Uh oh!
There was an error while loading. Please reload this page.
feat(world,world-vercel,core): bulk run cancellation primitive - #3347
Conversation
🦋 Changeset detectedLatest commit: 562e739 The changes in this PR will be included in the next version bump. This PR includes changesets to release 20 packages
Not sure what this means? Click here to learn what changesets are. Click here if you're a maintainer who wants to add another changeset to this PR |
🧪 E2E Test Results✅ All tests passed E2E Test SummarySummary
Details by Category✅ ▲ Vercel Production
✅ 💻 Local Development
✅ 📦 Local Production
✅ 🐘 Local Postgres
✅ 🪟 Windows
✅ 📋 Other
✅ vercel-multi-region
|
📊 Workflow Benchmarkscommit Backend:
📈 STSO distribution vs main (inline / queue-hop histograms)1020 steps (inline) Cumulative STSO time: main 133947ms → this run 168585ms (Δ +34638ms, +26%) 1020 steps (queue-hop) Cumulative STSO time: main 2956ms → this run 3411ms (Δ +455ms, +15%) 📜 Previous results (2)e703fbdWed, 05 Aug 2026 17:48:25 GMT · run logs
c1c4924Wed, 05 Aug 2026 03:36:41 GMT · run logs
ℹ️ Metric definitions & methodologyThe collapsed STSO distribution section above buckets every step gap of the sequential-steps run (not a sampled window), split by whether the step ending the gap ran inline — in the same warm process as the step before it, so the gap is pure framework overhead — or after a queue-hop — the first step of a fresh process, which pays queue dispatch, client reinit and event-log replay. Bars overlay the two runs: Best/P75/P90/P99 deltas compare against the most recent benchmark run on Metrics — TTFS: time to first step body (in-deployment start() → first step body, deployment clocks) · STSO: step-to-step overhead (gap between consecutive step bodies) · WO: workflow overhead (whole-run time outside step bodies, in-deployment anchored) · SL: stream latency (in-deployment write → read propagation, readAt - writtenAt) · SO: stream overhead (end-to-end write+consume time beyond the modelled generation window) Scenarios — step: one trivial no-op step, no stream; no hooks, so the run stays in turbo mode (in-process fast path) · stream: one streaming step; no hooks, so the run stays in turbo mode (in-process fast path) · hook + stream: registers a hook before one step, which exits turbo mode (dispatch path) · 1020 steps: 1020 trivial sequential steps; STSO is measured between consecutive steps in the given step ranges, and WO is the whole-run overhead outside step bodies · stream latency: parallel reader/writer steps on a dedicated stream; SL is the in-deployment write->read propagation (readAt - writtenAt) · stream overhead (text): writer streams 300 variable-length text token deltas paced at 100/s for 3s (a haiku-size LLM's token throughput) while a parallel reader drains the whole stream; SO is the end-to-end write+consume time beyond the 3s generation window (overhead/backpressure) · stream overhead (structured): same workload as stream overhead (text), but each delta is an AI-SDK-style structured object ({ type: 'text-delta', id, text }) instead of a raw string, so the SO gap vs the text scenario is the added serialization cost 🔴 marks a percentile over its target (within target is left unmarked). Targets (p75/p90/p99, ms) — TTFS 200/300/600 · SL 50/60/125 · SO 250/500/1000 All metrics are measured from deployment-side timestamps only. Runs are triggered by an in-deployment route that stamps the anchor ( Cold starts are kept in the numbers on purpose — they are part of real bursty-workload latency. The workbench deployment cold-starts the |
3e50891 to
c41bdeaCompare
VaguelySerious
left a comment
There was a problem hiding this comment.
Human review: just a bit verbose, contract seems fine
| '@workflow/world-vercel': minor | ||
| --- | ||
| Add a bulk run cancellation primitive. `@workflow/world` defines the `BulkCancelWorkflowRuns*` contract and an optional `runs.cancelMany`; `@workflow/world-vercel` implements it via a single `POST /v4/runs/cancel`; `@workflow/core` adds a `cancelRuns` helper that uses `cancelMany` when available and falls back to bounded-concurrency single-run cancellation. |
Uh oh!
There was an error while loading. Please reload this page.
Add a bulk cancellation contract to @workflow/world (schemas, types, and an optional Storage['runs'].cancelMany method), implement it in @workflow/world-vercel via a single POST /v4/runs/cancel request, and add a cancelRuns runtime helper to @workflow/core that uses the world fast path when available and otherwise falls back to bounded-concurrency (max 20) single-run cancellation. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: Peter Wielander <mittgfu@gmail.com> Signed-off-by: Karthik Kalyan <105607645+karthikscale3@users.noreply.github.com>
No backport to This commit adds a brand-new bulk run cancellation API surface: a To override, re-run the Backport to stable workflow manually via |
What
Adds a bulk run cancellation primitive across the storage layers:
BulkCancelWorkflowRuns*contract and an optionalruns.cancelMany.cancelManyas a single batched request.cancelRunshelper that usescancelManywhen available and otherwise falls back to bounded-concurrency single-run cancellation.Why
Cancelling many runs one at a time is slow and noisy. This provides a single primitive that the CLI and dashboard build on top of.
Docs
This API is v5-only; only v5 docs are updated (
storage.mdx). No v4 docs are changed.First of 3 stacked PRs.
🤖 Generated with Claude Code