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MuleSoft MCPA-Level-1-Maintenance Exam Syllabus Topics:

Topic	Details
Topic 1	Select CloudHub worker sizes and configuration as appropriate Specify how and when to promote APIs with API Manager
Topic 2	Correctly use the terms API, API implementation, API client, API consumer, and API invocation Describe the fundamentals of deployments, networking, and routing on CloudHub
Topic 3	Identify KPIs to measure the success of a C4E Select Anypoint Platform identity management vs client management for the correct purpose
Topic 4	Describe the purpose and roles of a Center for Enablement (C4E) Describe the capabilities and high-level components of Anypoint Platform
Topic 5	Identify single points of failure in typical CloudHub usage Identify the components of Anypoint Platform that generate data for monitoring and alerting
Topic 6	Identify when redeployment of API implementations is necessary Compare unit and integration tests and specify where MUnit is best employed
Topic 7	Define and describe the benefits of API-led connectivity and application networks Explain MuleSoft’s proposal for closing the IT delivery gap
Topic 8	Identify changes to an API that would require or not require a major version increment Explain how to register an API client for access to an API version

>> MuleSoft MCPA-Level-1-Maintenance Valid Exam Duration <<

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MuleSoft Certified Platform Architect - Level 1 MAINTENANCE Sample Questions (Q18-Q23):

NEW QUESTION # 18
When using CloudHub with the Shared Load Balancer, what is managed EXCLUSIVELY by the API implementation (the Mule application) and NOT by Anypoint Platform?

• A. The SSL certificates used by the API implementation to expose HTTPS endpoints
• B. The assignment of each HTTP request to a particular CloudHub worker
• C. The logging configuration that enables log entries to be visible in Runtime Manager
• D. The number of DNS entries allocated to the API implementation

Answer: A Explanation:
The SSL certificates used by the API implementation to expose HTTPS endpoints
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>> The assignment of each HTTP request to a particular CloudHub worker is taken care by Anypoint Platform itself. We need not manage it explicitly in the API implementation and in fact we CANNOT manage it in the API implementation.
>> The logging configuration that enables log entries to be visible in Runtime Manager is ALWAYS managed in the API implementation and NOT just for SLB. So this is not something we do EXCLUSIVELY when using SLB.
>> We DO NOT manage the number of DNS entries allocated to the API implementation inside the code.
Anypoint Platform takes care of this.
It is the SSL certificates used by the API implementation to expose HTTPS endpoints that is to be managed EXCLUSIVELY by the API implementation. Anypoint Platform does NOT do this when using SLBs.
NEW QUESTION # 19*
A company requires Mule applications deployed to CloudHub to be isolated between non-production and production environments. This is so Mule applications deployed to non-production environments can only access backend systems running in their customer-hosted non-production environment, and so Mule applications deployed to production environments can only access backend systems running in their customer-hosted production environment. How does MuleSoft recommend modifying Mule applications, configuring environments, or changing infrastructure to support this type of per-environment isolation between Mule applications and backend systems?

• A. Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted environments
• B. Create non-production and production environments in different Anypoint Platform business groups
• C. Configure firewall rules in the infrastructure inside each customer-hosted environment so that only IP addresses from the corresponding Anypoint Platform environments are allowed to communicate with corresponding backend systems
• D. Modify properties of Mule applications deployed to the production Anypoint Platform environments to prevent access from non-production Mule applications

Answer: A Explanation:
Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted environments.
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>> Creating different Business Groups does NOT make any difference w.r.t accessing the non-prod and prod customer-hosted environments. Still they will be accessing from both Business Groups unless process network restrictions are put in place.
>> We need to modify or couple the Mule Application Implementations with the environment. In fact, we should never implements application coupled with environments by binding them in the properties. Only basic things like endpoint URL etc should be bundled in properties but not environment level access restrictions.
>> IP addresses on CloudHub are dynamic until unless a special static addresses are assigned. So it is not possible to setup firewall rules in customer-hosted infrastrcture. More over, even if static IP addresses are assigned, there could be 100s of applications running on cloudhub and setting up rules for all of them would be a hectic task, non-maintainable and definitely got a good practice.
>> The best practice recommended ), is to have your Anypoint VPCs
seperated for Prod and Non-Prod and perform the VPC peering or VPN tunneling for these Anypoint VPCs to respective Prod and Non-Prod customer-hosted environment networks.
NEW QUESTION # 20*
How can the application of a rate limiting API policy be accurately reflected in the RAML definition of an API?

• A. By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example
• B. By refining the response definitions by adding the out-of-the-box Anypoint Platform rate-limit-enforcement securityScheme with description, type, and example
• C. By refining the resource definitions by adding a description of the rate limiting policy behavior
• D. By refining the request definitions by adding a remaining Requests query parameter with description, type, and example

Answer: A Explanation:
By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example
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References:
https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling#response-headers
https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling-sla-based-policies#response-headers
NEW QUESTION # 21*
An organization is deploying their new implementation of the OrderStatus System API to multiple workers in CloudHub. This API fronts the organization's on-premises Order Management System, which is accessed by the API implementation over an IPsec tunnel.
What type of error typically does NOT result in a service outage of the OrderStatus System API?

• A. The AWS region goes offline with a major network failure to the relevant AWS data centers
• B. API Manager has an extended outage during the initial deployment of the API implementation
• C. A CloudHub worker fails with an out-of-memory exception
• D. The Order Management System is Inaccessible due to a network outage in the organization's on-premises data center

Answer: C Explanation:
A CloudHub worker fails with an out-of-memory exception.
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>> An AWS Region itself going down will definitely result in an outage as it does not matter how many workers are assigned to the Mule App as all of those in that region will go down. This is a complete downtime and outage.
>> Extended outage of API manager during initial deployment of API implementation will of course cause issues in proper application startup itself as the API Autodiscovery might fail or API policy templates and polices may not be downloaded to embed at the time of applicaiton startup etc... there are many reasons that could cause issues.
>> A network outage onpremises would of course cause the Order Management System not accessible and it does not matter how many workers are assigned to the app they all will fail and cause outage for sure.
The only option that does NOT result in a service outage is if a cloudhub worker fails with an out-of-memory exception. Even if a worker fails and goes down, there are still other workers to handle the requests and keep the API UP and Running. So, this is the right answer.
NEW QUESTION # 22*
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 the System API can be assigned to a bounded context with a corresponding data model
• B. When the corresponding backend system is expected to be replaced in the near future
• C. When a pragmatic approach with only limited isolation from the backend system is deemed appropriate
• D. When there is an existing Enterprise Data Model widely used across the organization

Answer: C Explanation:
When a pragmatic approach with only limited isolation from the backend system is deemed appropriate.
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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
NEW QUESTION # 23
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