Scheduled runs create predictable hourly spikes that compete with
on-demand runs for node capacity. Runs triggered "on-demand" via the
SDK, API, or dashboard, are more sensitive to cold start latency since
users are typically
waiting on the result. When a burst of scheduled runs lands at the top
of the hour, it can saturate the shared pool resources causing
contention, affecting cold starts across the board.
The idea in this change is to absorb these periodic spikes in a
dedicated pool without affecting the cold starts of on-demand runs.
Scheduled runs are inherently less sensitive to cold starts.
### Changes in this PR
Follows up on run annotations (#3241), which made trigger origin
available on every run in the tree. This PR exposes
annotations at dequeue time to the supervisor. This enables scheduling
decisions based on trigger source.
The affinities are soft preferences at schedule time, so runs fall back
gracefully if the target pool is out out of capacity.
Queue limit ServiceValidationErrors were being logged at error level.
These are
expected validation rejections, not bugs.
- Add logLevel property to ServiceValidationError (webapp + run-engine)
- Set logLevel: warn on all queue limit throws
- Schedule engine: detect queue limit failures and log as warn
- Redis-worker: respect logLevel on thrown errors
Adds an `annotations` JSONB column to task runs that captures where and
how each run was triggered.
This enables filtering and analyzing trigger origins without querying up
the run tree. Also enables making scheduling decisions based on the
trigger source, e.g., use separate affinities for scheduled runs.
Each run records:
- **triggerSource**: who initiated it (sdk, api, dashboard, cli, mcp,
schedule)
- **triggerAction**: what kind of action (trigger, replay, test)
- **rootTriggerSource**: the trigger source of the root ancestor,
propagated through the entire run
tree
- **rootScheduleId**: schedule id, in case the run tree was triggered
from a schedule
Currently the main motivation for annotations it to determine whether a
run is part of a schedule-originated tree without traversing ancestors.
### A couple of design considerations
- **Decoupled source from method**: triggerSource and triggerAction are
separate fields to avoid
combinatorial explosion (every new source × every new action)
- **Server-side first**: all annotation values are primarily determined
on the server, only a minor SDK change needed
- **Forward-compatible**: annotation fields use
`z.enum([...]).or(anyString)` so new values can be
added without breaking validation; we currently don't need an explicit
version field for annotations.
Note: `metadata` would have been a more fitting name for the db column,
as it is consistent with other tables where we store this type of
information. It is already in use to store user metadata though, so we
go with `annotations` instead.
- Full prompt management UI: list, detail, override, and version
management for AI prompts defined with `prompts.define()`
- Rich AI span inspectors for all AI SDK operations with token usage,
messages, and prompt context
- Real-time generation tracking with live polling and filtering
## Prompt management
Define prompts in your code with `prompts.define()`, then manage
versions and overrides from the dashboard without redeploying:
```typescript
import { task, prompts } from "@trigger.dev/sdk";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
import { z } from "zod";
const supportPrompt = prompts.define({
id: "customer-support",
model: "gpt-4o",
variables: z.object({
customerName: z.string(),
plan: z.string(),
issue: z.string(),
}),
content: `You are a support agent for Acme SaaS.
Customer: {{customerName}} ({{plan}} plan)
Issue: {{issue}}
Respond with empathy and precision.`,
});
export const supportTask = task({
id: "handle-support",
run: async (payload) => {
const resolved = await supportPrompt.resolve({
customerName: payload.name,
plan: payload.plan,
issue: payload.issue,
});
const result = await generateText({
model: openai(resolved.model ?? "gpt-4o"),
system: resolved.text,
prompt: payload.issue,
...resolved.toAISDKTelemetry(),
});
return { response: result.text };
},
});
```
The prompts list page shows each prompt with its current version, model,
override status, and a usage sparkline over the last 24 hours.
From the prompt detail page you can:
- **Create overrides** to change the prompt template or model without
redeploying. Overrides take priority over the deployed version when
`prompt.resolve()` is called.
- **Promote** any code-deployed version to be the current version
- **Browse generations** across all versions with infinite scroll and
live polling for new results
- **Filter** by version, model, operation type, and provider
- **View metrics** (total generations, avg tokens, avg cost, latency)
broken down by version
## AI span inspectors
Every AI SDK operation now gets a custom inspector in the run trace
view:
- **`ai.generateText` / `ai.streamText`** — Shows model, token usage,
cost, the full message thread (system prompt, user message, assistant
response), and linked prompt details
- **`ai.generateObject` / `ai.streamObject`** — Same as above plus the
JSON schema and structured output
- **`ai.toolCall`** — Shows tool name, call ID, and input arguments
- **`ai.embed`** — Shows model and the text being embedded
For generation spans linked to a prompt, a "Prompt" tab shows the prompt
metadata, the input variables passed to `resolve()`, and the template
content from the prompt version.
All AI span inspectors include a compact timestamp and duration header.
## Other improvements
- Resizable panel sizes now persist across page refreshes (patched
`@window-splitter/state` to fix snapshot restoration)
- Run page panels also persist their sizes
- Fixed `<div>` inside `<p>` DOM nesting warnings in span titles and
chat messages
- Added Operations and Providers filters to the AI metrics dashboard
## Screenshots
<img width="3680" height="2392" alt="CleanShot 2026-03-21 at 10 14
17@2x"
src="https://github.com/user-attachments/assets/f3e59989-a2fa-4990-a9d0-3cacda431868"
/>
<img width="3680" height="2392" alt="CleanShot 2026-03-21 at 10 15
37@2x"
src="https://github.com/user-attachments/assets/2f2d02df-2d2b-44fb-ac6f-9153f6a6c387"
/>
<img width="3680" height="2392" alt="CleanShot 2026-03-21 at 10 15
54@2x"
src="https://github.com/user-attachments/assets/baa161e0-ef91-4fa4-a55f-986b71cccdf0"
/>
- Automatic LLM cost enrichment for AI SDK spans (streamText,
generateText, generateObject) or any other spans that use semantic
gen_ai attributes with support for 145+ models
- New AI span inspector sidebar showing model, tokens, cost, messages,
tool calls, and response text
- LLM metrics dual-write to ClickHouse `llm_metrics_v1` table for
analytics
- LLM metrics built-in dashboard (unlinked at the moment)
- Provider cost fallback — uses gateway/OpenRouter reported costs from
`providerMetadata` when registry pricing is unavailable
- Prefix-stripping for gateway/OpenRouter model names (e.g.
`mistral/mistral-large-3` matches `mistral-large-3` pricing)
- Admin dashboard for managing LLM model pricing (list, create, edit,
delete, search, test pattern matching)
- Missing models detection page — queries ClickHouse for unpriced models
with sample spans and Claude Code-ready prompts for adding pricing
- AI span seed script (`pnpm run db:seed:ai-spans`) with 51 spans across
12 provider systems for local dev testing
- UI fixes: `completionTokens`/`promptTokens` aliases,
`ai.response.object` display for generateObject, cache read/write token
breakdown
## Screenshots:
<img width="1030" height="104" alt="CleanShot 2026-03-17 at 16 48 54@2x"
src="https://github.com/user-attachments/assets/bc8fccda-e48b-4d0c-bfb1-e620064e5979"
/>
<img width="1094" height="1512" alt="CleanShot 2026-03-17 at 16 49
23@2x"
src="https://github.com/user-attachments/assets/c2424569-d07e-4d67-a436-e8250043a1ee"
/>
<img width="1074" height="1412" alt="CleanShot 2026-03-17 at 16 49
18@2x"
src="https://github.com/user-attachments/assets/22342ac4-4769-45d1-a328-a24fb9a82a50"
/>
<img width="1012" height="2292" alt="CleanShot 2026-03-17 at 16 39
01@2x"
src="https://github.com/user-attachments/assets/59e327d1-6652-4293-8be0-bb8326e5fbc5"
/>
<img width="3680" height="2392" alt="CleanShot 2026-03-15 at 08 29
38@2x"
src="https://github.com/user-attachments/assets/1f77beb8-de67-495b-b890-bcdb8d7f1fe8"
/>
---------
Co-authored-by: James Ritchie <james@trigger.dev>
When processing batchTriggerAndWait items, each batch item was acquiring
a
Redis lock on the parent run to insert a TaskRunWaitpoint row. With high
concurrency (processingConcurrency=50), this caused
LockAcquisitionTimeoutError
(880 errors/24h in prod), orphaned runs, and stuck parent runs.
Since blockRunWithCreatedBatch already transitions the parent to
EXECUTING_WITH_WAITPOINTS before items are processed, the per-item lock
is
unnecessary. The new blockRunWithWaitpointLockless method performs only
the
idempotent CTE insert and timeout scheduling without acquiring the lock.
## Summary
Major expansion of the MCP server (14 → 25 tools), context efficiency
optimizations, new API endpoints, and a fix for the dev CLI leaking
build directories on disk.
### New MCP tools
- **Query & analytics**: `get_query_schema`, `query`, `list_dashboards`,
`run_dashboard_query` — query your data using TRQL directly from AI
assistants
- **Profile management**: `whoami`, `list_profiles`, `switch_profile` —
see and switch CLI profiles per-project (persisted to
`.trigger/mcp.json`)
- **Dev server control**: `start_dev_server`, `stop_dev_server`,
`dev_server_status` — start/stop `trigger dev` and stream build output
- **Task introspection**: `get_task_schema` — get payload schema for a
specific task (split out from `get_current_worker` to reduce context)
### New API endpoints
- `GET /api/v1/query/schema` — discover TRQL tables and columns
(server-driven, multi-table)
- `GET /api/v1/query/dashboards` — list built-in dashboard widgets and
their queries
### New features
- **`--readonly` flag** — hides write tools (`deploy`, `trigger_task`,
`cancel_run`) so agents can't make changes
- **`read:query` JWT scope** — new authorization scope for query
endpoints, with per-table granularity (`read:query:runs`,
`read:query:llm_metrics`, etc.)
- **Paginated trace output** — `get_run_details` now paginates trace
events via cursor, caching the full trace in a temp file so subsequent
pages don't re-fetch
- **MCP tool annotations** — all tools now have
`readOnlyHint`/`destructiveHint` annotations for clients that support
them
- **Project-scoped profile persistence** — `switch_profile` saves to
`.trigger/mcp.json` (gitignored), automatically loaded on next MCP
server start
### Context optimizations
- `get_query_schema` requires a table name — returns one table's schema
instead of all tables (60-80% fewer tokens)
- `get_current_worker` no longer inlines payload schemas — use
`get_task_schema` for specific tasks
- Query results formatted as text tables instead of JSON (~50% fewer
tokens for flat data)
- `cancel_run`, `list_deploys`, `list_preview_branches` formatted as
text instead of raw `JSON.stringify()`
- Schema and dashboard API responses cached (1hr and 5min respectively)
### Bug fixes
- Fixed `search_docs` failing due to renamed upstream Mintlify tool
(`SearchTriggerDev` → `search_trigger_dev`)
- Fixed `list_deploys` failing when deployments have null
`runtime`/`runtimeVersion` fields (fixes#3139)
- Fixed `list_preview_branches` crashing due to incorrect response shape
access
- Fixed `metrics` table column documented as `value` instead of
`metric_value` in query docs
- Fixed `/api/v1/query` not accepting JWT auth (added `allowJWT: true`)
### Dev CLI build directory fix
The dev CLI was leaking `build-*` directories in `.trigger/tmp/` on
every rebuild, accumulating hundreds of MB over time (842MB observed).
Three layers of protection added:
1. **During session**: deprecated workers are pruned (capped at 2
retained) when no active runs reference them, preventing unbounded
accumulation
2. **On SIGKILL/crash**: the watchdog process now cleans up
`.trigger/tmp/` when it detects the parent CLI was killed
3. **On next startup**: existing `clearTmpDirs()` wipes any remaining
orphans
## Test plan
- [ ] `pnpm run mcp:smoke` — 17 automated smoke tests for all read-only
MCP tools
- [ ] `pnpm run mcp:test list` — verify 25 tools registered (21 in
`--readonly` mode)
- [ ] `pnpm run mcp:test --readonly list` — verify write tools hidden
- [ ] Manual: start dev server, trigger task, rebuild multiple times,
verify build dirs stay capped at 4
- [ ] Manual: SIGKILL the dev CLI, verify watchdog cleans up
`.trigger/tmp/`
- [ ] Verify new API endpoints return correct data: `GET
/api/v1/query/schema`, `GET /api/v1/query/dashboards`
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Queues with concurrency keys now appear as a single entry in the master
queue instead of one entry per key. This prevents high-CK-count tenants
from consuming the entire `parentQueueLimit` window and starving other
tenants on the same shard.
A new per-queue **CK index** (sorted set) tracks active concurrency key
sub-queues. The master queue gets one `:ck:*` wildcard entry per base
queue. Dequeuing from that entry round-robins across sub-queues,
maintaining per-CK concurrency tracking and fairness.
All existing operations (enqueue, dequeue, ack, nack, DLQ, TTL expiry)
are CK-index-aware and keep the index consistent. Old-format entries
drain naturally during rollout — no migration step needed, single
deploy.
## Adds 2 self serve features
### 1. self serve preview branches
- Copies the patterns of the self serve concurrency
- Self serve only available on Pro plan (otherwise you are linked to the
billing plans page)
- Global self serve branches limit: 180 (+20 for the Pro plan). It can
be overridden per Org
- You need to archive branches before reducing the number of extra
branches you're paying for
- Branches are removed immediately but remain billed until the end of
the billing cycle like extra concurrency
### 2. self serve team members
- Copies the patterns of the self serve concurrency
- Self serve only available on Pro plan (otherwise you are linked to the
billing plans page)
- Global self serve members is unlimited but can be limited with the
same env var quota and overridden per org if needed
- You need to remove team members before reducing the number of members
you pay for
- Team members are removed immediately but remain billed until the end
of the billing cycle like extra concurrency
Deprecates the syncVercelEnvVars build extension and adds warnings in
both the Vercel integration docs and the extension's own page to prevent
conflicts with the native env var sync
## Summary
2 new features, 2 improvements.
## Improvements
- Add syncSupabaseEnvVars to pull database connection strings and save
them as trigger.dev environment variables
([#3152](https://github.com/triggerdotdev/trigger.dev/pull/3152))
- Auto-cancel in-flight dev runs when the CLI exits, using a detached
watchdog process that survives pnpm SIGKILL
([#3191](https://github.com/triggerdotdev/trigger.dev/pull/3191))
## Server changes
These changes affect the self-hosted Docker image and Trigger.dev Cloud:
- A new Errors page for viewing and tracking errors that cause runs to
fail
- Errors are grouped using error fingerprinting
- View top errors for a time period, filter by task, or search the text
- View occurrences over time
- View all the runs for an error and bulk replay them
([#3172](https://github.com/triggerdotdev/trigger.dev/pull/3172))
- Add sidebar tabs (Options, AI, Schema) to the Test page for schemaTask
payload generation and schema viewing.
([#3188](https://github.com/triggerdotdev/trigger.dev/pull/3188))
<details>
<summary>Raw changeset output</summary>
# Releases
## @trigger.dev/build@4.4.3
### Patch Changes
- Add syncSupabaseEnvVars to pull database connection strings and save
them as trigger.dev environment variables
([#3152](https://github.com/triggerdotdev/trigger.dev/pull/3152))
- Updated dependencies:
- `@trigger.dev/core@4.4.3`
## trigger.dev@4.4.3
### Patch Changes
- Auto-cancel in-flight dev runs when the CLI exits, using a detached
watchdog process that survives pnpm SIGKILL
([#3191](https://github.com/triggerdotdev/trigger.dev/pull/3191))
- Updated dependencies:
- `@trigger.dev/core@4.4.3`
- `@trigger.dev/build@4.4.3`
- `@trigger.dev/schema-to-json@4.4.3`
## @trigger.dev/core@4.4.3
### Patch Changes
- Auto-cancel in-flight dev runs when the CLI exits, using a detached
watchdog process that survives pnpm SIGKILL
([#3191](https://github.com/triggerdotdev/trigger.dev/pull/3191))
## @trigger.dev/python@4.4.3
### Patch Changes
- Updated dependencies:
- `@trigger.dev/core@4.4.3`
- `@trigger.dev/build@4.4.3`
- `@trigger.dev/sdk@4.4.3`
## @trigger.dev/react-hooks@4.4.3
### Patch Changes
- Updated dependencies:
- `@trigger.dev/core@4.4.3`
## @trigger.dev/redis-worker@4.4.3
### Patch Changes
- Updated dependencies:
- `@trigger.dev/core@4.4.3`
## @trigger.dev/rsc@4.4.3
### Patch Changes
- Updated dependencies:
- `@trigger.dev/core@4.4.3`
## @trigger.dev/schema-to-json@4.4.3
### Patch Changes
- Updated dependencies:
- `@trigger.dev/core@4.4.3`
## @trigger.dev/sdk@4.4.3
### Patch Changes
- Updated dependencies:
- `@trigger.dev/core@4.4.3`
</details>
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
When the dev CLI exits (e.g. ctrl+c via pnpm), runs that were
mid-execution
previously stayed stuck in EXECUTING status for up to 5 minutes until
the
heartbeat timeout fired. Now they are cancelled within seconds.
The dev CLI spawns a lightweight detached watchdog process at startup.
The
watchdog monitors the CLI process ID and, when it detects the CLI has
exited,
calls a new POST /engine/v1/dev/disconnect endpoint to cancel all
in-flight
runs immediately (skipping PENDING_CANCEL since the worker is known to
be dead).
Watchdog design:
- Fully detached (detached: true, stdio: ignore, unref()) so it survives
even when pnpm sends SIGKILL to the process tree
- Active run IDs maintained via atomic file write
(.trigger/active-runs.json)
- Single-instance guarantee via PID file (.trigger/watchdog.pid)
- Safety timeout: exits after 24 hours to prevent zombie processes
- On clean shutdown, the watchdog is killed (no disconnect needed)
Disconnect endpoint:
- Rate-limited: 5 calls/min per environment
- Capped at 500 runs per call
- Small counts (<= 25): cancelled inline with pMap concurrency 10
- Large counts: delegated to the bulk action system
- Uses finalizeRun: true to skip PENDING_CANCEL and go straight to
FINISHED
Run engine change:
- cancelRun() now respects finalizeRun when the run is in EXECUTING
status,
skipping the PENDING_CANCEL waiting state and going directly to FINISHED
### Fixes and improvements to the onboarding questions:
**This change is worth double checking @matt-aitken**
- Update to the Button.tsx file: it now takes `isLoading` that shows a
spinner in the middle of the button (replacing the button text and any
icons) and sets it to `disabled`. It does this nicely by keeping the
button width the same so there's no layout shift.
**Other fixes**
- Fixes an issue where if you type a custom option in the "What
technologies do you use" question, it doesn't check the list to see if
it matches. Now it checks the box if you've typed an option from that
list.
- When we randomize the list of onboarding question options, we now
store the position they appeared in the list
<img width="2191" height="1023" alt="CleanShot 2026-03-06 at 13 36 53"
src="https://github.com/user-attachments/assets/4eba0d1a-1528-49a3-be5b-6bde89030193"
/>
<img width="411" height="1069" alt="CleanShot 2026-03-06 at 13 37 28"
src="https://github.com/user-attachments/assets/e5f7bb9c-c894-41cc-9ca6-96b43fcf6005"
/>
Add a tabbed sidebar to the Test page for standard tasks, reusing the
ClientTabs pattern from the Query page.
- Options tab: existing sidebar content (machine, version, queue, etc.)
- AI tab: AI-powered payload generation with streaming, supports JSON
Schema, inferred schema from recent runs, and task source code lookup
via tool calling for tasks without schemas
- Schema tab: displays payload JSON Schema (from schemaTask), inferred
schema (from recent runs via @jsonhero/schema-infer), or empty state
with schemaTask docs and example code
Data layer changes:
- Surface payloadSchema and inferredPayloadSchema from TestTaskPresenter
- Add payloadSchema and fileId to WorkerDeploymentWithWorkerTasks type
- Decompress zlib-deflated source files for AI context
A top-level Errors page that aggregates errors from failed runs with
occurrences metrics.
https://github.com/user-attachments/assets/8f0ef55e-90dd-4faa-9051-59f4665181e4
Errors are “fingerprinted” so similar errors are grouped together (e.g.
has an ID in the error message).
You can view an individual error to view a timeline of when it fired,
the runs, and bulk replay them.
# trigger.dev v4.4.2
## Summary
2 new features, 2 improvements, 8 bug fixes.
## Improvements
- Add input streams for bidirectional communication with running tasks.
Define typed input streams with `streams.input<T>({ id })`, then consume
inside tasks via `.wait()` (suspends the process), `.once()` (waits for
next message), or `.on()` (subscribes to a continuous stream). Send data
from backends with `.send(runId, data)` or from frontends with the new
`useInputStreamSend` React hook.
([#3146](https://github.com/triggerdotdev/trigger.dev/pull/3146))
- Add PAYLOAD_TOO_LARGE error to handle graceful recovery of sending
batch trigger items with payloads that exceed the maximum payload size
([#3137](https://github.com/triggerdotdev/trigger.dev/pull/3137))
## Bug fixes
- Fix slow batch queue processing by removing spurious cooloff on
concurrency blocks and fixing a race condition where retry attempt
counts were not atomically updated during message re-queue.
([#3079](https://github.com/triggerdotdev/trigger.dev/pull/3079))
- fix(sdk): batch triggerAndWait variants now return correct
run.taskIdentifier instead of unknown
([#3080](https://github.com/triggerdotdev/trigger.dev/pull/3080))
## Server changes
These changes affect the self-hosted Docker image and Trigger.dev Cloud:
- Two-level tenant dispatch architecture for batch queue processing.
Replaces the
single master queue with a two-level index: a dispatch index (tenant →
shard)
and per-tenant queue indexes (tenant → queues). This enables O(1) tenant
selection and fair scheduling across tenants regardless of queue count.
Improves batch queue processing performance.
([#3133](https://github.com/triggerdotdev/trigger.dev/pull/3133))
- Add input streams with API routes for sending data to running tasks,
SSE reading, and waitpoint creation. Includes Redis cache for fast
`.send()` to `.wait()` bridging, dashboard span support for input stream
operations, and s2-lite support with configurable S2 endpoint, access
token skipping, and S2-Basin headers for self-hosted deployments. Adds
s2-lite to Docker Compose for local development.
([#3146](https://github.com/triggerdotdev/trigger.dev/pull/3146))
- Speed up batch queue processing by disabling cooloff and increasing
the batch queue processing concurrency limits on the cloud:
- Pro plan: increase to 50 from 10.
- Hobby plan: increase to 10 from 5.
- Free plan: increase to 5 from 1.
([#3079](https://github.com/triggerdotdev/trigger.dev/pull/3079))
- Move batch queue global rate limiter from FairQueue claim phase to
BatchQueue worker queue consumer for accurate per-item rate limiting.
Add worker queue depth cap to prevent unbounded growth that could cause
visibility timeouts.
([#3166](https://github.com/triggerdotdev/trigger.dev/pull/3166))
- Fix a race condition in the waitpoint system where a run could be
blocked by a completed waitpoint but never be resumed because of a
PostgreSQL MVCC issue. This was most likely to occur when creating a
waitpoint via `wait.forToken()` at the same moment as completing the
token with `wait.completeToken()`. Other types of waitpoints (timed,
child runs) were not affected.
([#3075](https://github.com/triggerdotdev/trigger.dev/pull/3075))
- Fix metrics dashboard chart series colors going out of sync and
widgets not reloading stale data when scrolled back into view
([#3126](https://github.com/triggerdotdev/trigger.dev/pull/3126))
- Gracefully handle oversized batch items instead of aborting the
stream.
When an NDJSON batch item exceeds the maximum size, the parser now emits
an error marker instead of throwing, allowing the batch to seal
normally. The oversized item becomes a pre-failed run with
`PAYLOAD_TOO_LARGE` error code, while other items in the batch process
successfully. This prevents `batchTriggerAndWait` from seeing connection
errors and retrying with exponential backoff.
Also fixes the NDJSON parser not consuming the remainder of an oversized
line split across multiple chunks, which caused "Invalid JSON" errors on
subsequent lines.
([#3137](https://github.com/triggerdotdev/trigger.dev/pull/3137))
- Require the user is an admin during an impersonation session.
Previously only the impersonation cookie was checked; now the real
user's admin flag is verified on every request. If admin has been
revoked, the session falls back to the real user's ID.
([#3078](https://github.com/triggerdotdev/trigger.dev/pull/3078))
<details>
<summary>Raw changeset output</summary>
# Releases
## @trigger.dev/build@4.4.2
### Patch Changes
- Updated dependencies:
- `@trigger.dev/core@4.4.2`
## trigger.dev@4.4.2
### Patch Changes
- Updated dependencies:
- `@trigger.dev/build@4.4.2`
- `@trigger.dev/core@4.4.2`
- `@trigger.dev/schema-to-json@4.4.2`
## @trigger.dev/python@4.4.2
### Patch Changes
- Updated dependencies:
- `@trigger.dev/sdk@4.4.2`
- `@trigger.dev/build@4.4.2`
- `@trigger.dev/core@4.4.2`
## @trigger.dev/react-hooks@4.4.2
### Patch Changes
- Add input streams for bidirectional communication with running tasks.
Define typed input streams with `streams.input<T>({ id })`, then consume
inside tasks via `.wait()` (suspends the process), `.once()` (waits for
next message), or `.on()` (subscribes to a continuous stream). Send data
from backends with `.send(runId, data)` or from frontends with the new
`useInputStreamSend` React hook.
([#3146](https://github.com/triggerdotdev/trigger.dev/pull/3146))
Upgrade S2 SDK from 0.17 to 0.22 with support for custom endpoints
(s2-lite) via the new `endpoints` configuration, `AppendRecord.string()`
API, and `maxInflightBytes` session option.
- Updated dependencies:
- `@trigger.dev/core@4.4.2`
## @trigger.dev/redis-worker@4.4.2
### Patch Changes
- Fix slow batch queue processing by removing spurious cooloff on
concurrency blocks and fixing a race condition where retry attempt
counts were not atomically updated during message re-queue.
([#3079](https://github.com/triggerdotdev/trigger.dev/pull/3079))
- Updated dependencies:
- `@trigger.dev/core@4.4.2`
## @trigger.dev/rsc@4.4.2
### Patch Changes
- Updated dependencies:
- `@trigger.dev/core@4.4.2`
## @trigger.dev/schema-to-json@4.4.2
### Patch Changes
- Updated dependencies:
- `@trigger.dev/core@4.4.2`
## @trigger.dev/sdk@4.4.2
### Patch Changes
- Add input streams for bidirectional communication with running tasks.
Define typed input streams with `streams.input<T>({ id })`, then consume
inside tasks via `.wait()` (suspends the process), `.once()` (waits for
next message), or `.on()` (subscribes to a continuous stream). Send data
from backends with `.send(runId, data)` or from frontends with the new
`useInputStreamSend` React hook.
([#3146](https://github.com/triggerdotdev/trigger.dev/pull/3146))
Upgrade S2 SDK from 0.17 to 0.22 with support for custom endpoints
(s2-lite) via the new `endpoints` configuration, `AppendRecord.string()`
API, and `maxInflightBytes` session option.
- fix(sdk): batch triggerAndWait variants now return correct
run.taskIdentifier instead of unknown
([#3080](https://github.com/triggerdotdev/trigger.dev/pull/3080))
- Add PAYLOAD_TOO_LARGE error to handle graceful recovery of sending
batch trigger items with payloads that exceed the maximum payload size
([#3137](https://github.com/triggerdotdev/trigger.dev/pull/3137))
- Updated dependencies:
- `@trigger.dev/core@4.4.2`
## @trigger.dev/core@4.4.2
</details>
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
The global rate limiter was being applied at the FairQueue claim phase,
consuming 1 token per queue-claim-attempt rather than per item
processed.
With many small queues (each batch is its own queue), consumers burned
through tokens on empty or single-item queues, causing aggressive
throttling well below the intended items/sec limit.
Changes:
- Move rate limiter from FairQueue claim phase to BatchQueue worker
queue
consumer loop (before blockingPop), so each token = 1 item processed
- Replace the FairQueue rate limiter with a worker queue depth cap to
prevent unbounded growth that could cause visibility timeouts
- Add BATCH_QUEUE_WORKER_QUEUE_MAX_DEPTH env var (optional, disabled by
default)
Input streams enable sending typed data to executing tasks from external
callers — backends, frontends, or other tasks. This unlocks interactive
use cases like approval UIs, cancel buttons, chat interfaces, and
human-in-the-loop AI workflows where the task needs to receive data
while running.
Three consumption patterns inside a task:
* `.wait()` — Suspend the task until data arrives (process freed, most
efficient)
* `.once()` — Wait for the next message (process stays alive)
* `.on()` — Subscribe to a continuous stream of messages
One send pattern from outside:
* `.send(runId, data)` — Send typed data to a specific run's input
stream
## User-facing API
### Define a typed input stream
```ts
import { streams, task } from "@trigger.dev/sdk";
const approval = streams.input<{ approved: boolean; reviewer: string }>({ id: "approval" });
```
### Consume inside a task
```ts
export const myTask = task({
id: "my-task",
run: async () => {
// Pattern 1: Suspend until data arrives (most efficient — frees the process)
const result = await approval.wait({ timeout: "5m" });
// Pattern 2: Wait for next message (process stays alive)
const data = await approval.once().unwrap();
// Pattern 3: Subscribe to multiple messages
approval.on((data) => { /* handle each message */ });
},
});
```
### Send from outside
```ts
// From a backend (using secret API key)
await approval.send(runId, { approved: true, reviewer: "alice" });
// From a frontend (using public JWT token from trigger response)
const { send } = useInputStreamSend("approval", runId, { accessToken });
send({ approved: true, reviewer: "alice" });
```
---------
Co-authored-by: Claude <noreply@anthropic.com>
- New User onboarding questions added and stored in a new
`onboardingData` col
- Keeps the same Org creation screen and stores the data in the same
format in same DB column
- New Org onboarding questions addded and stored in a new
`onboardingData` col
https://github.com/user-attachments/assets/244e4bae-f74d-4ed4-a545-92c9b927e98b
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Pins vouch actions to `c6d80ead49839655b61b422700b7a3bc9d0804a9`
(v1.4.2) in favor of security practices. We were previously using the
`@main` tag.
Also removes the checkout steps as they're not needed in these
workflows.
There's a bug in react-window-splitter on Firefox. When trying to expand
the inspector panel in the query editor, it checks if the main panel has
space but gets an object instead of a number for the auto-sized
query-main panel. This causes the expand calculation to fail and it
snaps it back to collapsed.
I've removed this behavior for now as it's not an important feature.
Eric Allam