* 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.