For this question, refer to the Cymbal Retail case study.

A "cloud-first" modernization strategy for a retail product catalog typically involves moving from legacy relational databases to high-performance, managed services. AlloyDB for PostgreSQL is Google Cloud's premier choice for demanding transactional workloads. It offers superior performance (up to 4x faster than standard PostgreSQL) and built-in high availability, making it ideal for the low-latency requirements of web applications and AI virtual agents.

Option A follows the architecturally sound pattern of separating structured data from unstructured assets. Cloud Storage is the industry standard for storing "product images," providing massive scalability, high availability, and low cost through lifecycle management.

Option B is less ideal because Bigtable is not designed for storing binary image blobs efficiently, and Spanner can be significantly more expensive and complex to manage if global multi-region consistency is not a strict requirement for the "minimizing operational costs" goal. Option C is incorrect because Filestore (NFS) is not a suitable primary database for a modern web application catalog. Option D is technically flawed as Cloud Storage is not an efficient primary database for structured application queries, and BigQuery is an analytical warehouse, not an image store. By combining AlloyDB and Cloud Storage, Cymbal achieves a performant, scalable, and cost-optimized foundation for their digital transformation.