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PaperClipAI/doc/ci-profiling.md
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DottaandPaperclip 7ec6fd0972 perf(ci): remove repeated test setup and fixture work (#16429)
## Thinking Path

> - Paperclip is the open source app people use to manage AI agents for
work.
> - CI must check changes without making contributors wait for repeated
setup.
> - A complete CI profile showed 158 serialized Vitest launches and
repeated dependency installs.
> - A large fixture also transferred 40,000 files to prove two different
size boundaries.
> - This PR removes repeated controller, install, build, transfer, and
wait work.
> - It keeps isolated test processes and all useful regression
boundaries.
> - Paired command benchmarks check speed and test inventories before we
claim a benefit.

## Linked Issues or Issue Description

Refs #16423 for the complete CI profiling data path. No duplicate
optimization PR was found.

**Current behavior**

Each serialized file starts a new Vitest controller. Each CI lane
restores the pnpm store and installs dependencies. Large Git scanning
and staging share one 40,000-file fixture. A readiness regression waits
over a minute for the default database idle deadline.

**Proposed behavior**

Use one controller per serialized shard, with a fresh fork for each
file. Restore exact installed dependencies and certified shared/SDK
build outputs when inputs match. Keep the normal install and build paths
on a miss. Separate the 32 MiB Git scan proof from staging above command
argument limits. Cross a real database idle deadline with a one-second
fixture setting.

**Reason and benefit**

The paired Linux CI benchmark reduced the complete 566-case serialized
shard from 303.43s to 246.96s (18.6%). The Git/database fixture command
fell from 156.54s to 33.78s (78.4%). Exact dependency/build restoration
reduced setup from 56s to 19s (66.1%). These are measured command/setup
times. They do not establish a controlled reduction in the full
workflow's queue-to-completion time.

**Breaking changes**

None to application behavior. Tests still run in full. Test results are
not cached. Cache misses preserve the existing lockfile resolution
fallback.

## What Changed

- Batch serialized files into one isolated, single-worker Vitest
invocation per shard. Give each worker its own home, config and instance
ID.
- Add a real two-order isolation check for processes, environment,
globals, timers and filesystem state.
- Add exact dependency keys for all manifests, lockfile, workspace
settings, patches, installer, runtime, platform, libc, pnpm, store and
checkout path. Cache only installed package directories, not source
fixtures.
- Add a separate content key for the shared/SDK dependency graph. Retain
the existing source/output fingerprint verifier and rebuild path. Only
an exact canonical master push can populate normal caches. Stale
lockfile fallback runs cannot publish entries.
- Keep four real Git filename lanes above 32 MiB. Use a separate
4,000-file staging/deletion case above 2 MiB. Check every staged file,
unusual names, cleanup and bounded commands.
- Configure a real one-second PostgreSQL idle timeout in the readiness
fixture. Assert that the backend connection changes and that another
connection can write the parent row.
- Add an opt-in, unprivileged Linux benchmark under `profile-ci`. It
compares the tested merge tree with its actual first parent on one
runner. It also removes installed outputs and qualifies a real cache
restore using temporary PR-scoped entries.

## Verification

- Local Node 24.19.0: unchanged serialized shard 255.69s; candidate
231.44s; all 566 cases pass in both.
- Local fixture command: unchanged 189.13s; candidate 43.39s. Candidate
scan 18.58s, staging 13.41s, database case 2.80s. All three candidate
cases pass.
- Negative control: moving readiness back inside the real parent-lock
transaction fails the shortened regression at the parent-write
assertion. The production source was restored and is absent from the
diff.
- Worker isolation check passes in both file orders.
- 565 CI policy, partition and workflow regression checks pass with
local HTTP/IPC access enabled. The first sandboxed attempt was denied
listen access; it was not a code failure.
- `actionlint` passes for the three changed workflows.
- [All 48 main CI jobs
passed](https://github.com/paperclipai/paperclip/actions/runs/38745643045)
on head `5bec2edb2b194e74352ca697f3fd1d0ac03ce967`, including full
typecheck, tests, build, browser E2E and release checks. All 158
serialized files and 3,250 cases passed through 9 controller
invocations. Full typecheck/test/build were verified in CI; they were
not all repeated locally.
- [Paired Linux benchmark
passed](https://github.com/paperclipai/paperclip/actions/runs/38745643127)
on Node 24.21.0. Its baseline is
`57fa6b358de62922cfa9a67766b2a227c434fcdf`; its candidate merge tree is
`f68f1b32966090f11647502e31852130c20237cf`. The artifact contains
results, exact case inventories, setup times and raw logs. Serialized
case identities match exactly. All three fixture contracts execute in
both variants.

  | Measured work | Baseline | Candidate | Reduction |
  |---|---:|---:|---:|
  | Complete serialized shard, 566 cases | 303.43s | 246.96s | 18.6% |
  | Git/database fixture command | 156.54s | 33.78s | 78.4% |
  | Dependency/build setup, cold vs exact hit | 56s | 19s | 66.1% |

- [Honeycomb profile export succeeded on its second
attempt](https://github.com/paperclipai/paperclip/actions/runs/38747237615/attempts/2).
The first attempt failed on GitHub HTTP 503 while downloading an
artifact, before export. Only the export was retried; tests were not
repeated. The temporary PR-scoped qualification caches were removed
after validation, reclaiming 3.34 GB. Timing artifacts remain available.
- Greptile is 5/5 on the current head, with no unresolved review
threads. Its P1 checkout-prefix finding was fixed in `5bec2edb2`; the
corrected reporter paths and paired comparison passed. Earlier runs were
superseded while this was fixed. A copy-batching experiment did not
speed up the Git fixture and was replaced by the two-boundary fixture
split.

## Risks

- A persistent controller retains transform state longer. The local
shard's maximum RSS rose from about 1.52 GB to 1.99 GB. Full CI must
confirm all shards fit the runner budget.
- Materialized caches are larger than metadata caches. The Linux
benchmark measured real archive transfer and validation after removing
installed outputs. Its hit took 19s versus 56s cold. Normal PR lanes
cannot publish cache entries. Exact misses run installation. Canonical
cache warming requires a frozen-lockfile install; the existing
stale-lockfile fallback remains uncached.
- The PR uses the trusted reusable workflow from master. The paired
benchmark directly exercises the candidate dependency action; normal
workflow adoption still requires this PR to merge. This PR does not
change the trust references. The completed main workflow took 11m02
including queue time. No controlled full-workflow latency improvement is
claimed before this workflow adopts the cache change.
- Only deterministic dependency/build outputs are reused. Broad
dependency-based test omission and caching successful test results are
deliberately excluded from this change.
- The real Runner lease minimum and cold-admission waits remain. They
protect protocol boundaries and were not shortened by weakening
production limits.

## Model Used

OpenAI GPT-6 through Codex, with reasoning, shell execution and code
tools. The runtime does not expose a more specific deployment ID or
context-window size.

## Checklist

- [x] I have included a thinking path that traces from project context
to this change
- [x] I have specified the model used (with version and capability
details)
- [x] I have checked ROADMAP.md and confirmed this PR does not duplicate
planned core work
- [x] I have searched GitHub for duplicate or related PRs and linked
them above
- [x] I have either (a) linked existing issues with `Fixes: #` / `Closes
#` / `Refs #` OR (b) described the issue in-PR following the relevant
issue template
- [x] I have not referenced internal/instance-local Paperclip issues or
links (only public GitHub `#NNN` / `github.com/paperclipai/paperclip`
URLs)
- [x] My branch name describes the change (e.g. `docs/...`, `fix/...`)
and contains no internal Paperclip ticket id or instance-derived details
- [x] I have run tests locally and they pass
- [x] I have added or updated tests where applicable
- [x] I have updated relevant documentation to reflect my changes
- [x] I have considered and documented any risks above
- [x] All Paperclip CI gates are green
- [x] Greptile is 5/5 with no open P2s, recommendations, or follow-ups
- [x] I will address all Greptile and reviewer comments before
requesting merge

---------

Co-authored-by: Paperclip <noreply@paperclip.ing>
2026-10-15 09:23:47 -05:00

12 KiB

Profile the complete PR suite

Add the profile-ci label to a PR authored by a CI CODEOWNER. Adding the label starts a fresh PR workflow run. Further pushes while the label remains also run with profiling enabled. The run is named CI profile · PR #number. It runs all lanes of the main PR suite, including middle-of-stack and release-notes-only PRs that normally skip most lanes.

After the run finishes, open its Summary and follow Open the Honeycomb waterfall. The separate CI profile workflow exports the trace after all jobs finish. Its summary has the exact time range, job/span counts, and coverage warnings. Keep the label on the PR and its head unchanged until export finishes. Remove the label to stop profiling subsequent pushes. To profile the same revision again, remove and re-add the label or rerun all jobs.

The PR author, original workflow actor, and rerun actor must all be individual users in the trusted master branch's .github/** CODEOWNERS rule. GitHub user IDs are resolved from that rule; PR edits to CODEOWNERS cannot grant access. A label on an outside contributor's PR does not enable profiling, even when a maintainer applies it. The PR still runs normal CI and needs no Honeycomb access. Failed identity lookups disable profiling.

Ordinary PRs do not write timing artifacts or export traces. The exporter job is skipped for ordinary run names. Adding another label does not run the CI matrix.

Profiling preserves the existing trusted AWS runner routing. Eligible PR jobs use paperclip-public-pr-x64; the routing gate uses paperclip-ci-routing-x64. The existing fail-closed GitHub-hosted fallback still applies if AWS routing cannot be authorized. Only the separate post-run Honeycomb exporter uses ubuntu-latest directly; it is outside the measured PR suite.

Read the waterfall

The workflow root measures elapsed time from run creation to the last job's completion. For reruns, it starts at that attempt's run_started_at instead of the original creation time. Every job is a child on the same wall clock, with its steps and available test details beneath it. All spans use a sample rate of one. There is no sampling within the selected attempt. For a compact Gantt view, open a job row's menu and choose Collapse spans at this depth. Expand an individual job to inspect its steps and test files.

The expandable hierarchy is workflow → job → step → test filename → tests. Vitest, Playwright, and Node file rows use repository-relative filenames, also available in test.file. Separate files retain their own children even when individual test names repeat across files. Honeycomb shows only the 32,000 spans closest to the root in a very large trace. All file rows are near the root, but the chart can omit some individual test rows. Use View events to query all recorded test spans. Test names are limited to 256 characters in the trace; file paths remain intact.

  • Compare the jobs that finish last (ci.finishes_last) with other overlapping work. A long job that finishes early is not necessarily delaying CI.
  • Expand setup, dependency installation, cache restore, Rust compilation, builds, and tests to find repeated or slow work.
  • ci.execution_ms measures a job's execution. ci.start_offset_ms shows when it started relative to the whole run. Do not add parallel job durations to calculate elapsed time.
  • Waiting spans cover job creation to runner start. Dependency waits can occur before GitHub creates a job, so they appear as gaps from the workflow start. GitHub does not expose a separate ready timestamp; do not interpret every gap as runner queue time or claim this is a computed dependency critical path.

GitHub job/step timestamps have second precision. Vitest and Playwright record test timestamps at the runner. Node's test reporter records completion receipt time and duration (test.clock=reporter-receipt); buffered IPC delivery can shift those small test spans. Vitest file spans include its test/hook execution and carry collection/setup durations as fields. Playwright file spans cover the first through last test attempt in that file. Rust and standalone script checks retain their full job/step timings; stable libtest does not expose per-test wall timestamps. The trace is CI timing data, not application tracing.

Scope includes all main PR lanes: policy, typecheck/release registry, general and serialized tests, Runner checks, Docker context checks, build, canary dry run, browser E2E, and aggregate checks. Separate Storybook, image, deployment, release, and live-provider eval workflows are outside this trace.

Failure, coverage, and reruns

The exporter uses GitHub's attempt-specific job API and paginates jobs and artifacts. It includes failed and cancelled jobs and uploads available test timings with always(). A force-cancelled or failed setup job may leave no artifact. Coverage warnings and ci.profile_complete=false make missing artifacts, interrupted reporters, rejected data, and absent test details visible. Test launchers write an expected-invocation record before starting each Vitest, Playwright, or Node process. Each reporter must write matching start/end records, so a missing reporter cannot hide behind another successful invocation in the same job. Direct package scripts can start a reporter without the launcher; their start/end pair proves collection. Compare ci.expected_invocations with ci.reported_invocations. Failed or cancelled workflows are conservatively incomplete because a failed command can prevent later tests or steps from running.

Each attempt gets a different trace ID. Rerunning failed jobs alone produces an attempt trace for those jobs; it does not replay completed jobs. Reruns are marked ci.partial_rerun=true conservatively. Use a fresh label-triggered run for an unambiguous full-suite baseline. GitHub may carry earlier successful jobs into the new attempt's job inventory. Jobs completed before the new attempt started are excluded and counted in ci.carried_job_count.

The exporter sends bounded batches with pauses and retries only events that Honeycomb rejects temporarily. If export still fails, inspect CI profile before rerunning it. A partial HTTP export may already have sent some spans; reruns use the same IDs but the Events API does not promise deduplication. Timing artifacts remain available for 14 days. Invalid/oversized artifacts stop export instead of silently truncating the suite. No logs, environment dumps, error messages, stack traces, or credentials are included in the exported field allowlist.

Operator setup and activation

Use the existing Honeycomb paperclip team, test environment, and a separate service dataset named paperclip-ci. Create GitHub environment ci-profiling with Selected branches and tags: allow only the branch master, with no PR-ref or tag patterns. Store environment secret HONEYCOMB_CI_API_KEY with a dedicated ingest-only key for the Honeycomb test environment. Do not create a repository- or organization-level secret of that name: the environment restriction prevents in-repository PR workflows from requesting the key. Tests still execute the PR branch; only the separate exporter runs from master. It needs event ingest permission; dataset creation permission is needed only if the dataset has not been created yet. Do not store the environment configuration key in CI. Create the repository label profile-ci if it does not exist.

ci-profile.yml runs from the trusted default-branch revision. It checks out only the exporter, installs no dependencies, and parses PR artifacts as bounded JSON without extracting or executing their contents. The PR jobs never receive the Honeycomb key. The exporter independently verifies CI CODEOWNER identities, the current label, repository, and exact tested PR revision before reading artifacts or sending data. Its credential is sent only in an HTTPS header to api.honeycomb.io; redirects are rejected. Exported fields are allowlisted. CODEOWNERS also covers scripts/ci-profile/**, so changes to the privileged exporter require infrastructure-owner review.

The new trusted workflow and routing definitions must merge to master before the label-triggered journey is active. A PR uses pr-trusted.yml@master and ci-routing.yml@master; do not change those trust references just to test this feature before merge.

Local qualification

node --test .github/scripts/tests/ci-profile.test.mjs .github/scripts/tests/ci-routing.test.mjs
node --test scripts/ci-profile/reporters.test.mjs
actionlint .github/workflows/{pr,pr-trusted,ci-routing,ci-profile}.yml
node scripts/ci-profile/export.mjs --run-id=RUN_ID --attempt=1 --historical --dry-run --output=/tmp/ci-trace.json

--historical is local-only and permits a deliberate export of an existing unlabeled run. It has complete GitHub job/step timing but cannot reconstruct test details that were never recorded. Omit --dry-run and supply HONEYCOMB_CI_API_KEY to send the selected baseline to Honeycomb. It is labeled as historical/incomplete test coverage; it is not proof of the label-triggered workflow.

References: Honeycomb trace fields, Events API, large trace display limit, GitHub workflow_run.

Qualify reductions in CI work

For changes to the stable test launcher, dependency setup, or the large Git and readiness fixtures, profile-ci also runs CI work benchmark. It uses one GitHub-hosted runner without secrets or AWS access. It compares the unchanged PR base and candidate sequentially. It records complete command times, test inventories, revisions, and failure logs in the ci-work-benchmark artifact. The serialized shard must retain the same cases. The fixture comparison retains the database contract and splits large Git scanning from bounded staging. These command timings exclude queue time and setup; use the full Honeycomb waterfall to assess the complete CI critical path.

The benchmark also exercises cold dependency setup and a real materialized cache restore after removing the installed directories. Its two qualification entries are scoped to the PR merge ref and a separate checkout path. They cannot populate master's caches. Normal PR lanes restore only; the exact canonical master push in release verification is the normal cache writer.

Materialized dependency keys include every tracked package manifest, lockfile, workspace configuration, patches, repository scripts, Node version/ABI, platform, architecture, libc, pnpm version, store location, and physical checkout path. There are no prefix restores. An input change takes the normal install path. A stale lockfile uses the existing resolution fallback but cannot publish an entry. An additional workspace install/prepare hook disables materialized reuse until its inputs are modeled. Shared/SDK build outputs have a separate key that also includes both packages' source/configuration and the build verifier. The existing verifier checks source and output fingerprints and rebuilds incomplete or changed output. Tests and their results are never cached or omitted by this mechanism.

Serialized shards share one Vitest controller with forks, isolate, one worker, and file parallelism disabled. Each file gets a separate process and test home/configuration. The isolation regression runs files in both orders and checks process IDs, environment, globals, fake timers, and filesystem state.

The readiness regression uses a real one-second PostgreSQL idle timeout and verifies that the backend connection changes while the parent write can commit. Its configured readiness window stays long. The Git regression keeps all four filename lanes above 32 MiB, while the staging case transfers and deletes 4,000 files whose filename list exceeds 2 MiB. It still checks every staged file, unusual names, snapshot ownership, cleanup, and bounded command lengths.