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| Section | Weight | Objectives |
|---|---|---|
| Meeting API Quality Goals | 8% | - API Performance Optimization - Unit & Integration Testing - Resilience & Reliability Patterns |
| Designing and Sharing APIs | 11% | - API Design Best Practices - API-Led Connectivity Approach - Anypoint Exchange for Sharing Assets |
| Managing APIs | 12% | - API Lifecycle Management - API Versioning - API Security (Policies, SLAs) |
| Deploying API Implementations to CloudHub | 11% | - CloudHub Architecture - Deployment Strategies - CloudHub 2.0 & Runtime Fabric |
| Architecting and Deploying API Implementations | 11% | - Disaster Recovery (DR) Strategies - High Availability (HA) Design - Mule Runtime Architecture |
| Applying Integration Patterns | 11% | - Event-Driven Architecture (EDA) - Integration Scenarios & Patterns - Batch Processing |
| Establishing Organizational and Platform Foundations | 17% | - Platform Foundation Setup - IT Delivery & C4E Operating Model - Governance and Compliance Framework |
| Understanding the MuleSoft Platform & Application Networks | 11% | - Application Network Fundamentals - MuleSoft Anypoint Platform Core Concepts - C4E (Center for Enablement) Definition |
| Monitoring and Analyzing Application Networks | 8% | - Analytics & Business Insights - Anypoint Monitoring Tools - Alerting & Auditing |
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NEW QUESTION # 114
When designing an upstream API and its implementation, the development team has been advised to NOT set timeouts when invoking a downstream API, because that downstream API has no SLA that can be relied upon. This is the only downstream API dependency of that upstream API.
Assume the downstream API runs uninterrupted without crashing. What is the impact of this advice?
Answer: A
Explanation:
Correct Answe r: An SLA for the upstream API CANNOT be provided.
*****************************************
>> First thing first, the default HTTP response timeout for HTTP connector is 10000 ms (10 seconds). NOT 500 ms.
>> Mule runtime does NOT apply any such "load-dependent" timeouts. There is no such behavior currently in Mule.
>> As there is default 10000 ms time out for HTTP connector, we CANNOT always guarantee that the invocation of the downstream API will run to completion without timing out due to its unreliable SLA times. If the response time crosses 10 seconds then the request may time out.
The main impact due to this is that a proper SLA for the upstream API CANNOT be provided.
NEW QUESTION # 115
Which out-of-the-box key performance indicator measures the success of a typical Center for Enablement and is immediately available in responses from Anypoint Platform APIs?
Answer: B
Explanation:
Center for Enablement (C4E) KPIs:
A Center for Enablement (C4E) in MuleSoft focuses on enabling self-service and reuse by providing APIs that can be consumed across the organization. A key metric of success is how many consumers are utilizing the published APIs.
The number of consumers who have requested and received access to an API indicates the level of adoption and reuse, which aligns with the goals of a C4E.
Evaluating the Options:
Option A: This metric could indicate deployment automation, but it is not a direct measure of C4E's success in enabling API reuse and consumption.
Option B: Bandwidth usage per API implementation provides insight into API traffic but does not measure C4E enablement or consumer engagement.
Option C: The number of developers downloading an API specification can be an indicator of interest but does not confirm actual usage or enablement.
Option D (Correct Answer): The number of consumers who have requested and received access to an API in production is a key metric indicating API adoption and reuse, which aligns with C4E's goals.
Conclusion:
Option D is the correct answer as it provides a direct measure of consumer engagement and adoption, indicating the success of the C4E in promoting API usage across the organization.
Refer to MuleSoft's documentation on C4E KPIs and API usage metrics for additional insights.
NEW QUESTION # 116
An API implementation is updated. When must the RAML definition of the API also be updated?
Answer: C
Explanation:
Correct Answe r: When the API implementation changes the structure of the request or response messages
*****************************************
>> RAML definition usually needs to be touched only when there are changes in the request/response schemas or in any traits on API.
>> It need not be modified for any internal changes in API implementation like performance tuning, backend system migrations etc..
NEW QUESTION # 117
4A developer for a transportation organization is implementing exactly one processing functionality in a Reservation Mule application to process and store passenger records. This Reservation application will be deployed to multiple CloudHub workers/replicas. It is possible that several external systems could send duplicate passenger records to the Reservation application.
An appropriate storage mechanism must be selected to help the Reservation application process each passenger record exactly once as much as possible. The selected storage mechanism must be shared by all the CloudHub workers/replicas in order to synchronize the state information to assist attempting exactly once processing of each passenger record by the deployed Reservation Mule application.
Which type of simple storage mechanism in Anypoint Platform allows the Reservation Mule application to update and share data between the CloudHub workers/replicas exactly once, with minimal development effort?
Answer: A
Explanation:
Processing Requirements and Storage Mechanism:
The Reservation Mule application will be deployed to multiple CloudHub workers/replicas, meaning that each worker must share state information to handle records exactly once. This requires a shared storage mechanism where state can be stored and accessed by multiple instances to avoid duplicate processing of the same records.
A Persistent Object Store in Anypoint Platform can be used to store records in a way that is accessible across multiple workers, providing a reliable mechanism for "exactly once" processing.
Evaluating the Options:
Option A (Correct Answer): A Persistent Object Store is designed to retain data across different application instances and can be shared by all workers on CloudHub. It helps achieve idempotency by ensuring that a record is processed exactly once.
Option B: Runtime Fabric Object Store is used for applications deployed in Anypoint Runtime Fabric, not CloudHub. This option would not be compatible with the CloudHub deployment.
Option C: A Non-persistent Object Store does not retain data across application restarts or different instances, making it unsuitable for the requirement of synchronized storage for exactly-once processing.
Option D: An In-memory Mule Object Store is local to each worker and is not shared across instances, so it does not meet the requirement for a shared storage mechanism accessible to all CloudHub workers.
Conclusion:
Option A is the correct answer, as a Persistent Object Store allows data sharing across multiple CloudHub workers, enabling them to synchronize and achieve "exactly once" processing of passenger records with minimal development effort.
Refer to MuleSoft's documentation on Object Store configurations and usage for best practices on handling state across distributed instances.
NEW QUESTION # 118
An eCommerce company is adding a new Product Details feature to their website, A customer will launch the product catalog page, a new Product Details link will appear by product where they can click to retrieve the product detail description. Product detail data is updated with product update releases, once or twice a year, Presently the database response time has been very slow due to high volume.
What action retrieves the product details with the lowest response time, fault tolerant, and consistent data?
Answer: A
Explanation:
Scenario Analysis:
The eCommerce company's Product Details feature requires low response time and consistent data for a feature where data rarely changes (only once or twice a year).
The database response time is slow due to high volume, so querying the database directly on each request would lead to poor performance and higher response times.
Optimal Solution Requirements:
Low Response Time: Data retrieval should be fast and not depend on database performance.
Fault Tolerance and Data Consistency: Cached or stored data should be consistent and resilient in case of database unavailability, as the product details data changes infrequently.
Evaluating the Options:
Option A: Using a Cache scope would temporarily store the product details in memory, which could improve performance but might not be suitable for infrequent updates (only twice a year), as cache expiration policies typically require shorter durations.
Option B: Storing product details in Anypoint MQ and then retrieving it through a subscriber is not suitable for this use case. Anypoint MQ is better for messaging rather than as a data storage mechanism.
Option C (Correct Answer): Using an object store to store and retrieve product details is ideal. Object stores in MuleSoft are designed for persistent storage of key-value pairs, which allows storing data retrieved from the database initially. This provides quick, consistent access without querying the database on every request, aligning with requirements for low response time, fault tolerance, and data consistency.
Option D: Selecting data directly from the database for each request would not meet the performance requirement due to known slow response times from the database.
Conclusion:
Option C is the best answer, as using an object store allows caching the infrequently updated product details. This approach reduces the dependency on the database, significantly improving response time and ensuring consistent data.
Refer to MuleSoft documentation on Object Store v2 and best practices for data caching to implement this solution effectively.
NEW QUESTION # 119
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