The bridge to agent-scale Git infrastructure

figure — over the past year, while Git traffic grew exponentially, 99.99999% of the Git repositories on GitHub began living in two places at once: our own data centers and Azure. The rest are among the busiest on the platform, and they’re held back by just one thing: a 25ms round trip.

In an earlier blog post, we laid out the two principles behind our next-generation storage architecture: Minimize coordination Decouple storage from compute In this post, we’ll look at the immediate bridge between our old design and our new one. We’ll talk about how a change to the way our quorum serializes writes gets the busiest repositories into Azure, and how that same step opens the door to replicas that keep no persistent state of their own. How we got here The timing and shape of the move were driven by the agentic shift: rapidly growing traffic, a hard ceiling on the power capacity of our data centers and the surrounding geographical region, and physical supply chain constraints. At the beginning of our migration, the remaining capacity with all possible expansion gave us enough time to migrate safely, but not enough to do it slowly. While we had prototyped new architectural approaches for scaling Git on cloud infrastructure, changing the storage architecture and the hosting platform at the same time, under that growth, carried too much risk. Given our scale and how critical the service is to the community, we needed to sequence the work carefully: move the data first, then evolve the architecture once it arrived. Git operations are a Tier 0 service: they’re a core function of GitHub, and nearly everything in GitHub depends on the repository data. That meant the data, services, and every dependency had to move first. The first copy of a repository landed in Azure’s Central US region in August 2025. Today, most repositories have two of their five replicas in Azure, and Azure serves about half of Git traffic. For most of that time, Azure absorbed our growth while our own data centers held steady. During the migration, traffic follows the data. Most repositories have five replicas to balance durability, availability, and scale. To minimize read latency, Spokes uses preferential routing to direct traffic to a replica in the same region and availability zone as the request. As replicas move to Azure, the share of the traffic that can be served from Azure grows with each one, until the last replica arrives and the old region stops receiving requests entirely.