I lead a bazel conversion for a pretty complex piece of software written in 5+ programming languages and shipping native binaries to all 3 major OSes a few years ago, and it took multiple years to get it done.

For a less complex project (1 programming language, still shipping to all 3 major OSes), with my knowledge and agents I got the bazel conversion done in 2 weeks.

The setup cost for bazel just went down by a lot, and I don't think the industry as a whole is aware of that yet.

Bazel seems to have a lot of tradeoffs, from setup time of the sandbox for each task, to ergonomics that lead folks to maintain parallel 'normal' tooling.

Plus, 'with a warm cache' is doing heavy lifting, what's the real cache hit rate for a week of development? Investing in improving the cold build and frequent actions is still important with bazel or any incremental builder.

I'm not sure it's useful to talk about bazel broadly, it's actual performance and behavior comes down to the rules you use. You can configure bazel like turbo/nx and cache tsc/vitest/eslint on each package.json module, and get course cached units that are evicted on every change, or you can use gazelle and target per-file actions which are only invalidated when their dependencies change. But that trades off batching unless you use workers.

Can't comment on Bazel specifically, but having worked with both nx and turbo, the bottleneck was usually network and disk IOPS rarely compute.

Even fully cached outputs needs to fetched and read from a remote server[1]. A step n-1 outout fetched from remote cache server need to written to disk and then again read by step n[3] - all disk I/O and network bound operations.

10s may be achievable/realistic goal in the Java/C++ world where Bazel normally seen. In TS eco-system most people would be over the moon to get into ballpark of 1-2m for a decently large monorepo.

We should define Build more clearly here, if you mean running just transpile/compile steps or the full series of steps that includes tests (as the linear post here is talking about). It is hard to see even a small sub-set of a large suite of test that require a virtual DOM or a real browser can run in 10s or less.

[1] Typical for say managed CI setup .

[3] Common run-of-the-mill frontend + backend stacks in different languages etc.