An automotive manufacturer is implementing a vehicle telemetry diagnostics endpoint deployed within a single Google Cloud region (). The service accepts incoming HTTP REST webhooks from connected vehicles to log maintenance metrics into a standard relational database. Telemetry traffic is highly variable, experiencing sudden traffic surges during morning rush hours and long periods of near-zero activity overnight. Which architectural design meets the availability and regional relational storage requirements while minimizing overall cost and operational overhead?
- Deploy the stateless REST API on Cloud Run and store relational data in Cloud SQL for PostgreSQL.Cevap
- BDeploy the stateless REST API on a regional Google Kubernetes Engine (GKE) cluster and store relational data in Cloud Spanner.
- CDeploy the stateless REST API on a GKE Standard cluster maintaining a minimum of three worker nodes and store relational data in Cloud SQL for PostgreSQL.
- DProvision Compute Engine virtual machines using 3-year Committed Use Discounts (CUDs) behind a Load Balancer and store relational data in Cloud SQL for PostgreSQL.
Cevap
Deploying the stateless REST API on Cloud Run combined with Cloud SQL for PostgreSQL as the relational storage layer.
Deploying the API on Cloud Run paired with Cloud SQL for PostgreSQL directly aligns compute and storage resources with business cost requirements. Cloud Run automatically scales to zero instances when vehicle traffic drops overnight, eliminating idle compute expenses. Cloud SQL provides a fully managed relational database within a single region () without the overhead or expense of multi-region database systems.
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Selecting serverless compute and appropriate regional relational storage to optimize cost for bursty workloads with idle periods.