
An organization has implemented a Customer Address API to retrieve customer address
information. This API has been deployed to multiple environments and has been configured
to enforce client IDs everywhere.
A developer is writing a client application to allow a user to update their address. The
developer has found the Customer Address API in Anypoint Exchange and wants to use it
in their client application.
What step of gaining access to the API can be performed automatically by Anypoint
Platform?
A.
Approve the client application request for the chosen SLA tier
B.
Request access to the appropriate API Instances deployed to multiple environments using the client application's credentials
C.
Modify the client application to call the API using the client application's credentials
D.
Create a new application in Anypoint Exchange for requesting access to the API
Approve the client application request for the chosen SLA tier
Explanation: Explanation
Correct Answer: Approve the client application request for the chosen SLA tier
*****************************************
>> Only approving the client application request for the chosen SLA tier can be automated
>> Rest of the provided options are not valid
Reference: https://docs.mulesoft.com/api-manager/2.x/defining-sla-tiers#defining-a-tier
A client has several applications running on the Salesforce service cloud. The business requirement for integration is to get daily data changes from Account and Case Objects. Data needs to be moved to the client's private cloud AWS DynamoDB instance as a single JSON and the business foresees only wanting five attributes from the Account object, which has 219 attributes (some custom) and eight attributes from the Case Object. What design should be used to support the API/ Application data model?
A. Create separate entities for Account and Case Objects by mimicking all the attributes in SAPI, which are combined by the PAPI and filtered to provide JSON output containing 13 attributes.
B. Request client’s AWS project team to replicate all the attributes and create Account and Case JSON table in DynamoDB. Then create separate entities for Account and Case Objects by mimicking all the attributes in SAPI to transfer ISON data to DynamoD for respective Objects
C. Start implementing an Enterprise Data Model by defining enterprise Account and Case Objects and implement SAPI and DynamoDB tables based on the Enterprise Data Model,
D. Create separate entities for Account with five attributes and Case with eight attributes in SAPI, which are combined by the PAPI to provide JSON output containing 13 attributes.
A system API is deployed to a primary environment as well as to a disaster recovery (DR)
environment, with different DNS names in each environment. A process API is a client to
the system API and is being rate limited by the system API, with different limits in each of
the environments. The system API's DR environment provides only 20% of the rate limiting
offered by the primary environment. What is the best API fault-tolerant invocation strategy
to reduce overall errors in the process API, given these conditions and constraints?
A.
Invoke the system API deployed to the primary environment; add timeout and retry logic to
the process API to avoid intermittent failures; if it still fails, invoke the system API deployed
to the DR environment
B.
Invoke the system API deployed to the primary environment; add retry logic to the process
API to handle intermittent failures by invoking the system API deployed to the DR
environment
C.
In parallel, invoke the system API deployed to the primary environment and the system API
deployed to the DR environment; add timeout and retry logic to the process API to avoid
intermittent failures; add logic to the process API to combine the results
D.
Invoke the system API deployed to the primary environment; add timeout and retry logic to
the process API to avoid intermittent failures; if it still fails, invoke a copy of the process API
deployed to the DR environment
Invoke the system API deployed to the primary environment; add timeout and retry logic to
the process API to avoid intermittent failures; if it still fails, invoke the system API deployed
to the DR environment
Explanation: Explanation
Correct Answer: Invoke the system API deployed to the primary environment; add timeout
and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the
system API deployed to the DR environment
*****************************************
There is one important consideration to be noted in the question which is - System API in
DR environment provides only 20% of the rate limiting offered by the primary environment.
So, comparitively, very less calls will be allowed into the DR environment API opposed to
its primary environment. With this in mind, lets analyse what is the right and best faulttolerant
invocation strategy.
1. Invoking both the system APIs in parallel is definitely NOT a feasible approach because
of the 20% limitation we have on DR environment. Calling in parallel every time would
easily and quickly exhaust the rate limits on DR environment and may not give chance to
genuine intermittent error scenarios to let in during the time of need.
2. Another option given is suggesting to add timeout and retry logic to process API while
invoking primary environment's system API. This is good so far. However, when all retries
failed, the option is suggesting to invoke the copy of process API on DR environment which
is not right or recommended. Only system API is the one to be considered for fallback and
not the whole process API. Process APIs usually have lot of heavy orchestration calling
many other APIs which we do not want to repeat again by calling DR's process API. So this
option is NOT right.
3. One more option given is suggesting to add the retry (no timeout) logic to process API to
directly retry on DR environment's system API instead of retrying the primary environment
system API first. This is not at all a proper fallback. A proper fallback should occur only
after all retries are performed and exhausted on Primary environment first. But here, the
option is suggesting to directly retry fallback API on first failure itself without trying main
API. So, this option is NOT right too.
This leaves us one option which is right and best fit.
- Invoke the system API deployed to the primary environment
- Add Timeout and Retry logic on it in process API
- If it fails even after all retries, then invoke the system API deployed to the DR
environment.
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