Gerrit Code Review 3.13 has landed, bringing a significant wave of security enhancements, powerful automation, and next-generation AI features designed to streamline your development workflow. This release reflects a healthy, growing open-source project, with a focus on improving both the user experience and the underlying security and configurability of the platform.
Here are the top 6 features and improvements you need to know about in Gerrit 3.13:
Introducing Gerrit Flows for Powerful Automation
Gerrit Flows is a game-changing new concept that introduces automation rules for changes. It is a powerful generalization of the logic previously found in issue tracker plugins (like its-jira), allowing you to define a sequence of actions triggered when specific conditions are met.
This is a pluggable service, meaning that while the core functionality is in Gerrit, community plugins can easily integrate it with systems like Jira, GitHub Issues, or internal tools.
An example could be to add reviewers only after the CI/CD has validated the change, so that the reviewer doesn’t waste time reviewing a change that will ultimately receive a minus one from the build process.
HTTP Auth-Tokens Replace Long-Lived Passwords
In a major security upgrade driven primarily by SAP’s contribution, Gerrit 3.13 deprecates long-lived HTTP passwords in favor of secure, time-limited Authentication Tokens (Auth-Tokens).
This enhancement addresses two long-standing security concerns with previous HTTP passwords:
Expiration: Tokens can now be set to expire, allowing organizations to enforce rotation policies that were previously not enforceable when using Git or the Gerrit REST API over HTTPS.
Multiple Credentials: Users can have more than one token with friendly names, enabling proper credential rotation (like blue/green deployment) for automated scripts without downtime.
Tokens are a full replacement of the legacy HTTP passwords, as the ability to define their maximum lifetime is often a prerequisite for security compliance. Generating a new token credential would automatically remove the deprecated passwords stored in the account’s profile.
Next-Gen AI Assistance: AI prompt generation for Code Review
Gerrit 3.13 firmly steps into the era of AI-assisted development by enabling its foundational AI features by default and introducing native facilities to request help to review incoming changes using an external LLM.
AI-Assisted “Generate Prompt” Feature: This feature was previously released as an experiment and is now enabled by default. It helps users generate rich, explicitly crafted prompts for LLMs (such as Gemini, ChatGPT, or Claude) to assist with code reviews. Users can ask for help with the commit message, request improvements, or check for security concerns.
Dedicated UI for Project Labels and Submit Requirements
Configuration and administration are significantly simplified with the introduction of dedicated UI panels for managing Project Labels and Submit Requirements.
Interactive Project Configuration vs. config file editing: Previously, defining these project settings required cloning and editing the project.config file, either offline or online, a process described as difficult and error-prone for most users.
Submittability Split: This reinforces the modern split where Labels are just votes, and Submit Requirements formally define the logic for a change’s submittability.
End-to-End Group Deletion \o/
This was a long-awaited quality-of-life feature: Gerrit 3.13 provides full end-to-end functionality to delete internal groups directly through the UI and a dedicated REST API.
Administrative Control: In the past, groups, once created, were permanent. Now, administrators can remove them.
Prerequisite: A group cannot be deleted if it is referenced in any ACL (access control list). Admins must first reshape their ACLs before removal. The community has acknowledged that the resulting error message needs improvement to show where the group is referenced.
Significant UI/UX Updates, Including Drag-and-Drop
Gerrit continues its modernization effort, focusing on a cleaner, more efficient user experience, thanks largely to contributions from Paladox/Wikimedia.
Drag-and-Drop Reviewers: Users can now drag and drop reviewers and CCed users to move them between fields, eliminating the annoying multi-step process of removing a user from one list and adding them to the other.
Mobile and Material Updates: The release includes extensive modernization, replacing older components with @material/web, and a redesigned mobile UI for improved navigation.
Gerrit 3.13 By The Numbers
A Community Effort Gerrit 3.13 saw a significant push in core development, reversing the trend of previous releases that focused more heavily on plugins. The number of commits in Core Gerrit went from ~600 in Gerrit 3.12 to over 900 in Gerrit 3.13, showcasing an amazing increase of pace in the development speed of the project, which is great to see.
The open-source health of Gerrit is strong, with no single organization contributing over 50% of the changes. The contributions are spread across many companies, demonstrating the actual value of open source and the good health of the project. Google continues to lead the project from the forefront with almost 40% of commits.
GerritForge’s Contribution
Here at GerritForge, led by maintainer Luca Milanesio, we contributed 28% of the commits to the past 12 months of the Gerrit project contributions! We also, as usual, performed the crucial work required to take the finished code and turn it into a consumable release for the world, including, but not limited to, managing the whole release process and continuing to host the CI/CD pipelines for the project.
This dedicated effort ensures the smooth, professional delivery of every new version of Gerrit.
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.
Slow Git isn’t just annoying – it’s expensive for everyone: developers wait for a CI/CD validation of their changes, SCM admins are wasting their time in fire-fighting SCM slowdown and broken pipelines, IT managers are wasting millions of dollars in CPU and Disk hosting costs.What if your Git operations could be up to 100x faster, and keep up with the new AI-vibe coding landslide of PR and changes?
100x Faster Git, Powered by AI
GHS is an AI-based accelerator for Git SCM that redefines performance:
Up to 100x faster clones and fetches.
CI/CD pipelines that run without SCM barriers.
Adapt automatically to your repository shape and make it faster.
Scale without slowdown even under heavy loads
This isn’t traditional “tuning.” GHS learns your repos and access patterns, then continuously optimises them so your Git server is always running at maximum speed.
How Does GHS Deliver 100x Faster Git?
Measure Everything It collects detailed metrics in realtime on your repositories.
Spot Bottlenecks GHS AI model is trained on recognizing the bottlenecks and take immediate action, before they become a problem
Stay Fast Your Git stays consistently accelerated, not just temporarily boosted.
Why Speed Matters
Developers stop wasting hours on slow fetches and builds.
Release managers push features out faster.
IT leaders reduce infra costs by doing more with less.
Admins no longer fire-fight performance issues.
Every 1% of time saved in Git can add up to days of productivity across a large team. Imagine saving 100x that.
Who Needs 100x Faster Git?
Repositories of all sizes: AI-driven code generation and “vibe-coding” have dramatically accelerated the pace of software delivery.
Enterprises that have adopted the AI-pipeline want that value delivered faster to production.
Any team frustrated with slow CI/CD pipelines.
The GHS Advantage
Transformative speed: not just 2x or 5x faster, but up to 100x
SCM expertise: GerritForge’s decades of enterprise SCM know-how built in.
Proven reliability: Stability and uptime as performance scales.
Get Started Today
You can try GHS free for 30 days and experience the difference for yourself.
First, a huge thank you to the OpenInfra Foundation for hosting this event in Paris. Their invitation to have the Gerrit User Summit join the rest of the community set the stage for a truly collaborative and impactful gathering.
Paris last weekend wasn’t just a conference; it was a reunion. Fourteen years after the last GitTogether at Google’s Mountain View HQ, the “Git and Gerrit, together again” spirit was electric.
On October 18-19, luminaries from the early days (Scott, Martin, Luca, and many others) reconvened, sharing the floor with the new generation of innovators. The atmosphere was intense, filled with the same collaborative energy of 2011, but focused on a new set of challenges. The core question: how to evolve Git and Gerrit for the next decade of software development, a future dominated by AI, massive scale, and an urgent demand for smarter workflows.
Here are the key dispatches from the summit floor.
A Historic Reunion, A Shared Future
This event was a powerful reminder that the open-source spirit of cross-pollination is alive and well. The discussions were invigorated by the “fresh air” from new-school tools like GitButler and Jujutsu (JJ), which are fundamentally rethinking the developer experience.
In a significant show of industry-wide collaboration, we were delighted to have GitLab actively participating. Patrick’s technical presentation on the status of reftable was a highlight, but his engagement in discussions on collaborative solutions moving forward with the Gerrit community truly set the tone. It’s clear that the challenges ahead are shared by all platforms, and the solutions will be too.
Scaling Git in the Age of AI
The central theme was scale. In this rapidly accelerating AI era, software repositories are growing at an unprecedented rate across all platforms—Gerrit, GitHub, and GitLab alike. This isn’t a linear increase; it’s an explosion, and it’s pushing SCM systems to their breaking point.
The consensus was clear: traditional vertical and horizontal scaling is no longer enough. The community is now in a race to explore new techniques—from the metal up—to improve performance, slash memory usage, and make core Git operations efficient at a scale we’ve never seen before. This summit was a rare chance for maintainers from different ecosystems to align on these shared problems and forge collaborative paths to solutions.
Dispatches from the Front Lines: NVIDIA and Qualcomm
This challenge isn’t theoretical. We heard powerful testimonials from industry giants NVIDIA and Qualcomm, who are on the front lines of the AI revolution.
They shared fascinating and sobering insights into the repository explosion they are actively managing. Their AI workflows—encompassing massive datasets, huge model binaries, and unprecedented CI/CD activity—are generating data on a scale that is stressing even the most robust SCM systems. Their presentations detailed the unique challenges and innovative approaches they are pioneering to tackle this data gravity, providing invaluable real-world context that fueled the summit’s technical deep dives.
Beyond the Pull Request: The Quest for a ‘Commit-First’ World
One of the most passionate debates centered on the developer workflow itself. The wider Git community increasingly recognizes that the traditional, monolithic “pull request” model is ill-suited to the “change-focused” code review that platforms like Gerrit have championed for years.
The benefits of a change-based workflow, cleaner history, better hygiene, and higher-quality atomic changes—are driving a growing interest in standardizing a persistent Change-ID for each commit. This would make structured, atomic reviews a first-class citizen in Git itself. The collaboration at the summit between the Gerrit community, GitButler, JJ, and other Git contributors on defining this standard was a major breakthrough.
This shift is being powered by tools like GitButler and JJ, which are built on a core philosophy: Workflow Over Plumbing. Modifying commits, rebasing, and resolving conflicts remain intimidating hurdles for many developers. The Git command line can be complex and unintuitive. These new tools abstract that complexity away, guiding users through commit management in a way that feels natural. The result is faster iteration, higher confidence, and a far better developer experience.
AI and the Evolving Craft of Code Review
Finally, no technical summit in 2025 would be complete without a deep dive into AI. The arrival of AI-assisted coding is fundamentally shifting the dynamic between author and reviewer.
Engineers at the summit expressed a cautious optimism. On one hand, AI is a powerful tool to accelerate reviews, improve consistency, and bolster safety. On the other, everyone is aware of the trade-offs. Carelessly used, AI-generated code can weaken knowledge sharing, blur IP boundaries, and erode a team’s deep, institutional understanding of its own codebase.
The challenge going forward is not to replace the human in the loop, but to strengthen the craft of collaborative review by integrating AI as a true co-pilot.
A Path to 100x Scale: The GHS Initiative
The most forward-looking discussions at the summit centered on how to achieve the massive scale required. One of the most promising solutions presented was GHS (Git-at-High-Speed). This innovative approach is not just an incremental improvement; it’s a strategic initiative designed to increase SCM throughput by as much as 100x.
The project’s vision is to enable platforms like Gerrit, GitLab, and GitHub Enterprise to handle the explosive repository growth and build traffic generated by modern AI workflows. By re-architecting key components for hyper-scalability, GHS represents a concrete path forward, ensuring that the industry’s most critical SCMs can meet the unprecedented demands of the AI-driven future.
The Road from Paris
The Gerrit User Summit 2025 was more than a look back at the “glorious days.” It was a statement. The Git and Gerrit communities are unified, energized, and actively building the next generation of SCM. The spirit of GItTogether 2011 is back, but this time it’s armed with 14 years of experience and a clear-eyed view of the challenges and opportunities ahead.
GerritForge has confirmed over 2023 its commitment to the Gerrit Code Review platforming, helping deliver two major releases: Gerrit v3.8 and v3.9.
The major contributions combined are focused on the plugins for extending the reach of the Gerrit platform, first and foremost the pull-replication and multi-site, as shown by the split of the 853 contributions across the projects, weighted by the number of changes and average modifications per change.
Pull replication plugin This is where GerritForge excelled in providing an unprecedented level of performance over anything that has been built so far in terms of Git replication for Gerrit. Roughly one-third of the Team efforts have contributed to the pull replication plugin, which provided over 2022/23 a 1000x speedup factor compared to Gerrit tradition factor. GerritForge has further improved its stability, resilience and self-healing capabilities thanks to a fully distributed and pluggable message broker system.
Gerrit v3.8 and v3.9 GerritForge helped release two major versions of Gerrit Code Review, contributing noteworthy features like Java 17 support, cross-plugin communication, importing of projects across instances and the migration to Bazel 7.
Owners plugin Jacek has completely revamped the engine of the owners plugin, boosting it with an unprecedented level of performance, hundreds of times faster than in the previous release, and bringing it to the modernity of submit requirements without the need to write any Prolog rules.
Multi-site plugin The whole team helped provide more stability and bug fixes across multiple versions of Gerrit, from v3.4 up to the latest v3.9.
JGit GerritForge kept its promises in stepping up its efforts in getting important fixes merged, including the optimisation of the refs scanning in Git Protocol v2 and the fix for bitmap processing with incoming Git receive-pack concurrency that we promised to fix at the beginning of 2023.
Migration of Eclipse JGit/EGit to GerritHub.io
The 2023 has also seen a major improvement in GerritHub stability and availability, halving the total outage in a 12-month period from 19 to 10 minutes, with a total uptime of 99.998% (source: PIngdom.com)
The whole process was completed without any downtime and a reduced read-only window on the legacy Eclipse’s instance git.eclipse.org, which was needed because of the lack of multi-site support on the Eclipse side.
What we did achieve from our goals of 2023
JGit changes: we did merge 22 changes in 2023, most of them within the list of our targets for the year. One related to the packed-refs loading optimisation was abandoned (doesn’t get much traction from the rest of the community), and the last major one left is the priority queue refactoring still in progress on stable-6.6. Also, thanks to the migration of JGit/EGit to GerritHub.io, David Ostrovsky managed to get hold of its committer status and will now be able to provide more help in support in getting changes reviewed and merged.
JGit multi-pack index support: we did not have the bandwidth and focus to tackle this major improvement. The task is still open for anyone willing to help implement it.
Git repository optimiser: we kick-started the activity and researched the topic, with Ponch presenting the current status at the Gerrit User Summit 2023 in Sunnyvale CA.
Gerrit v3.8 and project-specific change numbers: the design document has been abandoned because of the need of rethinking its end-to-end user goals. However, we found and fixed many use cases where Gerrit wasn’t using the project/change-number pair for identifying changes, which is a pre-requisite for implementing any future project-specific change number use-case.
Gerrit Certified Binaries: the Platinum Enterprise Support for Gerrit has been enriched in 2023 with the certified binaries programme, with enhanced Gatling tests and E2E validation using AWS-Gerrit. Many bugs have been found and fixed in all the active versions of Gerrit; some of them were very critical and surprisingly undiscovered for months.
GerritForge Inc. revenue targets in the USA: the revenues increased by 50% in 2023, which was slightly below the initial expectations but still remarkable, despite the latest economic downturn of the past 12 months. 100% of the business has been transferred to the USA, including the GerritForge trademark and logo and we are now ready to start a new robust growth cycle in 2024 and beyond.
Looking at the future with AI in 2024
The recent economic news in the past 6 months has highlighted a difficult moment after the COVID-19 pandemic: the conjunction of the cost of living crisis, rising interest rates and two new major wars across the globe have pushed major tech companies to revise their small to medium-term growth figures, resulting in a series of waves of lay offs in the tech sector and beyond.
Whilst the layoffs are not immediately related to a lack of profitability of the companies involved, it highlights that in the medium term there will be a lot fewer engineers looking after the production systems across the company, including SCM.
SCM and Code Review are at the heart of the software lifecycle of tech companies and, therefore, represent the most critical part of the business that would need to be protected at all costs. GerritForge sees this change as a pivotal moment for stepping up its efforts in serving the community and helping companies to thrive with Gerrit and its Git SCM projects.
How do we maintain SCM stability with fewer people?
Gerrit Code Review has become more and more stable and reliable over the years, which should sound reassuring for all of those companies that are looking at a reduced staff and the challenge of keeping the lights on of the SCM. However, the major cause of disruption is represented by what is not linked to the SCM code but rather its data.
The Git repositories and their status are nowadays responsible for 80% of the stability issues with Gerrit and possibly with other Git servers as well. Imagine a system that is receiving a high rate of Git traffic (e.g. Git clone) of 100 operations per minute, and the system is able to cope thanks to a very optimised repository and bitmaps. However, things may change quickly and some of the user actions (e.g. a user performing a force-push on a feature branch) could invalidate the effectiveness of the Git bitmap and the server will start accumulating a backlog of traffic.
In a fully staffed team of SCM administrators and with all the necessary metrics and alerts in place, the above condition would trigger a specific alert that can be noticed, analysed, and actioned swiftly before anyone notices any service degradation.
However, when there is a shortage of Git SCM admins, the number of metrics and alerts to keep under control could be overwhelming, and the trade-offs could leave the system congestion classified as a lower-priority problem.
When a system congestion lasts too long, the incoming tasks queueing could reach its limits, and the users may start noticing issues. If the resource pools are too congested, the system could also start a catastrophic failure loop where the workload further reduces the fan out of the execution pool and causing soon a global outage.
The above condition is only one example of what could happen to a Git SCM system, but not the only one. There are many variables to take into account for preventing a system from failing; the knowledge and experience of managing them is embedded in the many of the engineers that are potentially laid off, with the potential of serious consequences for the tech companies.
GerritForge brings AI to the rescue of Git SCM stability
GerritForge has been active in the past 14 years in making the Git SCM system more suitable for enterprises from its very first inception: that’s the reason why this blog is named “GitEnterprise” after all.
We have been investing over 2022 and 2023 in analysing, gathering and exporting all the metrics of the Git repositories to the eyes and minds of the SCM administrators, thanks to open-source products like Git repo-metrics plugin. However, the recent economic downturn could leave all the knowledge and value of this data into a black hole if left in its current form.
When the work of analysing, monitoring and taking action on the data becomes too overwhelming for the size of the SCM Team left after the layoffs, there are other AI-based tools that can come to the rescue. However, none of them is available “out of the box” and their setup, maintenance and operation could also become an impediment.
GerritForge has a historic know-how on knowledge-based systems and has been lecturing the community about data collection and analysis for many years in the Gerrit Code Review community, for example the Gerrit DevOps Analytics initiative back in 2017. It is now the right time to push on these technologies and package them in a form that could be directly usable for all those companies who need it now.
Introducing GHS – GerritForge-AI Health Service
As part of our 2024 goals, GerritForge will release a brand-new service called GHS, directly addressing the needs of all companies that need to have a fully automated intelligent system for collecting, analysing and acting on the Git repository metrics.
The high-level description of the service has already been anticipated at the Gerrit User Summit 2023 in Sunnyvale by Ponch and the first release of the product is due in Q1 of 2024.
How does GHS work?
GHS is a multi-stage system composed of four basic processes:
Collect the metrics of your Gerrit or other Git repositories automatically and publish them on your registry of choice (e.g. Prometheus)
Combine the repository metrics with the other metrics of the system, including the CPU, memory and system load, automatically.
Detect dangerous situations where the repository or the system is starting to struggle and suggest a series of remediation policies, using the knowledge base and experience of GerritForge’s Team encoded as part of the AI engine.
Define a direct remediation plan with suggested priorities and, if requested, act on them automatically, assessing the results.
Stage 4, the automatic execution of the suggested remediation, can be also performed in cooperation with the SCM Administrators’ Team as it may need to go through the company procedures for its execution, such as change-management process or communication with the business.
However, if needed, point 4. can also be fully automated to allow GHS to act in case the SCM admins do not provide negative feedback on the proposed actions.
What the benefits of GHS for the SCM Team?
GHS is the natural evolution of GerritForge’s services, which have historically been proactive in the analysis of the Git SCM data and the proposal of an action plan. The GerritForge’s Health Check is a service that we have been successfully providing for years to our customers; the GerritForge Health Service is the completion of the End-to-End stability that the SCM Team needs now more than ever, to survive with a reduced workforce.
To the SCM Administrator, GHS provides the metrics, analysis and tailored recommendations in real-time.
To the Head of SCM and Release Management Team, GHS gives the peace of mind of keeping the system stable with a reduced workforce.
To the SCM users and developers, GHS provides a stable and responsive system throughout the day, without slowdowns or outages
To the Head of IT, GHS allows to satisfy the company’s needs of costs and head count reduction without sacrificing the overall productivity of the Teams involved.
GerritForge’s pledges to Gerrit Code Review quality and Open-Source
GerritForge has provided Enterprise Support and free contributions to Gerrit Code Review for 14 years, pretty much since the beginning of the project. We pledged in the past to be always 100% Open-Source and do commit to our promises.
For 2024, GerritForge will focus on delivering its promising Open-Source contributions to the stability and reliability of Gerrit Code Review, with:
Support for the Gerrit Code Review platform releases, Gerrit v3.10 and v3.11
Free support and development of the Gerrit CI validation process, in collaboration with all the other Gerrit Code Review contributors and maintainers
Free Open-Source fixes for all critical problems raised by any of its Enterprise Support Customers, available to everyone in the Gerrit Code Review community
Free Open-Source code base for the main four components of the new GHS product, following the Open-Core methodology for developing the service.
With regards to the initiatives that we started in the past few years, including pull-replication and multi-site, we believe they have reached a maturity level that would not need further major refactoring and extensions in 2024. We will continue to support and improve them over the years, based on the feedback and support requests coming from the Enterprise Support Customers and the wider Gerrit Open-Source community.
GHS AI engine and dogfooding on GerritHub.io.
GHS will have a rule-based AI system that will drive all the main decisions on the selection and prioritisation of the corrective actions on the system. As with all AI systems, the engine will need to start with a baseline knowledge and intelligence and evolve based on the experience made on real-life systems.
GerritForge’s commitment to quality is based on the base principle of dogfooding, where we use the system we develop every single day and learn from it. The paradigm is on the basis of our 14 years of success and we are committed to using it also for the development of GHS.
GerritForge has been hosting GerritHub.io since 2013, and tens of thousands of people and hundreds of companies are using it for their private and Open-Source projects every single day. The system is fully self-serviced; however, still relies on manual maintenance from our Gerrit and Git SCM admins.
We are committed to starting using GHS on GerritHub.io from day 1 and use the metrics and learning of the systems to improve its AI rule engine continuously. All customers of GerritForge’s GHS service will therefore benefit from historic knowledge and experience induced by the the learnings and optimisations made on GerritHub.io for the months and years to come.
GHS = Git SCM admins humans and AI-robots working together
GHS will revolutionise the way Git SCM admins are managing the system today: they will not be alone anymore, juggling a series of tools to understand what’s going on, but they will have an intelligent and expert robot at their service, driven by the wisdom and continuous learnings made by GerritForge, at their service every single day.
We expect a different future way of working in front of us: we are embracing this radical change in how people and companies work and making GHS serve them effectively and in line with our Open-Source pledges.
The future is bright with GerritForge-AI Health Service, Git and Gerrit Code Review at your service !
Luca Milanesio GerritForge CEO Gerrit Code Review Release Manager and member of the Engineering Steering Committee
GerritForge Blog 