Answer: Ensure that the load tests validate the performance of Cloud Bigtable, Create a separate Google Cloud project to use for the load-testing environment, Instrument the load-testing tool and the target services with detailed logging and metrics collection

Based on the community discussion and Google Cloud best practices, the correct answers are A, B, and F. Option A is essential because Cloud Bigtable, while managed, requires proper capacity planning and performance validation under load to ensure it meets application needs, as highlighted in Google's documentation and supported by comments emphasizing the need to test typical workloads. Option B is crucial for isolation, preventing interference with production resources, managing quotas separately, and avoiding accidental impacts, which is a widely accepted best practice. Option F is necessary for visibility and diagnostics during testing, enabling the collection of metrics and logs to analyze performance and identify bottlenecks. Option C is incorrect as running load tests against production is risky and not recommended. Option D is less relevant as the focus is on testing the primary cloud services, not necessarily third-party systems, and it may not apply to all scenarios. Option E is not ideal because recording every transaction in production for replay is unnecessary for load testing, which focuses on simulating load rather than exact transaction replay, and it could introduce performance overhead in production.

Author: LeetQuiz Editorial Team