Modern Build Systems Explained

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Build systems are the quiet engines of software development. They don’t attract the glamour of new frameworks or LLM-powered coding tools, yet they determine how reliably and quickly you can ship software. As repositories grow, teams scale, and microservices multiply, traditional build tools begin to strain. Incremental changes become slow, builds become inconsistent across machines, and the entire delivery pipeline becomes fragile.

This is exactly why modern build systems like Bazel, Buck, and Pants emerged. They were created to solve three core problems at scale: reproducibility, incrementality, and performance. In this edition of Nullpointer Club, we unpack how these tools work, why they matter, and what they unlock for engineering organizations.

Why Traditional Build Tools Hit a Wall

Systems like Make, Maven, and Gradle were designed in an era when repositories were smaller and monoliths were the norm. As engineering teams grew and codebases expanded, three challenges became painfully obvious:

1. Non-deterministic builds

Builds often varied between developer machines due to environment drift, caching inconsistencies, or unpinned dependencies.

2. Slow, non-incremental rebuilds

Changing a single file could trigger a rebuild of half the project due to imprecise dependency tracking.

3. Lack of horizontal scalability

These systems weren’t built to orchestrate thousands of targets, remote caches, or distributed build execution.

Modern tools emerged because companies like Google, Meta, and Twitter hit scaling issues no mainstream build system could solve.

What Modern Build Systems Do Differently

1. They enforce deterministic, reproducible builds

Tools like Bazel and Buck require explicit dependency declarations and controlled execution environments.
The result:

• Same inputs always produce the same outputs

• Builds become testable, cacheable, and shareable

• CI inconsistencies disappear

Determinism is the foundation that enables remote caching and distributed execution to work reliably.

2. They use fine-grained, graph-based dependency modeling

Instead of large opaque tasks, modern systems break the build into thousands of small, directed actions.
This enables:

• Precise incremental builds

• Strong isolation

• Faster rebuild times

• Parallelism by default

You change one file, and only the exact dependent targets are rebuilt.

3. They support remote caching and remote execution

This is where the performance magic happens.
Teams can:

• Cache build artifacts at a global level

• Share results across developers and CI

• Distribute build steps across many machines

This is critical for codebases measured in millions of LOC or dozens of languages.

4. They support polyglot monorepos

Large organizations run monorepos with mixed tech stacks (Java, Go, Python, Rust, JS).
Modern systems treat all languages as equal citizens, producing a unified build graph.

Bazel, Buck, and Pants: What Each One Brings

Bazel

Originally from Google, Bazel is the flagship of modern build systems.
Its strengths include:

• Battle-tested at massive scale

• Extremely strong caching guarantees

• A rich rule ecosystem

• Strict sandboxing

• First-class remote execution support

It’s the go-to choice for companies running large monorepos with complex dependency graphs.

Buck

Meta’s Buck was designed for very fast incremental builds and deep caching.
Key features:

• Fine-grained dependency modeling

• High focus on incremental performance

• Optimized for Android and Objective-C builds

• Fast development feedback loops

Buck 2 moves even closer toward deterministic and distributed builds.

Pants

Pants started at Twitter as a monorepo-native build system and has evolved significantly in its v2 rewrite.
It offers:

• A highly user-friendly UX

• Strong Python, JVM, and Go support

• Incrementality without requiring build files everywhere

• Efficient local and remote caching

Pants appeals to mid-sized teams that want modern build guarantees without Bazel’s configuration complexity.

How These Tools Improve Engineering Velocity

1. Faster builds → faster feedback loops

Developers avoid the “waiting for CI” tax.
A 10-minute build dropping to 30 seconds compounds massively across teams.

2. Reproducibility improves reliability

Debugging becomes easier.
CI flakiness drops.
Security teams gain confidence in build integrity.

3. Build graph visibility increases codebase health

Clear boundaries and dependencies reduce unintended coupling.

4. Remote execution scales with your team

The build no longer depends on a developer’s laptop performance.

5. Better foundations for secure supply chains

Reproducible builds enable:

• Verified provenance

• Artifact signing

• More trustworthy releases

In a world of increasing supply chain attacks, deterministic builds are not optional.

When Should a Team Consider Moving to a Modern Build System?

Adopting Bazel or Pants is not trivial. Migration takes planning and a shift in engineering culture.
A team should consider the switch when:

• Build times drag down developer productivity

• CI reliability becomes a recurring pain

• Your repo is moving toward a monorepo structure

• You have multi-language workflows

• You want stronger supply chain guarantees

• Teams are duplicating build logic across services

For small projects, modern systems may feel heavy. But for organizations planning to scale, they provide an architectural foundation that pays off for years.

Closing Thoughts

Modern build systems are not niche engineering tools—they are strategic infrastructure. Bazel, Buck, and Pants exist because large-scale software development demands determinism, speed, and repeatability. As codebases grow and security expectations rise, these systems provide the clarity, performance, and guarantees traditional build tools can’t. In the long run, the teams that invest early in reproducible and scalable build pipelines move faster, break less, and ship with far more confidence.

See you next time,

— Team Nullpointer Club