質問 1:Which of the following best fits the definition of API-led connectivity?
A. API-led connectivity is a technology which enabled us to implement Experience, Process and System layer based APIs
B. API-led connectivity is a 3-layered architecture covering Experience, Process and System layers
C. API-led connectivity is not just an architecture or technology but also a way to organize people and processes for efficient IT delivery in the organization
正解:C
解説: (Topexam メンバーにのみ表示されます)
質問 2:True or False. We should always make sure that the APIs being designed and developed are self-servable even if it needs more man-day effort and resources.
A. FALSE
B. TRUE
正解:B
解説: (Topexam メンバーにのみ表示されます)
質問 3: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 number of DNS entries allocated to the API implementation
B. The assignment of each HTTP request to a particular CloudHub worker
C. The SSL certificates used by the API implementation to expose HTTPS endpoints
D. The logging configuration that enables log entries to be visible in Runtime Manager
正解:C
解説: (Topexam メンバーにのみ表示されます)
質問 4:An organization has created an API-led architecture that uses various API layers to integrate mobile clients with a backend system. The backend system consists of a number of specialized components and can be accessed via a REST API. The process and experience APIs share the same bounded-context model that is different from the backend data model. What additional canonical models, bounded-context models, or anti-corruption layers are best added to this architecture to help process data consumed from the backend system?
A. Create a canonical model that combines the backend and API-led models to simplify and unify data models, and minimize data transformations.
B. Create an anti-corruption layer for every API to perform transformation for every data model to match each other, and let data simply travel between APIs to avoid the complexity and overhead of building canonical models
C. Create a bounded-context model for the system layer to closely match the backend data model, and add an anti-corruption layer to let the different bounded contexts cooperate across the system and process layers
D. Create a bounded-context model for every layer and overlap them when the boundary contexts overlap, letting API developers know about the differences between upstream and downstream data models
正解:C
解説: (Topexam メンバーにのみ表示されます)
質問 5:An API implementation is updated. When must the RAML definition of the API also be updated?
A. When the API implementation changes the structure of the request or response messages
B. When the API implementation changes from interacting with a legacy backend system deployed on-premises to a modern, cloud-based (SaaS) system
C. When the API implementation is migrated from an older to a newer version of the Mule runtime
D. When the API implementation is optimized to improve its average response time
正解:A
解説: (Topexam メンバーにのみ表示されます)
質問 6: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 a pragmatic approach with only limited isolation from the backend system is deemed appropriate
C. When there is an existing Enterprise Data Model widely used across the organization
D. When the corresponding backend system is expected to be replaced in the near future
正解:B
解説: (Topexam メンバーにのみ表示されます)
質問 7:A retail company with thousands of stores has an API to receive data about purchases and insert it into a single database. Each individual store sends a batch of purchase data to the API about every 30 minutes. The API implementation uses a database bulk insert command to submit all the purchase data to a database using a custom JDBC driver provided by a data analytics solution provider. The API implementation is deployed to a single CloudHub worker. The JDBC driver processes the data into a set of several temporary disk files on the CloudHub worker, and then the data is sent to an analytics engine using a proprietary protocol. This process usually takes less than a few minutes. Sometimes a request fails. In this case, the logs show a message from the JDBC driver indicating an out-of-file-space message. When the request is resubmitted, it is successful.
What is the best way to try to resolve this throughput issue?
A. Increase the number of CloudHub workers
B. se a CloudHub autoscaling policy to add CloudHub workers
C. Increase the size of the CloudHub worker(s)
D. Use a CloudHub autoscaling policy to increase the size of the CloudHub worker
正解:A
解説: (Topexam メンバーにのみ表示されます)
質問 8: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 API Manager, and then applied to ALL API instances in the specified environment
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 Runtime Manager as part of the API deployment to a Mule runtime, and then ONLY applied to the specific API Instance
正解:B
解説: (Topexam メンバーにのみ表示されます)
質問 9:Refer to the exhibit.

what is true when using customer-hosted Mule runtimes with the MuleSoft-hosted Anypoint Platform control plane (hybrid deployment)?
A. The MuleSoft-hosted Shared Load Balancer can be used to load balance API invocations to the Mule runtimes
B. Anypoint Runtime Manager initiates a network connection to a Mule runtime in order to deploy Mule applications
C. Anypoint Runtime Manager automatically ensures HA in the control plane by creating a new Mule runtime instance in case of a node failure
D. API implementations can run successfully in customer-hosted Mule runtimes, even when they are unable to communicate with the control plane
正解:D
解説: (Topexam メンバーにのみ表示されます)
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MuleSoft MCPA-Level-1-Maintenance 認定試験の出題範囲:
| トピック | 出題範囲 |
|---|
| トピック 1 | - Identify when redeployment of API implementations is necessary
- Compare unit and integration tests and specify where MUnit is best employed
|
| トピック 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
|
| トピック 3 | - Governing APIs on Anypoint Platform
- Select appropriate API policies to enforce non-functional constraints on API invocations
|
| トピック 4 | - Define and describe the benefits of API-led connectivity and application networks
- Explain MuleSoft’s proposal for closing the IT delivery gap
|
| トピック 5 | - Describe the metrics collected by Anypoint Platform for API invocations
- Specify alerts to define for key metrics of API invocations for all layers of API-led connectivity
|
| トピック 6 | - Describe the purpose and roles of a Center for Enablement (C4E)
- Describe the capabilities and high-level components of Anypoint Platform
|
| トピック 7 | - Break down functional requirements into business-aligned APIs with effective granularity
- Identify idempotent HTTP methods and HTTP-native support for optimistic concurrency
|
| トピック 8 | - Identify KPIs to measure the success of a C4E
- Select Anypoint Platform identity management vs client management for the correct purpose
|
参照:https://training.mulesoft.com/certification/architect-platform-level1-maintenance
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