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Difficulty: MediumDesigning Infrastructure for Business Requirements and Cost Optimization

An automotive manufacturer is implementing a vehicle telemetry diagnostics endpoint deployed within a single Google Cloud region (us−east4us-east4). 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?

  1. Deploy the stateless REST API on Cloud Run and store relational data in Cloud SQL for PostgreSQL.Answer
  2. B
    Deploy the stateless REST API on a regional Google Kubernetes Engine (GKE) cluster and store relational data in Cloud Spanner.
  3. C
    Deploy 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.
  4. D
    Provision Compute Engine virtual machines using 3-year Committed Use Discounts (CUDs) behind a Load Balancer and store relational data in Cloud SQL for PostgreSQL.

Answer

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 (us−east4us-east4) without the overhead or expense of multi-region database systems.

Step-by-Step Solution

1
Analyze the compute workload characteristics and business cost requirements.
The API is stateless with variable traffic and long idle periods overnight.
Serverless compute platforms like Cloud Run scale to zero instances, eliminating idle compute costs, whereas GKE clusters or Compute Engine VMs maintain baseline costs.
2
Evaluate data storage requirements against cost and architecture constraints.
The application requires a standard relational database operating within a single Google Cloud region (us−east4us-east4).
Cloud SQL for PostgreSQL satisfies single-region relational database needs at a significantly lower baseline cost than Cloud Spanner, which is optimized for multi-region global consistency.
3
Combine compute and storage choices to form the optimal cloud solution architecture.
Cloud Run paired with Cloud SQL for PostgreSQL offers minimal operational overhead and optimal cost efficiency.
This combination minimizes total cost of ownership while fully meeting functional business requirements.

Key Concept

Selecting serverless compute and appropriate regional relational storage to optimize cost for bursty workloads with idle periods.
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Topics

Designing Infrastructure for Business Requirements and Cost Optimization