How to Measure TTFT and Inter-Token Latency With Recorded Traffic
Record streamed LLM traffic with proxymock, replay it against a model server, and fail the run when TTFT, inter-token latency or token rates regress.
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Record streamed LLM traffic with proxymock, replay it against a model server, and fail the run when TTFT, inter-token latency or token rates regress.
Speedscale replays now measure AIPerf-defined TTFT, inter-token latency and token throughput on your recorded LLM traffic, next to what production measured.
AI writes code faster. Build autonomous verification with deterministic gates and LLM-powered tests to own reliability, scalability, and the consequences.
We searched our own API traffic for gRPC errors hiding behind HTTP 200 and found five dashboard bugs that showed an empty screen instead of an error.
Run recorded API mocks in GitHub Actions with proxymock. Use the existing Go demo, check response bodies, and connect the job to a reviewed replay baseline.
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Dark code is software no human has written, read, or reviewed. See what traffic replay can verify, its limits, and a working regression check.
API traffic replay testing guide with verified examples. Compare GoReplay, WireMock, Speedscale and proxymock, and see what a CI replay gate proves.
Use Speedscale's readiness scorecard to compare three API gateway builds on Kubernetes. Catch a broken endpoint, test a retry and gate CI on the verdict.