How should this guide be used in engineering workflows?

Use it as an implementation checklist, then convert key controls into automated tests and runbooks.

What is the expected outcome after applying this guide?

Lower validation defects, clearer failure diagnostics, and more predictable file-processing behavior.

Large File Performance Benchmarking

Benchmark file ingest and processing performance with reproducible workloads.

performance video audio archive document

Benchmark Design Principles

Benchmarks should mirror production behavior: realistic concurrency, mixed file sizes, and representative format distribution. Synthetic single-file tests are useful but insufficient for capacity planning.

Warm and cold cache runs.
Single-region and cross-region network paths.
CPU-bound and IO-bound workload splits.

Metrics to Track

Use budget thresholds for each metric and fail builds when regressions exceed tolerance.

P50/P95/P99 ingest latency.
Worker queue time and processing duration.
Memory high-water mark and OOM events.
Error rate by format and size bucket.

Make Results Actionable

Report benchmark deltas in release notes, including suspected causes and mitigation actions. Performance testing only has value when it changes release decisions.

Recommended Tools

Upload Test Matrix Builder

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Manifest Diff

Diff two manifests to detect added, removed, or changed files.

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