Table of contents

1. Why scaling code reviews matters
2. Common challenges in scaling code reviews
3. Code review best practices for large teams
4. Leveraging Graphite for managing code reviews at scale
5. Conclusion

As engineering organizations grow from small startups to enterprise-scale teams, one of the most critical challenges they face is maintaining effective code review processes. What works for a team of 5-10 developers quickly breaks down when you're managing hundreds or thousands of engineers across multiple time zones, products, and codebases. Scaling code reviews isn't just about handling more pull requests—it's about maintaining code quality, knowledge sharing, and team velocity while preventing bottlenecks that can cripple development speed. This comprehensive guide explores proven strategies, tools, and best practices for managing code reviews at scale.

Why scaling code reviews matters

Code reviews help maintain code quality, facilitate knowledge sharing, and promote consistency across large codebases. As organizations grow, the volume and complexity of code reviews increase, potentially slowing development and creating bottlenecks if not effectively managed. Unlike small team reviews where everyone can review everything, scaled code review requires:

• Distributed ownership models where specific teams or individuals own different parts of the codebase.
• Automated tooling to route reviews to appropriate reviewers.
• Clear policies and standards that work across diverse teams and projects.
• Metrics and monitoring to identify and resolve bottlenecks.

Organizations typically need to focus on scaling code reviews when they reach 50+ engineers, have multiple product teams, or maintain codebases with millions of lines of code.

Common challenges in scaling code reviews

• Volume of code changes: Increased team sizes lead to numerous code submissions, making timely reviews challenging.
• Reviewer availability: Limited availability of experienced reviewers can create review delays.
• Consistency: Maintaining uniform review standards across multiple teams becomes complex.
• Tool inefficiencies: Traditional review tools may not effectively handle the increased demand, leading to inefficiencies.

Code review best practices for large teams

Establish clear coding standards

Coding standards define clear guidelines for writing code, making reviews more straightforward and consistent. For example, standards could cover aspects like naming conventions, error handling, and documentation. Take a look at Google's coding standards for example.

Implement automated reviews

Automated tools such as linters, static analysis tools, and continuous integration (CI) platforms help detect routine errors early, enabling reviewers to focus on more complex issues.

Encourage smaller, incremental changes

Small pull requests (PRs) simplify the review process by making code changes easier to understand and quicker to review. This approach significantly reduces feedback loops.

Clearly define reviewer roles

Clearly defining reviewer responsibilities ensures accountability and expedites reviews. Roles might include mandatory senior reviewers for significant architectural changes and peer reviewers for routine updates.

Rotate reviewers regularly

Rotating reviewers promotes broader knowledge sharing and prevents expertise silos. Teams become more resilient and adaptable as more developers become familiar with various parts of the codebase.

Leveraging Graphite for managing code reviews at scale

As engineering teams grow, maintaining efficient and high-quality code reviews becomes increasingly challenging. Graphite and its AI-powered companion, Diamond, provide a robust solution to streamline and enhance the code review process at scale.

Graphite: streamlining the code review workflow

Graphite is a modern code review platform designed to improve developer productivity and collaboration. Key features include:

• Stacked pull requests: Graphite introduces a stacked changes workflow, allowing developers to create and manage stacks of related pull requests. This approach simplifies complex code changes by breaking them into smaller, manageable pieces that can be reviewed and merged independently.

• Unified pull request inbox: Developers can stay on top of their team's pull requests from a single dashboard, viewing reviews, CI status, stack information, and more in one place.

• Customizable filters and views: Graphite offers fully customizable inbox sections, enabling developers to filter pull requests based on author, CI status, reviews, labels, and other criteria to match their workflow.

• Seamless GitHub integration: Graphite integrates directly with GitHub, syncing pull requests, reviews, and comments in real-time, ensuring a smooth collaboration experience without disrupting existing workflows.

By adopting Graphite, teams can reduce the overhead associated with code reviews, improve code quality, and accelerate development cycles.

Diamond: AI-powered code review assistant

Diamond is Graphite's AI-powered code review companion that leverages advanced machine learning models to provide intelligent, context-aware feedback on pull requests. Key capabilities include:

• Automated code analysis: Diamond automatically evaluates pull requests, identifying logic bugs, security vulnerabilities, performance issues, and documentation inconsistencies.

• Codebase-aware reviews: Unlike traditional linters, Diamond understands the entire codebase, allowing it to provide more accurate and relevant feedback by considering the broader context of code changes.

• High-signal, actionable comments: Diamond focuses on delivering high-quality, actionable suggestions without overwhelming developers with noise, enhancing the effectiveness of code reviews.

• One-click fixes: Developers can quickly implement suggested changes directly from Diamond's comments, streamlining the review process and reducing the time spent on manual corrections.

• Customizable rules and templates: Teams can define custom rules or select from a library of predefined templates to enforce coding standards and best practices consistently across the codebase.

By integrating Diamond into the code review workflow, teams can enhance code quality, reduce review times, and maintain consistent coding standards across large and distributed engineering organizations.

Conclusion

Effectively scaling code reviews in large engineering teams involves adopting clear standards, automation, incremental change management, defined roles, and efficient tooling like Graphite. Implementing these best practices enables teams to maintain code quality and enhance productivity even as complexity and team size grow.