Currently Tusk Drift focuses on functional/regression testing - we mock outbound dependencies (DBs, external APIs) for determinism, so we're not measuring real-world performance characteristics today.
That said, we're also exploring extending it for capacity modeling and resource estimation, which would be a differentiated approach from traditional load testing. Synthetic benchmarks fail to capture how traffic patterns (not just volume) affect resource usage. Since we already record real production traffic, we're uniquely positioned to:
1. Replay specific time periods (e.g., last year's Black Friday sale)
2. Preserve the natural distribution of request types
3. Control downstream latency via our mock system
4. Build models beyond linear regression for QPS -> CPU/mem prediction
What performance testing use case did you have in mind? We're actively exploring this space.
Comments
Currently Tusk Drift focuses on functional/regression testing - we mock outbound dependencies (DBs, external APIs) for determinism, so we're not measuring real-world performance characteristics today.
That said, we're also exploring extending it for capacity modeling and resource estimation, which would be a differentiated approach from traditional load testing. Synthetic benchmarks fail to capture how traffic patterns (not just volume) affect resource usage. Since we already record real production traffic, we're uniquely positioned to:
1. Replay specific time periods (e.g., last year's Black Friday sale)
2. Preserve the natural distribution of request types
3. Control downstream latency via our mock system
4. Build models beyond linear regression for QPS -> CPU/mem prediction
What performance testing use case did you have in mind? We're actively exploring this space.