Correct Answer: Cache-aside (lazy loading) with a Time-To-Live (TTL) expiry on each cached entry
Cache-aside (lazy loading) with TTL is the standard pattern: check cache first; on miss, fetch from DB and store in cache with an expiry. The TTL ensures stale entries are automati...
Correct Answer
Cache-aside (lazy loading) with a Time-To-Live (TTL) expiry on each cached entry
Why This Answer Is Correct
Cache-aside (lazy loading) with TTL is the standard pattern: check cache first; on miss, fetch from DB and store in cache with an expiry. The TTL ensures stale entries are automatically evicted. It is flexible, language-agnostic, and prevents indefinite stale data without requiring write-through complexity.
This question evaluates your knowledge of Azure Cache for Redis — a core concept tested in Microsoft Certified: Azure Developer Associate (AZ-204). Understanding Azure Cache for Redis is essential for designing scalable, secure, and cost-effective cloud architectures. Mastery of this topic will help you answer scenario-based questions confidently on exam day.
You are implementing distributed session management for a horizontally scaled ASP.NET Core app using Azure Cache for Redis. After deployment, some users are getting logged out unexpectedly between requests. What is the most likely cause?
Your ASP.NET Core API queries the same product catalog data from SQL Database on every request. Under load, the database becomes a bottleneck with high DTU consumption. You want to add a caching layer that stores catalog data for 10 minutes and automatically refreshes stale data. Which implementation pattern should you use with Azure Cache for Redis?