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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing and Sharing APIs | 11% | - API Design Best Practices - Anypoint Exchange for Sharing Assets - API-Led Connectivity Approach |
| Topic 2: Architecting and Deploying API Implementations | 11% | - Mule Runtime Architecture - Disaster Recovery (DR) Strategies - High Availability (HA) Design |
| Topic 3: Applying Integration Patterns | 11% | - Integration Scenarios & Patterns - Batch Processing - Event-Driven Architecture (EDA) |
| Topic 4: Establishing Organizational and Platform Foundations | 17% | - Governance and Compliance Framework - IT Delivery & C4E Operating Model - Platform Foundation Setup |
| Topic 5: Understanding the MuleSoft Platform & Application Networks | 11% | - MuleSoft Anypoint Platform Core Concepts - C4E (Center for Enablement) Definition - Application Network Fundamentals |
| Topic 6: Managing APIs | 12% | - API Security (Policies, SLAs) - API Lifecycle Management - API Versioning |
| Topic 7: Deploying API Implementations to CloudHub | 11% | - CloudHub Architecture - Deployment Strategies - CloudHub 2.0 & Runtime Fabric |
| Topic 8: Monitoring and Analyzing Application Networks | 8% | - Analytics & Business Insights - Anypoint Monitoring Tools - Alerting & Auditing |
| Topic 9: Meeting API Quality Goals | 8% | - API Performance Optimization - Unit & Integration Testing - Resilience & Reliability Patterns |
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NEW QUESTION # 122
What Anypoint Connectors support transactions?
Answer: D
NEW QUESTION # 123
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?
Answer: C
Explanation:
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
NEW QUESTION # 124
When can CloudHub Object Store v2 be used?
Answer: B
Explanation:
CloudHub Object Store v2 is a managed key-value store provided by MuleSoft to support various use cases where temporary data storage is required. Here's why Option D is correct:
Key Length Support: Object Store v2 allows storage of keys with a length of up to 300 characters, making it suitable for applications needing flexible and descriptive keys.
Limitations on Size:
Object Store v2 is not intended for large payload storage and has a recommended size limit below 10 MB for each value. Payloads exceeding 15 MB may cause performance issues and are better suited to a file storage system or database.
Option B is incorrect because storing payloads above 15 MB exceeds Object Store's optimal usage specifications.
Key-Value Limits: Object Store v2 is designed for moderate, transient storage needs, and does not support unlimited storage. Thus, Option A is incorrect.
Backward Compatibility: Object Store v2 does not support Mule 4 applications running Object Store v1. Option C is incorrect as Object Store v1 and v2 are distinct.
Reference
For more on CloudHub Object Store v2, refer to MuleSoft documentation on Object Store limitations and configuration.
NEW QUESTION # 125
The Line of Business (LoB) of an eCommerce company is requesting a process that sends automated notifications via email every time a new order is processed through the customer's mobile application or through the internal company's web application. In the future, multiple notification channels may be added: for example, text messages and push notifications.
What is the most effective API-led connectivity approach for the scenario described above?
Answer: B
Explanation:
In this scenario, the best approach to satisfy the API-led connectivity principles and support future scalability is:
Experience APIs:
Create separate Experience APIs for the web application and the mobile application. This allows each application to have an optimized interface, supporting different needs and potential differences in request/response structures or security configurations.
Process API:
A single Process API can be used to orchestrate the workflow, including retrieving the email template from a database and preparing the email content. By centralizing this logic in the Process layer, we can ensure it is reusable and easily adaptable for different notification channels in the future.
System API:
A System API specifically designed for sending emails (using the Anypoint Connector for Email) abstracts the email-sending functionality from the business logic. This approach ensures that the email-sending function is reusable and scalable, and it can easily be extended or modified if other notification channels (like SMS or push notifications) are added later.
Why Option A is Correct:
This structure aligns with API-led connectivity principles by separating concerns across Experience, Process, and System layers. It provides flexibility for future notification channels and isolates each layer's responsibility, making it easier to maintain and scale.
of Incorrect Options:
Option B lacks a separate System API for sending emails, which goes against the principle of isolating back-end functionality in System APIs.
Option C similarly lacks a dedicated System API, reducing flexibility and reusability.
Option D suggests creating multiple Process APIs for database retrieval, which adds unnecessary complexity and does not adhere to the single-orchestration principle typically followed in API-led design.
Reference
For further guidance on API-led connectivity and the responsibilities of each API layer, refer to MuleSoft's documentation on API-led architecture and design best practices.
NEW QUESTION # 126
What CANNOT be effectively enforced using an API policy in Anypoint Platform?
Answer: B
Explanation:
Correct Answe r: Guarding against Denial of Service attacks
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>> Backend system overloading can be handled by enforcing "Spike Control Policy"
>> Logging HTTP requests and responses can be done by enforcing "Message Logging Policy"
>> Credentials can be tamper-proofed using "Security" and "Compliance" Policies However, unfortunately, there is no proper way currently on Anypoint Platform to guard against DOS attacks.
NEW QUESTION # 127
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