The whole dayMon 2 Nov 2026
AI Compass

OpenAI details Pando Git backend serving nearly 1 PB a day to Codex agents

Published on 2 November 2026, OpenAI’s custom distributed Git storage engine replaces global reference locks with per-branch causal consistency and trims median monorepo push latency by almost five times.

OpenAI’s Scaling Git at OpenAI title graphic set over an atmospheric blue cloudscape.
Image: OpenAI

OpenAI engineering published the architecture of Pando on 2 November 2026, detailing how it rebuilt internal Git hosting after parallel Codex coding agents pushed reliability on its legacy monorepo backend below 90%. Conventional replicated Git servers serialise reference updates through three-phase commits or a shared write-ahead log, turning millions of short-lived agent branches into a global lock bottleneck and inflating reference advertisements past 100 MiB.

Pando separates immutable packfiles in horizontally scalable blob storage from per-branch metadata logs enforced under causal consistency rather than global linearisability. When a developer or Codex worker pushes to a feature branch, Pando advertises only a designated trunk branch so clients upload thin deltas, keeping median push packfiles below 20 KiB and 99th-percentile pushes under 3 MiB. Fetch traffic reads immutable cached packfiles directly, hitting local disk caches on more than 99% of requests.

Diagram showing Pando storing commit objects and immutable packfiles in horizontally scalable blob storage while keeping independent ref logs per branch in metadata storage.
Pando separates immutable packfile blobs from per-branch metadata logs so pushes on separate branches never contend on a global lock.Image: OpenAI

OpenAI has contributed client-side patches including parallel pack indexing and explicit force-with-lease object negotiation upstream to Git, while keeping the Pando server infrastructure internal.

Key numbers

  • Nearly 5 times lower median Git push latency (roughly an 80% reduction).
  • Nearly 1 PB of Git data served per day, peaking above 57 TB in a single hour.
  • Under 20 KiB median push packfile size and under 3 MiB at the 99th percentile.
  • Over 99% local disk cache hit rate on packfile fetches.

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