What condition requires using a CloudHub Dedicated Load Balancer?
A.
When cross-region load balancing is required between separate deployments of the same Mule application
B.
When custom DNS names are required for API implementations deployed to customerhosted Mule runtimes
C.
When API invocations across multiple CloudHub workers must be load balanced
D.
When server-side load-balanced TLS mutual authentication is required between API
implementations and API clients
When server-side load-balanced TLS mutual authentication is required between API
implementations and API clients
Explanation: Explanation
Correct Answer: When server-side load-balanced TLS mutual authentication is required
between API implementations and API clients
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Fact/ Memory Tip: Although there are many benefits of CloudHub Dedicated Load
balancer, TWO important things that should come to ones mind for considering it are:
>> Having URL endpoints with Custom DNS names on CloudHub deployed apps
>> Configuring custom certificates for both HTTPS and Two-way (Mutual) authentication.
Coming to the options provided for this question:
>> We CANNOT use DLB to perform cross-region load balancing between separate
deployments of the same Mule application.
>> We can have mapping rules to have more than one DLB URL pointing to same Mule
app. But vicevera (More than one Mule app having same DLB URL) is NOT POSSIBLE
>> It is true that DLB helps to setup custom DNS names for Cloudhub deployed Mule apps
but NOT true for apps deployed to Customer-hosted Mule Runtimes.
>> It is true to that we can load balance API invocations across multiple CloudHub workers
using DLB but it is NOT A MUST. We can achieve the same (load balancing) using SLB
(Shared Load Balancer) too. We DO NOT necessarily require DLB for achieve it.
So the only right option that fits the scenario and requires us to use DLB is when TLS
mutual authentication is required between API implementations and API clients.
Reference: https://docs.mulesoft.com/runtime-manager/cloudhub-dedicated-load-balancer
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
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.
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.
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
A European company has customers all across Europe, and the IT department is migrating from an older platform to MuleSoft. The main requirements are that the new platform should allow redeployments with zero downtime and deployment of applications to multiple runtime versions, provide security and speed, and utilize Anypoint MQ as the message service. Which runtime plane should the company select based on the requirements without additional network configuration?
A. Runtime Fabric on VMs / Bare Metal for the runtime plane
B. Customer-hosted runtime plane
C. MuleSoft-hosted runtime plane (CloudHub)
D. Anypoint Runtime Fabric on Self-Managed Kubernetes for the runtime plane
Explanation:
For a European company with requirements such as zero-downtime
redeployment, deployment to multiple runtime versions, secure and fast
performance, and the use of Anypoint MQ without additional network configuration,
CloudHub is the best choice for the following reasons:
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 API invocations to an API implementation?
A. When the API invocations are sent directly to the internal DNS record of the API implementation
B. When the API invocations are not over-a- secure TLS/SSL communication channel
C. When the APL invecations originate from a geography different than the API
D. When the number of API invocations are below a threshold
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
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