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

According to the Google Cloud Architecture Framework for modernizing applications, Google Kubernetes Engine (GKE) is the most suitable compute platform for services requiring high scalability and availability. Cymbal’s AI-powered virtual agents must handle " anticipated growth " and fluctuating customer demands from their web and mobile apps. GKE’s Horizontal Pod Autoscaler (HPA) and Cluster Autoscaler ensure that the compute resources expand automatically during peak shopping hours and shrink during low-traffic periods to " minimize costs. "

GKE is explicitly mentioned in Cymbal’s " Existing Technical Environment " as their preferred platform for containerized applications. Leveraging GKE for the virtual agents allows the development team to use a microservices approach, isolating the agent ' s logic from other catalog enrichment tasks. Option D (Single large VM) is a " legacy " approach that creates a single point of failure and does not scale efficiently. Option A (Cloud SQL) is a database service, not a compute resource for running agent logic. While Vertex AI Agent Builder (Option B) is the tool used to create the agents, the underlying compute that hosts the integrated application and handles the traffic orchestration is best served by a managed Kubernetes environment like GKE, which aligns with their requirement for " Scalability and Performance. "