A telecommunications enterprise is migrating an event processing platform to Google Cloud. The application processes bursty telemetry data during a 6-hour daily peak window and relies on a stateless containerized worker layer. Operational metadata requires a regional relational database with high availability and transactional consistency. The primary business requirement is to minimize total cost of ownership (TCO) and eliminate idle compute spending without introducing unnecessary management complexity. Which TWO architectural decisions should you combine to meet these requirements? (Select TWO.)
- Deploy the stateless containerized worker workload using Cloud Run to automatically scale instances to zero outside peak hours.Answer
- Provision Cloud SQL configured with regional High Availability (HA) for storing operational metadata.Answer
- CDeploy the stateless worker workload on a Google Kubernetes Engine (GKE) Standard cluster with fixed multi-zone node pools running continuously.
- DProvision a multi-region Cloud Spanner instance to store operational metadata.
Answer
Deploy the stateless containerized worker workload using Cloud Run, and provision Cloud SQL configured with regional High Availability (HA) for storing operational metadata.
Combining Cloud Run with Cloud SQL HA minimizes total cost of ownership. Cloud Run automatically scales to zero when event traffic drops outside the daily 6-hour window, preventing idle compute expenses. Cloud SQL configured for regional high availability fulfills relational database requirements with automated failover at a fraction of the cost of globally distributed database services.
Step-by-Step Solution
Key Concept
Cost-optimized architectural design using serverless compute (Cloud Run) and right-sized relational database selection (Cloud SQL HA vs Cloud Spanner)