Question 950
A SaaS platform needs economical database isolation. The team confirms that storage costs rise because tenant audit histories are retained indefinitely. Which AWS architecture decision should be prioritized?
Explanation
Correct Answer
The scenario identifies this requirement: Storage costs rise because tenant audit histories are retained indefinitely. Select Implement compliant tiering and expiration for historical records as the specified technical mechanism. Data lifecycle policies control unbounded growth. This response addresses the problem described rather than a different design goal.
Incorrect Answers
Enforce tenant-scoped database authorization and key-based access would help if a shared table filters tenants only in app memory after querying all records. Safe multitenancy requires robust data-level boundaries. That is not the symptom described here: storage costs rise because tenant audit histories are retained indefinitely. The matching response is Implement compliant tiering and expiration for historical records, because data lifecycle policies control unbounded growth.
For the alternative failure customers' usage swings unpredictably throughout the day, the control Consider Aurora Serverless v2 or DynamoDB on-demand where workload semantics fit is relevant: elastic pricing aligns capacity with variable demand. Here the evidence instead is storage costs rise because tenant audit histories are retained indefinitely. The selected technical mechanism is Implement compliant tiering and expiration for historical records: data lifecycle policies control unbounded growth.
Keep dedicated databases/accounts according to compliance rather than pooling solves a different operational problem where tenants require physical data separation by legal contract. Isolation requirements override cost optimization. It does not directly address storage costs rise because tenant audit histories are retained indefinitely. The case calls for Implement compliant tiering and expiration for historical records, since data lifecycle policies control unbounded growth.