GitHub rebuilds its Git infrastructure for agents: September commits were more than five times a year earlier, and the new design delivered up to 35x write throughput in internal tests
GitHub says developers and agents working concurrently in repositories have sharply increased Git activity, with 7.38 billion commits in September, more than five times a year earlier; it is rebuilding its Git infrastructure without downtime, separating storage from compute, and reports up to 35 times higher write throughput in internal benchmarks.
In a post on its official blog, GitHub said agentic software development is driving its next architectural shift and that it is rebuilding its Git infrastructure accordingly. Between September 2025 and August 2026, Git activity on GitHub rose from 218.2 billion to 473.3 billion events per month, more than doubling; in September 2026 alone, developers and agents made 7.38 billion commits, more than five times as many as a year earlier. The busiest single repository received roughly a billion requests in August.
GitHub listed the sources of pressure: an agent commits or checkpoints after nearly every action, so the latency of a single push caps its speed; pushes grew 4.9x year over year, from 0.69 billion to 3.35 billion per month; pull request merges grew to nearly 4x their volume a year earlier; and CI and code scanning fetch the same branch tip thousands of times per minute, with GitHub Actions alone running 3.26 billion times in September, more than 4x a year earlier.
In the current architecture, Spokes keeps a full copy of each repository on the local disks of several fileservers, five by default, and pushes use a three-phase commit with a quorum for consistency. The problem is that the copies handle both durability and read scaling: adding replicas to absorb reads makes every write wait on one more replica, so writes slow down, and losing quorum stops writes entirely.
The new architecture separates the two: authoritative repository data lives in Azure Blob Storage, and reads are served by lightweight caching compute workers that can be added or removed with demand; only the reference update itself is coordinated, while object storage, connectivity validation and secret scanning run in parallel; compaction and garbage collection move to separate background workers. GitHub says internal benchmarks showed up to 35 times higher write throughput, with read capacity scaling independently. The work is being done while the service keeps running, controls such as branch protection, required reviews and audit logs are preserved, and a follow-up post will cover more details.
Sources
- Building Git infrastructure for agent-scale development — GitHub Blog