_ram_gb read mem_total_mb while mem_available_mb sat next to it, added by
3e9deab6f7 for the drill abort and never carried over here. The ceiling exists
to stop the sidecar from competing with what already runs, so measuring the
machine instead of what is free made the term inert: on a 16 GB runner it
computed five workers while 5.5 GB was actually available, and the CI cap was
the only thing that ever bound.
Reading MemAvailable makes the guard real and self-limiting, which matters now
that the onion case raises the count. Against the memory the run itself reports:
PASS 1, 9113M free clearnet 1 onion 2
PASS 2, 5550M free clearnet 1 onion 1
Also withdraws a CI CPU divisor I had added on a false premise. It cited the
matrix telemetry stall60 as evidence that reserving three cores of four buys
nothing on a CI runner - but mem_stall_pct reads /proc/pressure/memory
(utils/env/runtime.py:84), so that figure proves memory headroom and says
nothing about CPU. Raising the clearnet count needs CPU evidence this run does
not carry, and a contention flake would cost coverage, so the divisor stays at
four until something measures the CPU side.
The onion lift keeps its own justification, which never rested on that number:
a browser waiting on Tor circuits does not consume CPU, measured at 4817s over
Tor against 911s on clearnet for the same specs on the same cores.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The sidecar is the dominant cost of an onion round and almost free without it.
Measured on one Nextcloud variant at equal mode and filesystem, differing only
in the onion axis, sync pass:
test-e2e-playwright 4817s over Tor 911s on clearnet +5.3x
sys-svc-compose 2294s 2174s +120s
everything else < +25s
The whole Tor surcharge sits in one role. Tor burns no browser CPU, so a 5.3x
wall clock against identical specs on identical cores is circuit latency: the
phase waits rather than computes. The CPU divisor that sizes the clearnet count
does not describe it, and on a 4-core runner it yields exactly one worker,
which leaves the CI cap of 2 unreachable.
compute_workers takes an onion flag and, when set, multiplies the count and
caps it separately. The CI ceiling is overridden rather than respected: it
describes CPU contention, which Tor does not create. ram_workers keeps its
veto, because circuits are cheap and browsers are not.
The lookup reads the transport itself, from the same source the role derives
its own flag from, lookup(tls, application_id, url.base) tested for .onion,
following the _swarm_prefix idiom in plugins/lookup/image.py: read from
variables, render through the templar, fall back to the safe answer. One truth
about the onion state, and a caller asking for a worker count cannot forget to
pass it.
Factor 2 and cap 4 rather than more: each worker holds its own circuits and the
Tor daemon is the next bound, which no measurement here reaches. Expect the
sidecar near 2.6ks per pass instead of 4.8ks, roughly 4.4ks per onion job
against a 20.4ks budget. It does not help a clearnet round, where the sidecar
costs 911s to begin with.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
_ram_gb reimplemented the /proc/meminfo parse that utils/env/runtime.py owns: same pseudo-file, same MemTotal scan, same line.split()[1], same swallow-and-fall-back guard. It now calls mem_total_mb().
The error semantics map exactly. The helper returns 0 for an unreadable file, a malformed line and a missing field; all three previously produced 4.0, and 0 is falsy, so the conservative fallback still covers every one of them.
One real delta: the helper floors kB to MB before the GB conversion, so _ram_gb loses up to 0.001 GB. That can only move the worker count where MemTotal/2 sits within half a megabyte of an exact 1.5 GiB multiple, and it moves it downwards, which is the direction this sizing already prefers.
Touching the file pulled its ten pre-existing narration comments into the diff-scoped comment lint. They were deleted, not relabelled.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Resolve the 80 open CodeQL/code-scanning alerts on this branch.
Security-sensitive fixes:
- cli/administration/deploy/development: break the unsafe import cycle by
extracting the env/arg helpers into a leaf module `env.py`, giving the
load-time DAG compose -> common -> deps -> env.
- web-app-bluesky login-broker server.js: prototype-pollution guard on
cookie parsing, CR/LF + control-char log sanitisation, HTML-escaped
exception text, and a ReDoS-bounded handle regex.
- web-app-baserow SSO: harden the open-redirect `next` handling.
- network diagnose probes: require TLS >= 1.2.
- actionlint installer: validate tar members against path traversal.
- decidim/apt-purge lint regexes: rewrite to avoid catastrophic backtracking.
- 6x Playwright URL regexes anchored; crs-k/stale-branches pinned to a commit SHA.
Mechanical cleanups: unused imports/globals/locals, empty-except comments,
import-and-import-from, implicit-string-concat, multiple-definition,
unreachable/useless-assignment.
False positives are intentionally left in place (Django settings patches,
Odoo __manifest__, side-effect imports, cross-module symbols).
Recurrence guards:
- import-linter contract (pyproject + tests/lint) locks the dev-deploy
package acyclic; a new cycle now fails CI instead of only CodeQL.
- new lint test requires every bandit (S###) `noqa` to carry a justification.
- BLE001 (blind-except) added to ruff as a ratchet (tests/roles exempt,
current production offenders grandfathered).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add plugins/lookup/playwright_workers.py computing a conservative parallel-worker count (CPU/RAM-derived, app-under-test concurrency-capped, reduced on CI) and wire test_e2e_playwright_workers + test_e2e_playwright_fully_parallel + test_e2e_playwright_test_timeout into playwright.config.js (read from env) and 02_run_one.yml (passed via -e). fullyParallel stays false so parallelism is file-level only and intra-file ordering assumptions stay safe. Raise run_timeout to 3600 for addon-heavy roles (nextcloud ~50 specs).
Split the role's variables by Ansible precedence and intent: derived/fixed constants live in vars/main.yml (UPPERCASE, high precedence, not operator-tuned), operator-tunable knobs live in defaults/main.yml (lowercase, overridable). VARIANT_INDEX stays UPPERCASE with a single definition. Update references across tasks/templates/inventory/docs accordingly. Includes a unit test for playwright_workers and an autoformat pass.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
kevinveenbirkenbachandClaude Opus 5