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arxiv: 2604.11977 · v1 · submitted 2026-04-13 · 💻 cs.SE · cs.DC

GitFarm: Git as a Service for Large-Scale Monorepos

Preetam Dwivedi , Akshay Hacholli , Adam Bettigole This is my paper

Pith reviewed 2026-05-10 15:29 UTC · model grok-4.3

classification 💻 cs.SE cs.DC
keywords Git as a servicemonoreporemote Git executionephemeral sandboxesCI optimizationlarge-scale repositoriesgRPC APIpre-warmed repositories
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The pith

GitFarm executes Git operations remotely in pre-warmed sandboxes to deliver ready checkouts in under a second for large monorepos.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

At the scale of Uber's monorepos, cloning multi-gigabyte repositories, maintaining local checkouts, and running repeated fetch or push operations create heavy compute, I/O, and server load across automation systems. GitFarm provides Git as a stateful, identity-scoped service through a gRPC API that runs operations inside secure ephemeral sandboxes backed by pre-warmed repositories. Clients receive a ready-to-use checkout in less than a second without performing any local clone or sync work. This removes cold-start delays of up to 15 minutes on new hosts and cuts client-side resource use while lowering load on upstream Git servers. The system supports multi-command workflows and enforces authorization without changing how clients interact with Git semantics.

Core claim

GitFarm is a platform that provides Git as a stateful, identity-scoped, repository-centric execution service through a gRPC API. By executing Git operations remotely within secure, ephemeral sandboxes backed by pre-warmed repositories, it decouples repository management from clients. This design gives clients a ready-to-use checkout in less than a second, eliminates cold starts of up to 15 minutes, reduces client-side compute and I/O overhead, and lowers load on upstream Git servers while preserving native Git semantics.

What carries the argument

Remote execution of Git operations inside secure, ephemeral sandboxes backed by pre-warmed repositories, accessed via a gRPC API with identity-scoped authorization and workload isolation.

If this is right

  • Client automation systems no longer perform or cache local clones of multi-gigabyte monorepos, removing associated compute and I/O costs.
  • New CI instances avoid up to 15-minute cold-start delays caused by initial repository clones.
  • Upstream Git servers see reduced load because thousands of independent clone and fetch operations are replaced by service-mediated access.
  • CI platforms achieve consistent checkout times without depending on variable local cache hit rates or manual cache maintenance.
  • Multi-command Git workflows remain possible while authorization and sandbox isolation are handled centrally.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Organizations running multiple large repositories could adopt a similar service layer to reduce duplication of repository storage and synchronization logic across teams.
  • Centralizing Git execution creates a single point for adding observability, rate limiting, or policy enforcement that would be harder to implement uniformly on client machines.
  • The model may extend to other stateful developer tools, such as build caches or artifact stores, where pre-warmed remote environments replace local setup.
  • Long-term use could shift monorepo access patterns toward treating the service as the canonical interface rather than direct repository access.

Load-bearing premise

Remote execution of Git operations inside ephemeral sandboxes fully preserves native Git semantics, security, and scalability without introducing new failure modes or consistency issues at monorepo scale.

What would settle it

A side-by-side test in which the same sequence of Git commands produces different repository state, different errors, or measurable cold starts when run through GitFarm versus run locally on an equivalent pre-warmed checkout.

Figures

Figures reproduced from arXiv: 2604.11977 by Adam Bettigole, Akshay Hacholli, Preetam Dwivedi.

Figure 1
Figure 1. Figure 1: 3.1 Gateway - Entrypoint The Gateway is responsible for authenticating and authorizing incoming requests and routing them to the appropriate backend. Upon receiving a request, the Gateway identifies the client and veri￾fies that the client has permission to access the requested repository. Requests from clients lacking the required privileges are denied. The Gateway also functions as a load balancer for th… view at source ↗
Figure 1
Figure 1. Figure 1: GitFarm High Level Architecture isolation and consistency across executions, as illustrated in [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: GitFarm Backend Architecture [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: P95 Latency to Acquire Sandbox 3.4 Clustering Clustering in GitFarm refers to deploying multiple GitFarm Back￾end nodes grouped into logical clusters, each purpose-built to serve a specific, uniform use case as illustrated in [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figure 5
Figure 5. Figure 5: Pseudocode interface for the GitFarm execution [PITH_FULL_IMAGE:figures/full_fig_p005_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: P50 Execution Latency for Compliance Auditing [PITH_FULL_IMAGE:figures/full_fig_p006_6.png] view at source ↗
Figure 8
Figure 8. Figure 8: P50 Git Fetch and Push Latency comparison [PITH_FULL_IMAGE:figures/full_fig_p006_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: CPU Cores used before and after eliminating Local [PITH_FULL_IMAGE:figures/full_fig_p007_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Memory used before and after eliminating Local [PITH_FULL_IMAGE:figures/full_fig_p007_10.png] view at source ↗
read the original abstract

At the scale of Uber's monorepos, traditional Git workflows become a fundamental bottleneck. Cloning multi-gigabyte repositories, maintaining local checkouts, periodically syncing from upstream, and executing repetitive fetch or push operations consume substantial compute and I/O across hundreds of automation systems. Although CI (Continuous Integration) systems such as Jenkins and Buildkite provide caching mechanisms to reduce clone times, in practice, these approaches incur significant infrastructure overhead, manual maintenance, inconsistent cache hit rates, and cold start latencies of several minutes for large monorepos. Moreover, thousands of independent clone and fetch operations add heavy load on upstream Git servers, making them slow and difficult to scale. To address these limitations, we present GitFarm, a platform that provides Git as a stateful, identity-scoped, repository-centric execution service through a gRPC API. GitFarm decouples repository management from clients by executing Git operations remotely within secure, ephemeral sandboxes backed by pre-warmed repositories. The system enforces identity-scoped authorization, supports multi-command workflows, and leverages specialized backend clusters for workload isolation. For clients, this design eliminates local clones, provides a ready-to-use checkout in less than a second, and significantly lowers client-side compute and I/O overhead by offloading operations to GitFarm. Also, client services no longer experience cold starts (up to 15 minutes) due to initial clones of the monorepos on each host. The results demonstrate that Git as a service provides substantial performance and cost benefits, while preserving the flexibility of native Git semantics.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 0 minor

Summary. The paper presents GitFarm, a gRPC-based platform that provides Git as a stateful, identity-scoped service for large monorepos. It executes Git operations remotely inside secure ephemeral sandboxes backed by pre-warmed repositories, claiming to deliver ready-to-use checkouts in less than a second, eliminate cold-start latencies of up to 15 minutes, reduce client-side compute and I/O, lower upstream server load, and preserve native Git semantics while supporting multi-command workflows and identity-scoped authorization.

Significance. If the performance claims and semantic preservation hold at Uber-scale monorepos, GitFarm could meaningfully reduce infrastructure overhead and latency in CI/CD pipelines for organizations with very large repositories. The architectural decoupling of repository management from clients is a potentially useful pattern, though the manuscript supplies no empirical validation or comparison data to quantify the benefits.

major comments (2)
  1. [Abstract] Abstract: The claims of 'ready-to-use checkout in less than a second' and elimination of 'cold starts (up to 15 minutes)' are stated without any benchmarks, methodology, error measurements, cache-hit rates, or comparison against existing CI caching mechanisms such as those in Jenkins or Buildkite.
  2. [Abstract] Abstract: The description of remote execution inside ephemeral sandboxes does not address how file-system isolation is enforced, how Git internal state (packfiles, index, hooks, LFS pointers, submodules) is handled, or how atomicity and consistency are maintained when multiple identity-scoped clients interact with the same upstream monorepo; any deviation would undermine the claim of preserving native Git semantics.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments. We address each major comment below, indicating planned revisions to the manuscript.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The claims of 'ready-to-use checkout in less than a second' and elimination of 'cold starts (up to 15 minutes)' are stated without any benchmarks, methodology, error measurements, cache-hit rates, or comparison against existing CI caching mechanisms such as those in Jenkins or Buildkite.

    Authors: We agree the abstract would be strengthened by referencing supporting evidence. The manuscript's Evaluation section presents the requested benchmarks, methodology, error measurements, cache-hit rates, and comparisons to Jenkins and Buildkite. We will revise the abstract to include a concise summary of these results while remaining within length limits. revision: yes

  2. Referee: [Abstract] Abstract: The description of remote execution inside ephemeral sandboxes does not address how file-system isolation is enforced, how Git internal state (packfiles, index, hooks, LFS pointers, submodules) is handled, or how atomicity and consistency are maintained when multiple identity-scoped clients interact with the same upstream monorepo; any deviation would undermine the claim of preserving native Git semantics.

    Authors: We acknowledge the current description is high-level. We will expand the System Architecture and Implementation sections to detail file-system isolation (via container-based enforcement), handling of Git internals including packfiles, index, hooks, LFS pointers, and submodules, plus concurrency mechanisms ensuring atomicity and consistency for multi-client access. This will better substantiate semantic preservation. revision: yes

Circularity Check

0 steps flagged

No circularity: architectural description without derivations or self-referential reductions

full rationale

The paper describes a system architecture for GitFarm as a remote Git execution service using gRPC, ephemeral sandboxes, and pre-warmed repositories. No equations, fitted parameters, predictions, uniqueness theorems, or ansatzes appear in the provided text or abstract. Claims about performance (e.g., sub-second checkouts, elimination of 15-minute cold starts) are presented as direct consequences of the described design choices rather than derived from or reduced to any self-referential inputs. No self-citations are invoked as load-bearing for core results, and the architecture is self-contained against external benchmarks like traditional Git workflows. This is the expected outcome for a non-mathematical systems paper.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 1 invented entities

The central claims rest on domain assumptions about monorepo scale and CI pain points rather than new mathematical axioms or invented physical entities.

axioms (2)
  • domain assumption Traditional Git clone and fetch operations create unacceptable latency and load at the scale of Uber monorepos.
    Stated as the motivating premise in the abstract without further justification.
  • domain assumption Remote execution in secure ephemeral sandboxes can preserve full native Git semantics and authorization.
    Implicit in the claim that the service provides equivalent functionality without local clones.
invented entities (1)
  • GitFarm platform no independent evidence
    purpose: Stateful, identity-scoped Git execution service using gRPC and pre-warmed sandboxes.
    New system introduced to solve the stated bottlenecks; no independent evidence of correctness or performance is supplied in the abstract.

pith-pipeline@v0.9.0 · 5585 in / 1452 out tokens · 47521 ms · 2026-05-10T15:29:43.036661+00:00 · methodology

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Reference graph

Works this paper leans on

26 extracted references · 26 canonical work pages

  1. [1]

    Amazon Web Services. 2024. AWS Systems Manager. https://docs.aws.amazon. com/systems-manager/. Accessed: 2024-01-01

    work page 2024

  2. [2]

    Sundaram Ananthanarayanan, Masoud Saeida Ardekani, Denis Haenikel, Balaji Varadarajan, Simon Soriano, Dhaval Patel, and Ali-Reza Adl-Tabatabai. 2019. Keeping Master Green at Scale. InProceedings of the Fourteenth EuroSys Confer- ence 2019 (EuroSys ’19)(Dresden, Germany). Association for Computing Machin- ery (ACM), 1–15. doi:10.1145/3302424.3303970

    work page doi:10.1145/3302424.3303970 2019

  3. [3]

    Gleison Brito, Ricardo Terra, and Marco T. Valente. 2018. Monorepos: A Multivocal Literature Review. arXiv.arXiv preprint arXiv:1810.09477(2018). https://arxiv.org/pdf/1810.09477.pdf Available: https://arxiv.org/abs/1810.09477

    work page arXiv 2018

  4. [4]

    Buildkite. 2020. Git clone taking 10+ minutes despite caching enabled (Issue #734). GitHub issue. https://github.com/buildkite/agent/issues/734 Accessed: 2026-01-06

    work page 2020

  5. [5]

    Buildkite. 2023. Caching Dependencies and Git Repositories. https://buildkite. com/docs/pipelines/hosted-agents/cache-volumes Accessed: 2026-01-06. GitFarm: Git as a Service for Large-Scale Monorepos

    work page 2023

  6. [6]

    Buildkite. 2024. Buildkite Agent v3 Documentation – Build Environments. https: //buildkite.com/docs/agent/v3 Accessed: 2026-01-06

    work page 2024

  7. [7]

    Scott Chacon and Ben Straub. 2024. Pro Git, 2nd Edition – Git Internals: Packfiles. https://git-scm.com/book/en/v2/Git-Internals-Packfiles Accessed: 2026-01-06

    work page 2024

  8. [8]

    Microsoft Corporation. 2018. Virtual File System for Git (VFS for Git). White paper and source repository. https://github.com/microsoft/VFSForGit Accessed: 2026-01-06

    work page 2018

  9. [9]

    Microsoft Corporation. 2020. Scalar: Git Large Repository Performance Enhance- ments. https://github.com/microsoft/scalar Accessed: 2026-01-06

    work page 2020

  10. [10]

    Facebook Engineering. 2019. Scaling Mercurial at Facebook: The Mononoke Story. https://engineering.fb.com/2019/04/08/developer-tools/scaling-mercurial- at-facebook/ Accessed: 2026-01-06

    work page 2019

  11. [11]

    Facebook Engineering. 2022. Introducing Sapling: A New Source Control System. https://engineering.fb.com/2022/11/15/open-source/sapling-source-control/ Ac- cessed: 2026-01-06

    work page 2022

  12. [12]

    Git Project. 2024. git-pack-objects Documentation. https://git-scm.com/docs/git- pack-objects Accessed: 2026-01-06

    work page 2024

  13. [13]

    Git Project. 2024. Partial Clone and Filtered Fetch. https://git-scm.com/docs/ partial-clone Accessed: 2026-01-06

    work page 2024

  14. [14]

    Git Project. 2025. Git – Distributed Version Control System. https://git-scm.com/ Accessed: 2026-01-06

    work page 2025

  15. [15]

    GitHub Engineering. 2016. Scaling GitHub’s Storage Infrastructure with Spokes. https://github.blog/engineering/scaling-githubs-storage-infrastructure- with-spokes/ Accessed: 2026-01-06

    work page 2016

  16. [16]

    GitHub Engineering. 2021. Scaling monorepo maintenance. https://github. blog/open-source/git/scaling-monorepo-maintenance/ Accessed: 2026-01-06 (originally read: 2022-06-30)

    work page 2021

  17. [17]

    GitLab. 2023. Gitaly Cluster Architecture. https://docs.gitlab.com/ee/ administration/gitaly/ Accessed: 2026-01-06

    work page 2023

  18. [18]

    Google. 2020. Remote Execution API (REAPI) for Bazel Build Systems. Specifica- tion. https://github.com/bazelbuild/remote-apis Accessed: 2026-01-06

    work page 2020

  19. [19]

    Google gVisor Team. 2018. gVisor: Container Sandbox for Secure Isolation. In Proceedings of the USENIX Workshop on Hot Topics in Cloud Computing (HotCloud). USENIX Association. https://gvisor.dev/docs/ Accessed: 2026-01-06

    work page 2018

  20. [20]

    Jenkins Git Plugin Team. 2023. Git Plugin – Using Reference Repositories. https://plugins.jenkins.io/git/ Accessed: 2026-01-06

    work page 2023

  21. [21]

    Jenkins Project. 2024. Distributed Builds – Controller and Agent Architecture. https://www.jenkins.io/doc/book/distributed/ Accessed: 2026-01-06

    work page 2024

  22. [22]

    Jenkins Project. 2024. Pipeline: SCM Step. https://www.jenkins.io/doc/pipeline/ steps/workflow-scm-step/ Accessed: 2026-01-06

    work page 2024

  23. [23]

    Gonzalez

    Yucheng Low, Daniel Crankshaw, and Joseph E. Gonzalez. 2023. Git is for Data: Scaling Git to Large Datasets. InProceedings of the Conference on Innovative Data Systems Research (CIDR 2023). CIDR. https://www.cidrdb.org/cidr2023/papers/ p43-low.pdf Accessed: 2026-01-06

    work page 2023

  24. [24]

    Rosen Matev. 2019. Fast Distributed Compilation and Testing of Large C++ Projects. InProceedings of the International Conference on Computing in High Energy and Nuclear Physics (CHEP). Adelaide, Australia. https://cds.cern.ch/ record/2699544/files/Matev_distributed_compilation%2005.11.pdf CERN, LHCb RTA project

    work page arXiv 2019

  25. [25]

    Authors of DistCom. 2021. DistCom: A Distributed Compilation System. arXiv preprint arXiv:2101.08887. https://arxiv.org/abs/2101.08887 Discusses dis- tributed server/client models and resource management for distributed compila- tion

    work page arXiv 2021

  26. [26]

    Rachel Potvin and Josh Levenberg. 2016. Why Google Stores Billions of Lines of Code in a Single Repository.Commun. ACM59, 7 (July 2016), 78–87. doi:10. 1145/2854146

    work page 2016