A smart utility company is architecting a new RESTful microservice on Google Cloud to collect and validate incoming telemetry data from millions of smart electric meters. The HTTP payload handling is entirely stateless, containerized, and experiences unpredictable traffic spikes throughout the day, dropping to near-zero volume overnight. The engineering team prioritizes minimizing operational maintenance, avoiding idle capacity charges, and deploying without managing underlying server infrastructure or Kubernetes cluster configurations. Which compute platform should the Cloud Architect recommend?
- Deploy the containerized service on Cloud Run.Answer
- BProvision a Standard Google Kubernetes Engine (GKE) cluster with an Autopilot node pool.
- CDeploy the service on a Compute Engine Managed Instance Group (MIG) backed by 1-year Committed Use Discounts.
- DDeploy the application to Compute Engine virtual machines configured with CPU-based autoscaling policies.
Answer
Deploying the containerized service on Cloud Run is the optimal architecture choice.
Deploying on Cloud Run is correct because it directly executes stateless containers in a fully managed serverless environment. It automatically handles scaling up for incoming traffic bursts and scaling down to zero when there are no incoming HTTP requests, fulfilling the requirement of zero idle costs and zero cluster maintenance.
Step-by-Step Solution
Key Concept
Selecting serverless compute vs. cluster-based compute for stateless web workloads