rdc-optimizer

You can structure performance optimization requests by providing captures, traces, profiles, A/B data, or dashboards alongside your performance goals to generate bottleneck attributions, optimization proposals, or experiment designs for validation.

The best way to attribute a latency bottleneck using A/B data is to intake the A/B data with your target metrics and acceptable budgets to produce a structured attribution and experiment design validating the optimization gains.

Yes, you can use telemetry artifacts like captures and traces to design experiments for validating optimization gains by clarifying the scope, target metrics, and expected outputs to produce a structured experiment plan.

Yes, this approach works for early-stage optimizer workflows without a production-grade platform by enforcing scope and distinguishing optimization responsibilities from debugging workflows to avoid assuming a verification loop.

You should not use this structured intake for debugging workflows or if you require a production-grade verification loop, as it focuses specifically on early-stage bottleneck attribution and experiment design rather than debugging.