--- title: "Keep full history and download old blobs on demand" description: "Change detection often needs commit history and filenames, not old file contents." url: https://starsling.dev/ci-playbooks/techniques/blobless-history canonicalUrl: https://starsling.dev/ci-playbooks/techniques/blobless-history --- # Keep full history and download old blobs on demand Change detection often needs commit history and filenames, not old file contents. ## How to choose an approach This technique currently has one documented company example. Validate its prerequisites, tradeoffs and original CI environment against your repository before adapting it. - **[Mastra](https://starsling.dev/ci-playbooks/mastra#blobless-history)**: Use it when Checkout transfer dominates jobs that compare names or trees across commits. Check before adopting: Lazy blob reads still need network access and appropriate credentials. ## Apply this technique ````text Evaluate and apply this CI technique to my repository: Keep full history and download old blobs on demand. Change detection often needs commit history and filenames, not old file contents. Read the technique and its source-backed company examples: https://starsling.dev/ci-playbooks/techniques/blobless-history.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 Mastra used this technique Read what Mastra changed and follow the original sources. ### Mastra: Keep full history and download old blobs on demand Seven full-history checkouts gained filter: blob:none while retaining fetch-depth: 0. History stays complete, and old blobs download on demand. Evidence: Source PR/commit evidence The PR reports transfer falling from 1,572 MB to 189 MB, about 88% fewer bytes. ([Source](https://github.com/mastra-ai/mastra/pull/21298)) Use it when: Checkout transfer dominates jobs that compare names or trees across commits. Before applying it: Lazy blob reads still need network access and appropriate credentials. [Read more in the Mastra playbook](https://starsling.dev/ci-playbooks/mastra#blobless-history) [Primary source](https://github.com/mastra-ai/mastra/pull/21298) ## 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 ### [Fetch only the repository history a job needs](https://starsling.dev/ci-playbooks/techniques/fetch-needed-history) Limit checkout depth and fetched refs to the comparisons or release history the job actually consumes. 4 implementations · 4 companies (Linear, Mastra, OpenAI, Stripe) ### [Serve checkouts from pre-warmed repository clones](https://starsling.dev/ci-playbooks/techniques/git-checkout-service) Keep repository clones warm on a few machines and run Git operations against them, so jobs skip the cold clone. 1 implementation · 1 company (Uber) ### [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) ## 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. ### [Filter workflows by changed files](https://starsling.dev/best-practices/github-actions/path-filter-workflows) Use paths and job conditions while keeping required checks reporting. ### [Cancel superseded CI runs](https://starsling.dev/best-practices/github-actions/cancel-superseded-runs) Cancel obsolete PR runs with a correctly scoped concurrency group.