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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Architecting and Deploying API Implementations | 11% | - Runtime architecture and deployment options - High availability and fault tolerance - Networking and security configuration - CI/CD and DevOps integration |
| Topic 2: Managing APIs | 12% | - API lifecycle management - Versioning and deprecation strategies - API policies and security enforcement - Rate limiting and throttling |
| Topic 3: Deploying API Implementations to CloudHub | 11% | - Worker sizing and resource planning - CloudHub architecture and capabilities - Deployment optimization and scaling - VPC and private space configuration |
| Topic 4: Monitoring and Analyzing Application Networks | 8% | - Analytics and insight generation - Logging and alerting configuration - Operational visibility and optimization - Monitoring strategies and tools |
| Topic 5: Designing and Sharing APIs | 11% | - API layering: Experience, Process, System APIs - Asset sharing and reuse via Anypoint Exchange - API specification and documentation - API design standards and best practices |
| Topic 6: Meeting API Quality Goals | 8% | - Maintainability and testability - Security and compliance standards - Performance and latency requirements - Reliability and availability targets |
| Topic 7: Applying Integration Patterns | 11% | - Scalability and performance patterns - Error handling and reliability patterns - Common integration patterns and use cases - Event-driven and synchronous integration |
| Topic 8: Establishing Organizational and Platform Foundations | 17% | - Anypoint Platform architecture and components - Governance and organizational structure - Center for Enablement (C4E) operating model - Platform strategy and roadmap definition |
| Topic 9: Explaining Application Network Basics | 11% | - Benefits of modern API design - API-led connectivity principles - Core concepts of application networks |
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問題 #119
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?
答案：A
解題說明：
Correct Answe r: 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
問題 #120
How are an API implementation, API client, and API consumer combined to invoke and process an API?
答案：A
解題說明：
Correct Answe r: The API consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation
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Terminology:
>> API Client - It is a piece of code or program the is written to invoke an API
>> API Consumer - An owner/entity who owns the API Client. API Consumers write API clients.
>> API - The provider of the API functionality. Typically an API Instance on API Manager where they are managed and operated.
>> API Implementation - The actual piece of code written by API provider where the functionality of the API is implemented. Typically, these are Mule Applications running on Runtime Manager.
問題 #121
Which layer in the API-led connectivity focuses on unlocking key systems, legacy systems, data sources etc and exposes the functionality?
答案：C
解題說明：
Correct Answe r: System Layer
The APIs used in an API-led approach to connectivity fall into three categories:
System APIs - these usually access the core systems of record and provide a means of insulating the user from the complexity or any changes to the underlying systems. Once built, many users, can access data without any need to learn the underlying systems and can reuse these APIs in multiple projects.
Process APIs - These APIs interact with and shape data within a single system or across systems (breaking down data silos) and are created here without a dependence on the source systems from which that data originates, as well as the target channels through which that data is delivered.
Experience APIs - Experience APIs are the means by which data can be reconfigured so that it is most easily consumed by its intended audience, all from a common data source, rather than setting up separate point-to-point integrations for each channel. An Experience API is usually created with API-first design principles where the API is designed for the specific user experience in mind.
問題 #122
A Platform Architect inherits a legacy monolithic SOAP-based web service that performs a number of tasks, including showing all policies belonging to a client. The service connects to two back-end systems - a life-insurance administration system and a general-insurance administration system - and then queries for insurance policy information within each system, aggregates the results, and presents a SOAP-based response to a user interface (UI).
The architect wants to break up the monolithic web service to follow API-led conventions.
Which part of the service should be put into the process layer?
答案：C
解題說明：
In the API-led connectivity approach, each layer (System, Process, and Experience) has a distinct purpose:
System APIs: These APIs connect directly to backend systems to expose and unlock data in a standardized way.
Process APIs: These are responsible for orchestrating and processing data across different systems, combining information where needed.
Experience APIs: These are designed for specific user interfaces or applications, often transforming data formats to fit the needs of each consumer application.
Why Option A is Correct:
Process APIs are designed to combine data from multiple systems, which aligns with the function of aggregating policy information from both the life and general insurance systems. This aggregation logic would ideally reside in the Process layer, separating data retrieval from data orchestration.
Moving this functionality to the Process layer enables reusability and modularity, as other Experience APIs or services could also leverage the combined policy data if needed.
of Incorrect Options:
Option B (Presenting the SOAP-based response) would be managed by the Experience layer, as this layer adapts data formats for specific interfaces.
Option C (Authenticating and maintaining backend connections) would typically be handled within the System layer, where backend integration and security handling occurs.
Option D (Querying data) is the function of System APIs, which access the backend systems directly and expose the raw data without additional processing.
Reference
For further details on API-led architecture and the roles of each layer, refer to MuleSoft's documentation on API-led connectivity and API layers.
問題 #123
A company is using an on-prem cluster in the data center as a runtime plane and MuleSoft-hosted control plane.
How can the company monitor the detailed performance metrics on the Mule applications deployed to the cluster from the control plane?
答案：D
解題說明：
Monitoring On-Premise Mule Applications:
For Mule applications deployed on an on-premises cluster, monitoring detailed performance metrics requires communication with the MuleSoft-hosted control plane. The control plane, when used with on-premises runtimes, relies on Anypoint Monitoring and requires a Monitoring Agent to gather and send detailed performance metrics.
Setting Up Monitoring:
To enable detailed metrics, the Monitoring Agent must be installed on each node in the cluster where Mule applications are deployed. This agent collects data on memory usage, CPU load, response times, and other metrics, and sends it to the control plane for aggregation and visualization.
Evaluating the Options:
Option A: Updating settings in the control plane alone does not enable detailed monitoring; the agent must be installed on each node to capture detailed metrics.
Option B (Correct Answer): Installing the Monitoring Agent on each node ensures that each runtime node in the cluster can send its metrics to the control plane, enabling detailed monitoring.
Option C: Installing the agent on a separate server would not be effective, as each node in the cluster needs to independently report its metrics to ensure full visibility.
Option D: The on-prem runtime does not automatically send detailed metrics to the control plane without the Monitoring Agent installed.
Conclusion:
Option B is the correct answer, as installing the Monitoring Agent on each node is essential for detailed performance monitoring of on-prem applications in a cluster.
Refer to MuleSoft's documentation on configuring Anypoint Monitoring for on-premises deployments and using the Monitoring Agent.
問題 #124
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