In evanix we explored making the scheduling of Nix builds more controllable. in particular, we look into implementing constraints such as –-max-builds and –-max-build-time, which ensure that build operations remain within manageable limits while maximizing throughput.
explore how evanix achieves its goals in this informative blog
- Utilize mixed-integer programming to approximate the most optimal solution efficiently, using the HiGHS solver.
- Maximize the number of requested packages produced within a specified budget, with a maximum constraint of n builds.
- Maximize the number of requested packages produced within a specified budget, constrained by a maximum time limit of t.
- Utilize data from Hydra to estimate the build times for derivations.
- Develop a linear regression model to estimate build times for derivations when such data is unavailable in Hydra.
- Implement unit tests using Meson’s built-in testing framework, and integration tests utilizing the NixOS integration testing framework.
- Implement a pipelined architecture to initiate the building of derivations immediately following their evaluation.
- Enhance the linear regression model and conduct additional tests to validate its performance and accuracy.
- Integrate the linear regression model with evanix
- 1.0 refactor
$ nix run github:sinanmohd/evanix -- --help
Usage: evanix [options] expr
-h, --help Show help message and quit.
-f, --flake Build a flake.
-d, --dry-run Show what derivations would be built.
-s, --system System to build for.
-m, --max-builds Max number of builds.
-t, --max-time Max time available in seconds.
-b, --break-evanix Enable experimental features.
-r, --solver-report Print solver report.
-p, --pipelined <bool> Use evanix build pipeline.
-l, --check_cache-status <bool> Perform cache locality check.
-c, --close-unused-fd <bool> Close stderr on exec.
-e, --statistics <path> Path to time statistics database.
-k, --solver sjf|conformity|highs Solver to use.