GitHub's Universe conference kicked off in San Francisco on Wednesday with news that its infrastructural universe is expanding to address staggering demand from AI agents.

GitHub recorded 7.4 billion code commits in September 2026, five times more than hit its servers a year earlier. This surge in traffic over the past year, the result of developers running AI agents and generating increased amounts of programming code, caught the company unprepared and led to a series of outages and service availability woes.

AI-driven code commits started becoming a problem last December, and led to problems in February, April, August, not to mention the months in between. On May 7, the site's 90-day availability hit a low of about 84 percent, according to reconstructed data from GitHub's status page.

GitHub execs apologized and promised to do better. Those commitments have put four million CPU cores and 160 petabytes of high-speed storage on its infrastructure roadmap, alongside extra compute capacity for GitHub Actions, the company's beleaguered continuous integration and continuous delivery (CI/CD) platform.

The Microsoft-owned code hosting biz also says it is redesigning its technical architecture (an effort discussed previously) to separate compute and storage, with the expectation that will enable 35x more throughput.

"We’re also migrating to a multi-region deployment in Azure, while continuing to serve incredible levels of traffic from developers around the world," said Jay Parikh, EVP of CoreAI, Microsoft, in a blog post provided to . "We expect to complete the migration early next year. Those investments give us more room to grow. The next step is building the systems that handle the work."

Also at the its Universe event, GitHub announced general availability of Copilot Fusion, the company's model routing service that was previewed under the name HydraFusion. The idea is that allowing GitHub to route requests to different models can improve task-completion rates while reducing token consumption costs.

"Different tasks need different models," said Parikh. "Developers shouldn’t have to manage every model choice to get the right result at the right price. Copilot Fusion evaluates what a task needs across reasoning, code generation, debugging, and tool use, then chooses how to execute across one or more models. In the Artificial Analysis Coding Agent Index, Fusion Max scored within two points of Opus 5.5 Max at half the cost and 40% less time per task."

GitHub is making more bells and whistles available through its Copilot app, including Copilot Projects, for coordinating parallel work; Copilot Connectors, for simplifying how Copilot connects to MCP servers; and Copilot Automations, which are reusable agent tasks.

And in what appears to be an effort to boost Copilot usage in the workplace, GitHub is extending Copilot access to all GitHub Enterprise users without requiring any additional per-seat purchases. Customer still get billed for the tokens they use.

Microsoft's code collab biz is also expanding its suite of AI services for developers with an offering called AI Scans, which checks pull requests for vulnerabilities in languages not addressed by rule-based scanning and in code that's already merged, plus new reachability analysis tools that allow development to focus on issues that are plausibly exploitable. Another new offering is a package firewall that checks enterprise policy settings before fetching npm packages. ®