What should you configure in your application to investigate performance issues with downstream dependencies?

Configuring Cloud Trace for tracking request latency is essential for investigating performance issues with downstream dependencies because it provides a detailed view of how requests traverse through different services and components within your application. By capturing latency data, you can pinpoint bottlenecks and understand how long requests spend in the different stages of processing. This information is critical when evaluating the performance of downstream services, as you'll be able to see where delays are occurring, whether in the application itself or the interaction with external services.

Cloud Trace collects distributed traces of requests and visualizes the latency, allowing you to identify which particular requests or operations are causing slowdowns. This visibility is vital for diagnosing issues effectively because it helps teams decide where to focus their optimization efforts.

In contrast, enabling Error Reporting primarily focuses on capturing and aggregating error logs, which is important for identifying failures but does not provide insights into performance or request timing. Utilizing Managed Service for Prometheus is relevant for metrics collection and monitoring but does not directly address request latency analysis. Setting up Cloud Profiler helps optimize code performance but is not designed specifically for tracking request latencies across service boundaries, which is crucial in understanding downstream dependency performance.