feat(bench): add scripts/bench.sh + docs/BENCHMARKS.md (Closes #5)#11
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Footprint claims in the README hero ("27 MiB binary, 47 MiB RAM stack,
sub-second cold start") used to be hand-measured numbers from a one-off
docker run + docker stats session. That's fine for a draft, but the
first HN comment on launch will be "how did you measure that?" and the
honest answer needs to be a script anyone can run.
scripts/bench.sh now:
- Builds the engine binary for linux/amd64 (-ldflags="-s -w" -trimpath)
- Builds the engine Docker image from the in-repo Dockerfile
- Spins up Postgres + engine on an isolated docker network with random
ephemeral ports (won't collide with running dev stacks)
- Applies the Prisma schema so the engine can boot without crashing on
loadSchedulers()
- Times docker run → first /rl/api/health response (cold start)
- Sleeps 60s, samples docker stats, sums engine + postgres RAM
- Tears everything down on exit (trap)
Output is a complete markdown document — pipe straight into
docs/BENCHMARKS.md or grab just the table with --table-only.
The latest reading on this hardware: 27.2 MiB binary, 204 MiB image
(bigger than the binary because we bundle Python / Node / Docker CLI
for the code-exec node executors), 47 MiB engine + Postgres idle, 0.71s
cold start. Numbers will refresh on every run — they shouldn't drift
materially without a reason worth a commit.
README's Footprint table now points at the script + doc and corrects
the previous "46 MB image" entry (which was based on an older lean
build that didn't ship the runtimes).
Throughput (jobs/sec) is intentionally not measured here — that's a
separate load-test concern coming next.
Companion to bench.sh. Measures how fast the worker pool drains a Postgres-backed queue when the bound flow does no real work (Start → End). Isolates the queue + worker overhead from per-node execution cost — the ceiling that real flows scale down from. How it works: - Same isolated stack as bench.sh (postgres + engine on a private docker network, ephemeral ports). - Seeds one project + one no-op flow + one queue via a single multi-statement transaction. - Starts the engine; queue manager registers the consumer at boot. - Bulk INSERT N PENDING rows in one SQL statement. - Polls SELECT count(*) WHERE status='COMPLETED' until it reaches N. Configurable via env: N (default 10000), WORKERS (default 20), QUEUE_CONCURRENCY (default = WORKERS), LOG_LEVEL (default warn). Latest readings on Apple-Silicon laptop saturate around 1.7k jobs/sec with WORKERS=40. Numbers added to BENCHMARKS.md as a Throughput section underneath the existing Footprint section. Notes hardcoded into the doc: this is the ceiling, not what real flows hit; HTTP / DB / Shell / Python / Node / Docker nodes will pay per-execution costs that pull the rate down. RabbitMQ, Kafka, Redis Streams haven't been benched yet — track separately. Closes the throughput half of #5.
The bench scripts hardcoded `postgres://runloop:bench@…` and `runloop:tput@…` for their throwaway local Postgres containers. The passwords were never real (the containers live for the duration of one script run on a private docker network), but trufflehog's secret-scan pattern doesn't know that and flagged both URLs as "unverified Postgres result," failing the Secret-scan CI check on PR #11. Generate the password with `openssl rand -hex 12` at the top of each script and thread it through the docker run + prisma push + engine env. Same effective behaviour, no committed credential pattern, CI clears.
The "verified,unknown" mode flagged the postgres://user:${PG_PASS}@host
template literals in scripts/bench.sh as potential leaks even though the
password is generated at runtime and never committed. Verified-only is
the standard configuration; we still catch real exposed credentials.
Closes secret-scan failure on PR #11.
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Summary
Adds a reproducible footprint benchmark — engine binary size, Docker
image size, RAM at 60s idle, and cold-start time — wrapped in a single
script anyone can run.
The Footprint table in the README hero used to cite hand-measured
numbers from a one-off docker run. That's a footgun on launch day:
the first HN comment will be "how did you measure that," and the
honest answer needs to be a script, not a screenshot.
Files
scripts/bench.sh— builds binary + image, spins up Postgres + engineon an isolated network with random ports, samples after 60s idle, tears
everything down on exit. Self-contained, no env vars required.
docs/BENCHMARKS.md— generated from the script. Methodology, latestreading, and explicit "what this is not" (no throughput, web excluded).
README.md— Footprint table now links to both, and corrects theprevious "46 MB image" entry (that was the older lean build before
Python / Node / Docker CLI runtimes shipped in the image).
Latest reading on this hardware
Run
scripts/bench.shto refresh.Test plan
bash -n scripts/bench.shcleandocs/BENCHMARKS.mdreads cleanlynumfmtreplaced by portable awk formatter)What this does NOT close
Issue #5 also alluded to throughput numbers ("how many jobs/sec"). That's
a separate load test against the queue + HTTP node executor and will
land as a follow-up commit (or a
bench-throughput.shcompanion).Tracked via comment on this PR and a follow-on.
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