Speedup your CI

There is an article in Russian about speeding up building and testing in CI. This page contains a list of tools that helps with speedup.

Fast source code checkout

• Use --depth N in Git.
• Enable parallel mode in Git:
  • git config fetch.parallel 0
  • git config submodule.fetchJobs 0

Hints with CI setup

• Ignoring paths with non-relevant files
  • Github CI: paths-ignore (Documentation)
• Use caching dependencies
  • Github Actions (Documentation)

Hints with OS setup

• Disable unnecessary triggers in packages (Processing triggers for man-db (2.9.4-2) ...).
  • Debian - https://wiki.debian.org/DpkgTriggers

Compilation and linking

• Profile build system
  • ninjatracing - converts .ninja_log files to chrome's about:tracing format.
  • buildbloat converts ninja build logs to webtreemap JSON files.
• Use parallel mode.
  • Make - option -j
  • Ninja - option -j
  • CMake - https://www.kitware.com//cmake-building-with-all-your-cores/
• Replace Make with Ninja.
• Replace default linker with Mold. Faster in 17 times in comparison with GNU gold and 3-5 times in comparison with LLVM lld.
• Include what you use - is a tool for use with clang to analyze #includes in C and C++ source files.
• Use cache
  • ccache - is cache is a compiler cache. ccache could speed up your build in 30 (!) times. See performance results.
  • sccache - is ccache with cloud storage. Supported C, C++ and Rust.
• Use distributed compilation (boost 2-4 times)
  • Goma (C/C++) - is a distributed compiler service for open-source project such as Chromium and Android. It's some kind of replacement of distcc+ccache. Used by Google.
  • nocc (C/C++) - is distributed C++ compiler. Used by VK.
  • distcc is a fast, free distributed C/C++ compiler.
  • icecream - is a distributed compiler with a central scheduler to share build load. Created by SUSE.

Running unit tests

• Use distributed running
  • gg - the Stanford Builder. Uses lambdas for running self-contained binaries, see a paper From Laptop to Lambda: Outsourcing Everyday Jobs to Thousands of Transient Functional Containers.
  • llama - is a tool for running UNIX commands inside of AWS Lambda. Its goal is to make it easy to outsource compute-heavy tasks to Lambda, with its enormous available parallelism, from your shell.

Running e2e tests

• Fail fast
• Parallel execution
• Profile your tests
  • Python pytest-profiling
  • Ruby test-prof
• Test prioritization
• Test minimization
• Test impact analysis

Setup test environment