CI race — round 2: the real-world suite (2026-09-13)

Eleven interleaved rounds per platform of the full suite: the synthetic micro
tier plus four notorious OSS projects built cold at pinned tags inside the
timed window. Protocol: one commit per round pushed to both mirrors,
alternating which platform receives it first, ~5 min between same-platform
pushes, timestamps in push-times.jsonl, joined by
scripts/join_push_times.py. 22/22 runs succeeded; every step in every run
recorded status: ok — no skips, no reruns, nothing excluded.

Environment (as disclosed, not as matched)

	rickub	GitHub Actions
runner class	`large` — 4 vCPU / 8 GiB / 32 GiB scratch	ubuntu-latest — 4 vCPU / 16 GiB
silicon	1× AMD Ryzen 9700X bare metal (EU)	Azure standard fleet (shared)
isolation	Firecracker microVM per job	VM per job
measured single-core (probe)	594 kops/s	220 kops/s (2.7×)

vCPU COUNT is matched; silicon and RAM are not — the probe row quantifies the
CPU gap so readers can attribute. This is a platform-vs-platform race as a
customer consumes them, not a controlled-CPU experiment.

Real-world tier — medians, n=11 (p95 in parens)

step	project @ pin	github	rickub	ratio
`rust-ripgrep`	BurntSushi/ripgrep @ 15.2.0	28.75 s (29.73)	12.70 s (13.32)	rickub 2.3×
`cpp-sqlite`	SQLite amalgamation @ 3.45.1	80.86 s (86.35)	42.22 s (42.87)	rickub 1.9×
`node-typescript`	microsoft/TypeScript @ v5.9.3	47.27 s (50.98)	22.91 s (24.70)	rickub 2.1×
`java-guava`	google/guava @ v33.7.1	38.00 s (43.40)	40.27 s (42.79)	github +6%

Micro tier — medians, n=11 (p95 in parens)

step	github	rickub
rust cold build	12.97 s (18.61)	4.97 s (5.92)
rust test	1.47 s (2.04)	0.37 s (0.37)
docker build	5.77 s (10.65)	3.13 s (3.54)
push → job start	9.78 s (p95 80.2 s)	4.32 s (4.73)
end-to-end wall (run create→update)	243 s (197–342)	134 s (128–138)

Honest readings

Three of four real projects run ~2× faster on rickub (2.3× ripgrep,
2.1× TypeScript, 1.9× SQLite). The fourth — Guava — GitHub wins by 6%.
That is the most informative row in the table: a single-module Maven build
is dominated by dependency download and single-threaded javac, the least
CPU-bound workload here. Where the build is not CPU-bound, the gap closes
or flips; the probe's 2.7× single-core advantage is what the other three
rows are made of. We report the loss because it bounds the claim.
Variance is as lopsided as the medians. rickub's p95 sits within 1–6%
of its median on every step, and the whole 11-run wall-clock spans 10 s
(128–138 s). GitHub's per-step p95s run 5–30% over median and its wall
spans 145 s (197–342 s) — and one round's push→job-start was 80 s (p95
row), a queue wait, not execution. Medians understate the experienced gap.
Storage burst numbers are round-noisy: the 2 GiB dd medians flipped
between rounds (GitHub 3.9 GB/s → 1.7 GB/s; rickub 3.5 → 2.5). A
cache-warm dd burst measures as much luck as storage — read it as
"comparable", no stronger, on both platforms.
What this does NOT prove: fleet-scale queueing (one rickub node vs
GitHub's planet), warm-cache paths (cold by construction — caches are a
separate experiment), and workloads unlike these five.

Traces

Per-step results.jsonl for all 22 runs is collected under results/
(machine-local, gitignored); the public originals:

rickub runs 14–24: rickub.com/rickub/ci-bench/actions
GitHub runs 34749218316, 34749658712, 34749753971, 34750047176,
34750152332, 34750423984, 34750527899, 34750819327, 34750925882,
34751250473, 34751355186: github.com/ogirardot/ci-bench/actions
Push timestamps: push-times.jsonl → scripts/join_push_times.py →
compare.py --push-times push-times.json; raw compare output preserved in
the repo history of this commit's message thread (reproduce with the same
three commands).

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# CI race — round 2: the real-world suite (2026-09-13)

Eleven interleaved rounds per platform of the full suite: the synthetic micro
tier plus four notorious OSS projects built cold at pinned tags inside the
timed window. Protocol: one commit per round pushed to both mirrors,
alternating which platform receives it first, ~5 min between same-platform
pushes, timestamps in `push-times.jsonl`, joined by
`scripts/join_push_times.py`. 22/22 runs succeeded; every step in every run
recorded `status: ok` — no skips, no reruns, nothing excluded.

## Environment (as disclosed, not as matched)

| | rickub | GitHub Actions |
|---|---|---|
| runner class | `large` — 4 vCPU / 8 GiB / 32 GiB scratch | ubuntu-latest — 4 vCPU / 16 GiB |
| silicon | 1× AMD Ryzen 9700X bare metal (EU) | Azure standard fleet (shared) |
| isolation | Firecracker microVM per job | VM per job |
| measured single-core (probe) | 594 kops/s | 220 kops/s (2.7×) |

vCPU COUNT is matched; silicon and RAM are not — the probe row quantifies the
CPU gap so readers can attribute. This is a platform-vs-platform race as a
customer consumes them, not a controlled-CPU experiment.

## Real-world tier — medians, n=11 (p95 in parens)

| step | project @ pin | github | rickub | ratio |
|---|---|---|---|---|
| `rust-ripgrep` | BurntSushi/ripgrep @ 15.2.0 | 28.75 s (29.73) | **12.70 s** (13.32) | rickub 2.3× |
| `cpp-sqlite` | SQLite amalgamation @ 3.45.1 | 80.86 s (86.35) | **42.22 s** (42.87) | rickub 1.9× |
| `node-typescript` | microsoft/TypeScript @ v5.9.3 | 47.27 s (50.98) | **22.91 s** (24.70) | rickub 2.1× |
| `java-guava` | google/guava @ v33.7.1 | **38.00 s** (43.40) | 40.27 s (42.79) | github +6% |

## Micro tier — medians, n=11 (p95 in parens)

| step | github | rickub |
|---|---|---|
| rust cold build | 12.97 s (18.61) | **4.97 s** (5.92) |
| rust test | 1.47 s (2.04) | **0.37 s** (0.37) |
| docker build | 5.77 s (10.65) | **3.13 s** (3.54) |
| push → job start | 9.78 s (p95 **80.2 s**) | **4.32 s** (4.73) |
| end-to-end wall (run create→update) | 243 s (197–342) | **134 s** (128–138) |

## Honest readings

- **Three of four real projects run ~2× faster on rickub** (2.3× ripgrep,
  2.1× TypeScript, 1.9× SQLite). The fourth — Guava — **GitHub wins by 6%**.
  That is the most informative row in the table: a single-module Maven build
  is dominated by dependency download and single-threaded javac, the least
  CPU-bound workload here. Where the build is not CPU-bound, the gap closes
  or flips; the probe's 2.7× single-core advantage is what the other three
  rows are made of. We report the loss because it bounds the claim.
- **Variance is as lopsided as the medians.** rickub's p95 sits within 1–6%
  of its median on every step, and the whole 11-run wall-clock spans 10 s
  (128–138 s). GitHub's per-step p95s run 5–30% over median and its wall
  spans 145 s (197–342 s) — and one round's push→job-start was 80 s (p95
  row), a queue wait, not execution. Medians understate the experienced gap.
- **Storage burst numbers are round-noisy**: the 2 GiB dd medians flipped
  between rounds (GitHub 3.9 GB/s → 1.7 GB/s; rickub 3.5 → 2.5). A
  cache-warm dd burst measures as much luck as storage — read it as
  "comparable", no stronger, on both platforms.
- What this does NOT prove: fleet-scale queueing (one rickub node vs
  GitHub's planet), warm-cache paths (cold by construction — caches are a
  separate experiment), and workloads unlike these five.

## Traces

Per-step `results.jsonl` for all 22 runs is collected under `results/`
(machine-local, gitignored); the public originals:

- rickub runs 14–24: rickub.com/rickub/ci-bench/actions
- GitHub runs 34749218316, 34749658712, 34749753971, 34750047176,
  34750152332, 34750423984, 34750527899, 34750819327, 34750925882,
  34751250473, 34751355186: github.com/ogirardot/ci-bench/actions
- Push timestamps: `push-times.jsonl` → `scripts/join_push_times.py` →
  `compare.py --push-times push-times.json`; raw compare output preserved in
  the repo history of this commit's message thread (reproduce with the same
  three commands).