Why Grog?

Many teams are recognizing the strong organizational value in moving to a monorepo (see why). Initially, teams might simply place all their projects in one repository. However, as complexity grows and interdependencies emerge, challenges arise—especially when working with multiple languages or frameworks.

At this point, most teams are stuck between a rock and a hard place:

1. Adopt sophisticated build tools like Bazel or Pants.
2. Create ad-hoc solutions with scripts, Makefiles, or internal CLIs.

Adopting Bazel requires lots of resources and is almost certainly overkill for small to medium-sized teams. Grog instead offers the building blocks(parallelization and caching) that ease the pain while remaining flexible. Below we explore when and why Grog is and is not a better solution than more sophisticated build tooling or rolling your own scripts.

Why Bazel can be overkill

Bazel is Google’s battle-tested, open-source build system that guarantees hermetic, reproducible builds—no matter how large your codebase grows. Its lightning-fast caching, fine-grained dependency tracking, and parallel execution make every build predictable and snappy. That said, in smaller teams you often hit a few common roadblocks:

1. Steep learning curve Bazel uses its own Starlark-based BUILD language and enforces a specific workspace layout. You can spend several weeks just getting comfortable writing and tuning BUILD files, macros, and custom rules before moving beyond “hello world.”
2. Lagging tooling support While Bazel has first-class integrations for C++, Java, and Go, adding or updating rules for newer languages or frameworks can be tricky. You’ll frequently find yourself writing and maintaining custom rules or waiting on the community for updates. Even simple things like building a Docker image can become quite tricky with Bazel.
3. Infrastructure demands To unlock remote caching and distributed execution, you need dedicated servers (or a managed service), plus someone to provision, monitor, and troubleshoot them. Small teams often lack the headcount or budget to run a full-blown buildfarm.

While Pants offers a more ergonomic approach with first-class Docker and Python support and a more intuitive way of writing BUILD files it still requires a lot more investment than what feels necessary for smaller teams.

Grog’s Philosophy

Bazel and Pants are this complicated and tricky to adopt not because their author are sadistic, but because reproducibility is a challenging problem that requires constraints on what a build command can do.

Grog on the other hand takes a simpler more “grug-brained” approach: Grog doesn’t impose a custom build language or sandboxing layer. Instead, it treats each build step as a simple command you already know. Grog scans your declared inputs, hashes them, and only re-runs a target when one of its inputs has changed. Independent targets are dispatched in parallel according to the dependency graph, maximizing CPU utilization without any additional setup.

As a result, you keep using your existing scripts, Makefile rules, NPM commands, or any CLI you love—while grog transparently handles change detection, (remote) caching, and concurrent execution. This focused approach delivers immediate ROI for small teams: there’s no new DSL to learn, minimal infrastructure to stand up, and visible speed-ups on every incremental build.

When not to choose Grog?

Grog might not be the right fit for you, if:

• You are using a single language stack that already has mature mono-repo build support (Java/Gradle, Golang, JS with Turborepo, …).
• You have higher demands for performance and reproducibility AND the spare engineering resources to adopt and maintain Bazel.