--- title: "Prepare shared test inputs once" description: "Produce or download common test inputs once and pass them to the jobs that consume them." url: https://starsling.dev/ci-playbooks/techniques/reuse-shared-test-inputs canonicalUrl: https://starsling.dev/ci-playbooks/techniques/reuse-shared-test-inputs --- # Prepare shared test inputs once Produce or download common test inputs once and pass them to the jobs that consume them. ## How to choose an approach Compare the examples by repository setup, prerequisites, and risks before adopting one. Each company implemented this in its own environment; measure each change against your own baseline. - **[Mastra](https://starsling.dev/ci-playbooks/mastra#publish-once)**: Use it when Independent fixture tests repeat the same package publishing and registry preparation. Check before adopting: The producer becomes a shared dependency. Compare its latency plus artifact transfer against repeated work; bind artifacts to the same commit and platform, preserve trust and never fall back silently to public packages. - **[Stripe](https://starsling.dev/ci-playbooks/stripe#handoff-shared-test-inputs)**: Use it when Many jobs independently download identical versioned fixtures. Check before adopting: A producer job adds a serial step and transfer time, so a very small download can stay in each job. Keep fixture identity and version selection exact. ## Apply this technique ````text Evaluate and apply this CI technique to my repository: Prepare shared test inputs once. Produce or download common test inputs once and pass them to the jobs that consume them. Read the technique and its source-backed company examples: https://starsling.dev/ci-playbooks/techniques/reuse-shared-test-inputs.md Inspect this repository’s CI workflows, build and test commands, dependencies, and recent run timings. Identify where this technique applies and explain the expected benefit using this repository’s evidence. Measure a baseline from recent comparable runs: elapsed time, queue time, runner minutes and failures where available. If data is unavailable, say what cannot be measured. Compare relevant company approaches, checking prerequisites, platform differences and tradeoffs. Rank applicable options by evidence, fit and measurable opportunity; do not present company results as predictions for this repo. Recommend the smallest safe change, show what checks and fallback paths remain, and ASK ME WHICH CHANGE TO APPROVE BEFORE EDITING ANY FILES. Only after approval, work on a new feature branch, make one reversible change, and open a reviewable pull request. Never merge or push to a default or protected branch. Keep required checks, test coverage, deployment and release behavior intact. Validate the change and compare equivalent runs where possible; report limitations and what should be monitored after merge. ```` ## How companies used this technique Read what each company changed and follow the original sources. ### Mastra: Publish test packages once and hand off the registry Mastra introduced a producer job that publishes required local packages to Verdaccio storage, uploads it, and lets each consumer job download and serve that snapshot. Evidence: Source PR/commit evidence Use it when: Independent fixture tests repeat the same package publishing and registry preparation. Before applying it: The producer becomes a shared dependency. Compare its latency plus artifact transfer against repeated work; bind artifacts to the same commit and platform, preserve trust and never fall back silently to public packages. [Read more in the Mastra playbook](https://starsling.dev/ci-playbooks/mastra#publish-once) [Primary source](https://github.com/mastra-ai/mastra/pull/18821) ### Stripe: Download shared test inputs once Stripe .NET moved its OpenAPI spec and fixture download into one job and passes them to every matrix test job as an artifact, so all lanes test against the same selected spec. Evidence: Source PR/commit evidence Use it when: Many jobs independently download identical versioned fixtures. Before applying it: A producer job adds a serial step and transfer time, so a very small download can stay in each job. Keep fixture identity and version selection exact. [Read more in the Stripe playbook](https://starsling.dev/ci-playbooks/stripe#handoff-shared-test-inputs) [Primary source](https://github.com/stripe/stripe-dotnet/pull/3340) ## CI optimization is continuous work. Apply this technique yourself, or use StarSling Runners for faster GitHub Actions and optional agent-driven optimization PRs, which teams on eligible paid plans can turn on. [Get self-improving CI](https://starsling.dev/products/runners) ## Related techniques ### [Build once and share the output with test shards](https://starsling.dev/ci-playbooks/techniques/build-once-for-shards) Separate the build producer from test consumers and hand the same verified artifact to each shard. 2 implementations · 2 companies (OpenAI, Stripe) ### [Bake stable dependencies into runner images](https://starsling.dev/ci-playbooks/techniques/prebuild-runner-images) Prepare versioned system dependencies and build downloads once in the runner image instead of installing them on every job. 2 implementations · 2 companies (Anthropic, Linear) ### [Cache package downloads and dependency stores](https://starsling.dev/ci-playbooks/techniques/reuse-package-downloads) Restore package-manager downloads or dependency stores while keeping a locked install that validates the requested dependency graph. 7 implementations · 6 companies (DoorDash, Linear, Shopify, Spotify, Stripe, Uber) ## Company Playbooks ### [Anthropic](https://starsling.dev/ci-playbooks/anthropic) Run only affected tests ### [DoorDash](https://starsling.dev/ci-playbooks/doordash) Run build and test in parallel, sharded across CI agents ### [Linear](https://starsling.dev/ci-playbooks/linear) Benchmark the same job on faster hardware ### [Mastra](https://starsling.dev/ci-playbooks/mastra) StarSling runners for the slowest test workflow ### [OpenAI](https://starsling.dev/ci-playbooks/openai) Rank CI fixes by the minutes they save ### [Ramp](https://starsling.dev/ci-playbooks/ramp) Move a CPU-bound test suite to a faster CPU ### [Shopify](https://starsling.dev/ci-playbooks/shopify) Let an agent iterate against one CI metric ### [Spotify](https://starsling.dev/ci-playbooks/spotify) Build arm64 on native arm64 runners ### [Stripe](https://starsling.dev/ci-playbooks/stripe) Run only the tests a change can reach ### [Uber](https://starsling.dev/ci-playbooks/uber) Build the merge-queue speculations most likely to be needed ## Related guides Implementation guides for this technique. ### [Cache workflow dependencies](https://starsling.dev/best-practices/github-actions/cache-dependencies) Choose dependency cache paths and keys for your package manager. ### [Cut repeated test setup](https://starsling.dev/best-practices/github-actions/cut-repeated-test-setup) Share expensive setup at the scope your tests need. ### [Share setup steps across jobs](https://starsling.dev/github-actions/optimizations/avoid-duplicated-setup) Centralize repeated setup definitions and remove duplicate or unused steps. ### [Optimize npm installs](https://starsling.dev/github-actions/optimizations/optimize-npm-install) Cache npm dependencies and large downloads and remove unused tool installs. ### [Optimize pnpm installs](https://starsling.dev/github-actions/optimizations/optimize-pnpm-install) Set up the pnpm store cache in the right order and scope recursive commands.