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How to scale a large codebase – Vercel

vercel.com · 2,158 words · saved by 1 readers

You may have heard many terms thrown around as answers — monoliths, monorepos, micro frontends, module federation, and more. At Vercel, we’ve helped thousands of large organizations evolve their codebases, and we have an opinion on the optimal way to build software. In this post, we’ll share common issues encountered when scaling a codebase over time, useful open-source tools you can leverage, and the best practices and architectural patterns to follow. This post will cover: Teams struggle to evolve their codebase without sacrificing iteration velocity. It's common to see frontend performance degrade over time as multiple teams work on a single large codebase. Releasing code can become time-consuming, taking anywhere from a few hours to several days. Teams often lack confidence in releasing code, particularly if new features are not behind feature flags. Each team may end up developing their own configuration and tooling for every new project, rather than reusing and sharing common bit

Recommendations for building and scaling large software projects. Scaling a codebase is an integra l, and inevitable, part of growing a software company. You may have heard many terms thrown around as answers — monoliths, monorepos, micro frontends, module federation, and more. At Vercel, we’ve helped thousands of large organizations evolve their codebases, and we have an opinion on the optimal way to build software. In this post, we’ll share common issues encountered when scaling a codebase over time, useful open-source tools you can leverage, and the best practices and architectural patterns

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