Why Traditional Git Servers Won’t Survive 2025

Git changed how we build software.

However, the world it was built for – local repositories and teams, along with simple, human-centric CI/CD pipelines – no longer exists.

Today, codebases are massive. Teams are global. And AI is generating code faster than ever before. Our infrastructure hasn’t kept pace, and traditional Git servers are reaching their limits.

Development Has Outgrown Traditional Git

Software development has exploded in both volume and velocity. According to Archive Market Research, the global software repository market will hit $15 billion in revenue in 2025, growing at 15% annually through 2033. GitHub now hosts over 420 million repositories, supporting more than 100 million developers – each pushing more commits, more frequently, and with more automation than ever.

At the same time, 97% of teams now use AI-assisted tools for vibe-coding, AI-agents for creating PRs and commits, automated AI-code-review, and AI-generated documentation. This results in a massive surge in server traffic, particularly read operations from increased test jobs and automated quality-checking processes, which are literally exploding.

Traditional scaling methods – adding more servers, bigger instances, or wider clusters – simply don’t address the core issue: the world has changed since Git was built 20 years ago.

The Breaking Point for Traditional Git Servers

The symptoms are now familiar to most engineering teams:

  • Slow performance. Git clones and fetches are taking several minutes or even timing out instead of completing swiftly in a few seconds.
  • Pipeline delays. CI/CD is waiting for repositories to be available for cloning or fetching, which delays the feedback cycle.
  • Storage capacity strain. Larger monorepos or multi-repo setups are hitting massive BLOB count and hitting ref limits. When storage is hosted on the Cloud or on shared disks, the increase in the directories and I/O transfer makes Git almost unusable.
  • Rising costs. Over-provisioned infrastructure is trying (and failing) to keep up. The provisional or elastic filesystem limits increase significantly, bringing operational costs to new heights never seen before, and putting more pressure on the budget.

The Archive Market Research report warns: “The rising complexity of software development necessitates efficient and reliable repositories for managing code, dependencies, and artifacts.”

In other words, the systems we depend on to deliver software are now slowing software down.

Scaling Smarter, Not Harder

At GerritForge, we believe that simply throwing more hardware at the problem is no longer enough: it is Git and its utilisation that need to be smarter. We have been researching on the use of AI for optimising the performance and scalability of repositories for over 3 years and shared our findings with the global scientific community.

That’s why we built GHS, an AI-powered accelerator for Git-based SCMs.

We have simulated and demonstrated how traditional tools would collapse and developed GHS, a brand-new model to overcome the traditional limitations of the Git repositories.

GHS learns how your repositories behave, your access patterns, your CI/CD workflows, and your traffic peaks – and, using reinforcement learning, automatically optimises performance in real-time.

With GHS, the whole development team will experience:

  • Up to 100× faster Git operations. Clones and fetches keep on completing at raw speed, without slowdowns, timeouts or slack.
  • Real-time auto-optimisation. The Git repositories are automatically monitored and optimised for speed, without manual operations.
  • Lower operational costs. The CPU and storage do not suffer from the overload of incoming traffic, delivering better performance on existing hardware. There is no need to scale up the infrastructure and costs massively.
  • Increased reliability. Git servers remain stable even under extreme load, eliminating the need for emergency restarts or maintenance.

Traditional scaling adds more servers. GHS scales using its sophisticated AI model to get the most out of what you already have.

The Gerrit User Summit 2025 made one thing clear: the era of traditional scaling is coming to an end.

As repositories grow and workflows evolve, the next generation of developer infrastructure must be intelligent, simplified & resilient. AI isn’t replacing developers – it’s augmenting them. But if your Git infrastructure can’t keep pace with this new level of activity, your entire SDLC pipeline will suffer.

2025 marks a turning point for software delivery. Traditional Git servers can’t keep up, but that doesn’t mean your team can’t. Because in modern DevOps, speed isn’t just efficiency, it’s a competitive edge.