New Cloud Run service writes to Cloud Spanner. Validate it supports 5,000 reads/s and 1,000 writes/s, identify bottlenecks, and use autoscaling test infrastructure. What test setup do you use?

The correct answer is to use a Google Kubernetes Engine (GKE) cluster with tools like Locust or JMeter. GKE provides a scalable and flexible environment to generate high-volume, distributed load tests, which is essential for validating performance targets like 5,000 reads/s and 1,000 writes/s, and for identifying bottlenecks in a Cloud Run service. Cloud Trace is ideal for analyzing these results as it provides detailed, end-to-end latency breakdowns across services, helping pinpoint performance issues. Building a test harness on Cloud Run might not generate sufficient load and VPC Flow Logs are for network traffic, not application performance. Cloud Tasks and Cloud Scheduler are for asynchronous task execution, not for generating synchronous, high-throughput load tests. A single Compute Engine instance with Apache Bench is unlikely to generate the required distributed load and may itself become a bottleneck.