You are migrating third-party applications from optimized on-premises virtual machines to Google Cloud. You are unsure about the optimum CPU and memory options. The applications have a consistent usage pattern across multiple weeks. You want to optimize resource usage for the lowest cost. What should you do?

The correct answer leverages Google Cloud's Rightsizing Recommendations, which analyze actual usage data to suggest optimal CPU and memory configurations, directly addressing the goal of optimizing resource usage for the lowest cost. Starting with a configuration similar to on-premises ensures a baseline for performance, and running a load test with normal traffic provides realistic data for the recommendations. Installing the Cloud Monitoring agent is crucial for collecting the necessary metrics. The first incorrect option, using an instance template with the smallest machine type and autoscaling, might lead to performance issues if the smallest type is insufficient, and while autoscaling helps, it doesn't directly optimize the individual instance size for cost. The second incorrect option, App Engine flexible environment, is a platform-as-a-service (PaaS) solution, which might be an option for migration but doesn't directly address the specific need to determine optimal CPU/memory for an existing third-party application with unknown requirements in a cost-optimized way. The third incorrect option, creating multiple instances and running a high-traffic load test, is an expensive and potentially complex approach to determine optimal settings, and high traffic might not reflect the "consistent usage pattern" mentioned.