PROFESSIONAL-CLOUD-DEVELOPER · Question #322
Your ecommerce application has a rapidly growing user base, and it is experiencing performance issues due to excessive requests to your backend API. Your team develops and manages this API. The…
The correct answer is A. Use Apigee to expose your API. Use Memorystore for Redis to cache frequently accessed data. The root cause is excessive requests reaching Cloud SQL. The two-part fix is: (1) a proper API gateway layer and (2) a caching layer to absorb repeated reads. Apigee provides enterprise API management (traffic control, monitoring, developer portal) and sits in front of the…
Question
Your ecommerce application has a rapidly growing user base, and it is experiencing performance issues due to excessive requests to your backend API. Your team develops and manages this API. The Cloud SQL backend database is struggling to handle the high demand, leading to latency and timeouts. You need to implement a solution that optimizes API performance and improves user experience. What should you do?
Options
- AUse Apigee to expose your API. Use Memorystore for Redis to cache frequently accessed data.
- BUse Apigee to expose your API. Implement rate limiting and access control policies in Apigee to
- CUse Cloud Load Balancing to expose your API. Use Cloud CDN in front of the load balancer to
- DUse Cloud Load Balancing to expose your API. Increase the memory for the database instances
How the community answered
(30 responses)- A83% (25)
- B3% (1)
- C10% (3)
- D3% (1)
Explanation
The root cause is excessive requests reaching Cloud SQL. The two-part fix is: (1) a proper API gateway layer and (2) a caching layer to absorb repeated reads. Apigee provides enterprise API management (traffic control, monitoring, developer portal) and sits in front of the backend. Memorystore for Redis provides an in-memory cache so frequently requested data is served without hitting Cloud SQL at all. Option B adds rate limiting but does not reduce database load for legitimate requests. Cloud CDN (C) caches static/HTTP responses but is not designed for dynamic API caching. Increasing database memory (D) treats a symptom rather than the cause and is not scalable.
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