1Z0-997-25 Question 97
Single answerYou manage a high-traffic e-commerce platform on Oracle Cloud Infrastructure (OCI) that experiences frequent updates to product data (e.g., pricing and availability). To reduce the load on your primary database, you plan to leverage OCI Cache for faster reads. However, you also need to minimize the risk of serving stale product information. Which strategy best addresses both performance gains and data freshness for these frequently changing items?
- A
Implement a short Time to Live (TTL) for product data and use an event-driven invalidation mechanism whenever updates occur
- B
Set a long TTL (e.g., 24 hours) for product data to maximize cache hits across the day
- C
Flush the entire cache whenever a single product detail changes to ensure absolute consistency
- D
Disable TTL entirely and rely on manual cache purges when data is updated
Show answer and explanation
Correct answer: A
Explanation
Using OCI Cache effectively for dynamic data involves setting shorter TTLs for frequently updated content and utilizing event-driven or microservice-based triggers to invalidate or refresh specific cache entries as needed. This aligns with OCI best practices for balancing application performance (through caching) and data accuracy (via timely invalidation). Refer to the OCI documentation on cache invalidation strategies and distributed caching patterns for guidance on implementing and automating event-driven cache updates.
- A. Correct.
Correct. A short TTL ensures that cached data will not stay in the cache longer than necessary. An event-driven invalidation mechanism (for example, triggered by a change notification from the data store or a microservice event) further helps keep the cache synchronized with the latest product data. This approach balances performance benefits with data freshness requirements.
- B. Incorrect.
Incorrect. A 24-hour TTL risks serving outdated information for products that change multiple times within that period. While this might reduce cache misses, it does not adequately address rapidly changing pricing or availability data.
- C. Incorrect.
Incorrect. Flushing the entire cache on each product update guarantees fresh data but incurs significant performance overhead by invalidating all cached entries, not just the ones that changed. This approach reduces the overall benefit of caching.
- D. Incorrect.
Incorrect. Completely disabling TTL relies on manual intervention to remove stale data, which is error-prone and can lead to severely outdated information being served to customers.