Commit Graph

226 Commits

Author SHA1 Message Date
Chris Arderne cca1ea6159 feat(cli,webapp): allow deploys with environment API keys
📦 Preview packages (pkg.pr.new) / Build and publish previews (push) Has been cancelled
2026-08-10 16:33:02 +01:00
Chris Arderne 0a44b88b39 fix: security release 2026-07-21 (#4528) 2026-08-07 12:25:40 +01:00
Eric Allam 6c6e58e6ff perf(webapp): batch declarative schedule cleanup queries (#4522)
## Summary

`syncDeclarativeSchedules` runs on every background-worker creation
(every deploy, and every file save during `trigger dev`). It issued one
instance-delete per declarative schedule the current worker no longer
declares, in a loop, and the overwhelming majority of those deletes
matched zero rows. This collapses the loop into at most two set-based
statements and skips the instance delete entirely when the current
environment owns no instance of the schedule.

## Why so many, and mostly no-op

The loop runs once per entry in `missingSchedules`, which starts as
every DECLARATIVE schedule for the whole project across all its
environments (the query filters only by `projectId`). A schedule leaves
that set only when a declared task matches it by `taskIdentifier`
**and** the schedule already has an instance in the current environment.

That last clause is the amplifier. When a task's schedule has no
instance in the current environment, the create branch inserts a
brand-new `TaskSchedule` row with an instance for this environment
rather than adding an instance to the existing row. So the same
scheduled task, once it has run in dev and been deployed to prod, exists
as two separate schedule rows: one carrying a dev instance, one carrying
a prod instance.

On a dev worker sync of that project:

- the dev-instance row matches the declared task and is removed from the
set
- the prod-instance row has the same `taskIdentifier` but no dev
instance, so it stays in the set and gets `deleteMany(taskScheduleId =
prodRow, environmentId = dev)`, which matches zero rows

So every declarative task that has been synced in another environment
contributes one guaranteed no-op delete per sync, and the count scales
with (declarative tasks x environments), plus any leftover rows from
renamed or removed tasks. A project does not need to have dropped a
schedule to generate these; it just needs the same declarative tasks
present in more than one environment, which is the normal
develop-in-dev, deploy-to-prod case.

## Fix

The candidate schedules are already loaded with their instances, so the
branch is decided in memory:

- schedules with no instances (or only current-environment instances)
are removed in a single `taskSchedule.deleteMany`
- schedules that still have another environment's instance have only the
current environment's instance detached, in a single
`taskScheduleInstance.deleteMany`, and only when such an instance
actually exists

Behavior is unchanged (cascade delete still removes the instances of a
deleted schedule); the difference is statement count. A zero-row delete
writes no WAL and creates no dead tuples, so the removed work was pure
query and commit overhead.

Verified with a testcontainer test (red before, green after) counting
the emitted deletes across the no-op, batched-detach, and
schedule-delete cases, and end to end through `trigger dev`: three
declarative schedules created, surviving a re-sync, then two removed in
a single batched delete with the third preserved.
2026-08-07 10:27:39 +01:00
Matt Aitken 04f9c4e1a5 fix(webapp,run-engine,core): drop the hidden debounce ceiling, fail fast on an unusable maxDelay (#4521)
Debouncing with a `delay` longer than an hour did nothing at all.

The engine applied a server-side ceiling on how long a debounced run
could be pushed back, measured from the run's `createdAt` and defaulting
to one hour. A run is only pushed back while its new execution time
stays inside that ceiling, so a `delay` at or above it could never push
anything: the waiting run was released, the trigger started its own run,
and the next trigger repeated it. A `delay: "12h"` produced one run per
trigger, each correctly delayed by 12h, with no error raised and nothing
on the run to show the debounce key had been ignored.

The ceiling is now unset by default. A debounce key with no `maxDelay`
keeps collapsing triggers for as long as they keep arriving, which is
what the docs have always described. Self-hosters who want a bound can
still set `RUN_ENGINE_MAXIMUM_DEBOUNCE_DURATION_MS`.

That has a consequence worth stating plainly, so the docs now carry a
warning for it: with no `maxDelay`, a continuously triggered key never
executes. Set `maxDelay` when the work has to happen eventually.

**Failing fast on an unusable `maxDelay`.** A caller who sets `maxDelay`
no longer than their `delay` hits exactly the dead end described above,
so that pair is now rejected at trigger time instead of silently
behaving as if no debounce were set:

```
debounce.maxDelay (1h) must be longer than debounce.delay (12h). A debounced run is only
pushed back while it stays inside maxDelay, so with these values every trigger would create
its own run.
```

An unparseable `maxDelay` is rejected too, rather than quietly falling
back to no bound at all, and so is a `delay` given as a date rather than
a duration, which could never work because the value is re-applied on
every push.

The same check runs against a configured server ceiling, so a
self-hosted deployment that sets
`RUN_ENGINE_MAXIMUM_DEBOUNCE_DURATION_MS` gets the error rather than the
silent failure this PR is about. With no `maxDelay` and no configured
ceiling, which is the default, there is nothing to conflict with and
nothing is rejected.

The docs, the `TriggerOptions` JSDoc and the engine option all now state
that the room available to push is the gap between `delay` and
`maxDelay`. The run engine suite gains the case that motivated this:
four triggers on one key with a 12h delay now collapse to a single run.
2026-08-07 07:55:35 +00:00
Chris Arderne 088f68b373 feat(webapp): share rate limit bucket across additional API keys per environment (#4508)
## What

Rate-limit the API by **environment** rather than per API key.

Previously the limiter keyed its bucket on the hash of the full
`Authorization` header — one bucket per key. With additional environment
API keys (`tr_*_sk_*`), an environment can mint many keys and each got
its own full bucket, so more keys = higher effective rate limit. This
collapses all of an environment's keys onto a single shared
per-environment bucket, so the ceiling is exactly the configured limit
regardless of key mix.

## How

- `authorizationRateLimitMiddleware` now lets the override return `{
config?, identifier? }`. `identifier`, when present, is the rate limit
bucket key; otherwise it falls back to the hashed `Authorization` header
(unchanged legacy behavior, still used by `engineRateLimiter` and any
unauthenticated fallthrough).
- `apiRateLimiter`'s override resolves the environment id and uses it as
the identifier:
- **Additional keys** (`isAdditionalApiKey`) resolve via a new
`resolveAdditionalApiKeyRateLimitScope()` — a **scope-agnostic** keyHash
→ (environmentId, org limiter config) lookup. It is deliberately
permissive (restricted keys resolve too) because it's used **only for
bucketing, never as an auth decision** — request auth still goes through
the RBAC bearer controller, which enforces scopes. Revoked/expired keys
are excluded so they can't hold a bucket warm.
- **Root/legacy keys** reuse the environment already resolved by
`authenticateAuthorizationHeader` and key on `environment.id` too.
- The identifier is always the stable environment id, never the secret
key (which can rotate and would split the bucket).
- The whole override result is cached per key by the existing SWR cache,
so **no extra per-request lookup and no separate Redis mapping** is
added.

## Behavior notes

- Root + additional keys of the same environment now share one bucket
(ceiling = configured limit, not a multiple of it). Restricted
additional keys are included — they were the biggest gap, since they
authenticate via the RBAC controller and previously fell back to per-key
buckets.
- **Public JWTs** keep their existing fixed-window, per-token bucketing.
- One-time bucket reset on deploy (bucket keys change); harmless.

## Tests

- New: two tokens resolving to the same identifier share one bucket.
- New: with no identifier, bucketing stays per-key (legacy behavior
preserved).
- Updated existing override tests to the new `{ config }` return shape.

Base: `feat/multi-keys-surface`. Closes TRI-12888.
2026-08-06 16:05:27 +01:00
Chris Arderne 9409ddf9bc feat(webapp): add multiple environment API key management (#4390)
## Summary

Projects can create, inspect, expire, and revoke multiple API keys for
each environment. Plaintext values are shown only at creation; stored
credentials are hashed and the API keys page displays only an obfuscated
suffix afterward.

Self-hosted installations support full-access additional keys by
default. Authorization extensions can provide additional access presets
and optional task selection. Additional keys can also mint scoped public
access tokens through the Trigger.dev API without receiving the
environment signing key.

## Feature notes
- Only admin+ can create API keys (Developer can make in Development
branch).
- JWT self-signing will be a server call when used with new `_ak_` keys.
- JWTs with long expiry can keep working even with api key deleted (gets
priveleges from api key, signed with root key)
- Unfiltered session listings intentionally preserve the existing broad
task-read behavior. Filtered listings enforce task-level scopes for
every requested task.
- Buffered runs without a task identifier are not safely authorizable,
so cancel/replay requests fail closed rather than resolving an unscoped
run.
- Batch and waitpoint endpoints intentionally return server-minted,
narrowly scoped public tokens to all callers. These tokens have bounded
lifetimes and may remain valid until expiry after API-key revocation.

## Deployment notes

Deploy the management UI and public-token endpoint with new key creation
disabled. Enable creation for selected organizations after the
authentication path and released SDK have been verified, then expand
availability gradually.

Revoking an API key prevents new bearer requests and new token minting.
Public tokens already minted by that key remain valid until their own
expiration because they are signed by the environment signing key.

## TODO
- [x] Add "Created by" to the key table
- [x] Document that streamed batch ingestion is non-atomic and may
 partially accept items before a validation or authorization error.

## Follow-ups

- [x] Add an organization-level feature flag for the API key management
UI and creation action.
- [x] Document rollout ordering: enable additional-key lookup before
enabling issuance.
- [x] Add a system-wide gate that can stop new key issuance without
disabling authentication for existing keys.
- [x] Replace the generic SDK compatibility warning with the first
published compatible version. Old SDK will mint an unusable token if
given an `_ak_` key.
- [x] Add public documentation covering creation, storage, expiration,
revocation, SDK compatibility, and public-token lifetime behavior.
- [x] Add observability for key creation, revocation, policy preparation
failures, and public-token mint failures.
- [ ] Exercise create, copy-once display, authenticate, mint, expire,
and revoke flows end to end before broad enablement.
2026-08-06 15:27:10 +01:00
Katia Bulatova fbd6df33b4 feat(webapp): Themes + contrast settings update (#4206)
Adds System Preferences, Dark and Light themes, gated by the
`hasThemeSwitcher` feature flag (off by default — dark stays the default
theme for everyone).

Old theme is now "Classic"and set as default. 
"System preferences" theme has both Light and Dark modes and uses your
laptop settings to use a correct one.
It has less color accents (specifically less colored text), and they are
the same for both modes, only grayscale values change between them. And
Light/Dark themes can be used separately.

New Contrast setting is available for System Preferences, Dark and Light
themes - it changes the contrast for the whole app. All new visual
Settings live in Account.
2026-08-03 19:29:33 +02:00
Chris Arderne 763b5dc582 feat(webapp): enforce scopes for environment API keys (#4389)
## Summary

Environment API keys backed by the additional-key table can authenticate
API requests using their stored effective scopes. Revoked and expired
keys are rejected, branch environments retain their existing routing
behavior, and last-used timestamps are updated on a throttled
best-effort basis.

## Design

API route builders receive the resolved ability and reject restricted
keys on routes without an authorization declaration. Existing
deployment, environment variable, queue, run, task, batch, session, and
waitpoint routes declare the resources they access.

Trigger and batch responses return server-signed public access tokens,
so additional keys never need access to the environment signing secret.
Root-key rotation also keeps public tokens valid for the existing grace
window.

## Feature notes
- Root environment keys remain unrestricted for backward compatibility.
Additional keys enforce their persisted scopes and fail closed on routes
   without an authorization declaration.
- Machine-key requests never exchange one credential for another.
Additional keys cannot retrieve the root key, and rotated root keys are
not upgraded
   during their grace window.
- Public JWT validation remains host-owned, while installed RBAC plugins
continue to supply root-key abilities.
- Unfiltered session and run listings preserve existing broad task-read
behavior. Filtered requests enforce the supplied task identifiers.
- Related-run summaries remain embedded in run retrieval for API
compatibility. Retrieving or mutating a related run independently still
requires
   permission for that run.
- Queue management authorizes at collection scope, matching the queue
permissions currently issued.
- Batch responses deliberately include server-signed public access
tokens for all clients. Selected-task credentials continue using their
original
   credential for per-item authorization.
- Two-phase batches authorize declared task identifiers before creation
and authorize every streamed item. Streaming paths that cannot declare
the
   complete task set remain fail closed.
- Authentication telemetry records successful credential resolution
separately from subsequent resource-authorization failures.
- API keys are high-entropy random tokens. SHA-256 is intentionally used
for deterministic indexed lookup, not password hashing.

## Deployment notes

The schema migration must be present before this code is deployed.
Because bearer resolution runs on every authenticated request, deploy
the resolver with additional-key lookup disabled, verify root-key and
public-token parity, then enable lookup before any additional keys can
be issued.

The multi-task authorization tightening changes the result for narrowly
scoped tokens that request tasks outside their grants. Observe
would-deny results before enforcing that check. Request-idempotency keys
are also newly isolated by environment and task, so a retry crossing the
deployment boundary may execute once more before old cache entries
expire.

## Follow-ups

- [x] Add a system-wide kill switch for additional-key lookup, defaulted
off for the initial deployment.
- [x] Add authentication observability by credential kind, result,
latency, and lookup path without recording credential values.
- [ ] ~Add would-deny observability and an independent enforcement
switch for multi-task authorization.~
- [ ] ~Add an independent switch for server-issued batch tokens while
root-key parity is verified.~
- [ ] Confirm every API route reachable by a restricted key has an
explicit authorization declaration or intentionally fails closed.
- [x] Verify root-key rotation, revoked-key grace, and public-token
validation through each bearer resolver path.
2026-08-03 14:00:29 +01:00
Eric Allam db6228dd1e chore(webapp,core,sdk): upgrade @s2-dev/streamstore to 0.25 and migrate S2 hosts (#4349) 2026-08-01 11:33:34 +01:00
Eric Allam f9c8d518c7 perf(webapp,run-engine,database): resolve the newest worker and deployment by createdAt (#4452) 2026-08-01 11:32:21 +01:00
Eric Allam 0445b8ec27 fix(webapp,clickhouse): keep the rest of a ClickHouse batch when one run or span has un-ingestable JSON (#4358)
## Summary

A single run output, trace span, or payload carrying JSON that
ClickHouse can't ingest (for example nesting past its depth limit) used
to fail the whole insert batch, so unrelated runs and spans silently
disappeared from the runs list, traces, and logs. This keeps the rest of
the batch and handles the offending row instead of dropping everything
around it.

## Fix

Recovery is per-table, matched to what each table needs:

- **Runs** (`task_runs_v2`) keep their status. We follow ClickHouse's
failing-row hint to strip just the un-ingestable JSON column(s) so the
run still lands (its output reads from Postgres on the detail page), up
to a configurable limit (`RUN_REPLICATION_MAX_POISON_STRIPS_PER_BATCH`,
default `1`). Past the limit we stop and land the batch with
`allow_errors` in a single pass, skipping the remainder. Cost stays a
fixed handful of inserts no matter how large or poisoned a flush is.
- **Trace events and payloads** (high volume, append-only) recover with
a single `allow_errors` insert: the good rows land in one pass and only
the un-ingestable rows are skipped.

Before falling back, a lightweight sanitizer still repairs what it can
losslessly (lone UTF-16 surrogates, out-of-range integers) so a
repairable row lands in full.

To read the failing-row hint we patch `@clickhouse/client-common`: its
error parser truncates the server response and discards the `(at row N)`
position, so the patch preserves the full text for the recovery path to
read.
2026-08-01 09:17:20 +01:00
Eric Allam c72ebf9084 fix(webapp,run-engine): stop batchTriggerAndWait hanging when item streaming never completes (#4397)
## Summary

`batchTriggerAndWait()` could leave a parent run waiting forever. The
2-phase batch API blocks the parent on the batch's waitpoint as soon as
the batch is created, but the batch is only sealed at the end of item
streaming. If streaming never completed, nothing sealed the batch,
nothing completed the waitpoint, and the parent stayed suspended with no
timeout and no way to recover.

Supersedes #4016, which added the reaper alone.

## Fix

Admission for item streaming was being decided twice. Batch creation
passes its own rate limiter, which fixes `expectedCount` and blocks the
parent, and then the item stream had to pass the general API limiter as
well, competing with unrelated traffic. A second limiter could therefore
veto work the first had already committed the parent to. Creation now
mints a bounded grant that the item stream spends, so an admitted batch
can finish streaming. The grant is capped per batch rather than
exempting the path, and every failure mode (no grant, spent grant,
unreachable store) falls back to the normal limiter.

That makes stranding much rarer but not impossible, since a request
timeout or a crash can still end streaming for good. So a seal-timeout
reaper aborts any batch still unsealed after `BATCH_SEAL_TIMEOUT_MS` and
completes the parent's waitpoint with an error, letting
`batchTriggerAndWait()` reject instead of hang. It is race-safe against
a late seal, and it is only scheduled for batches that actually block a
parent, so fire-and-forget batches cost nothing.

Finally, the batches page used to report "Batch completion checked." for
these batches while doing nothing, because the completion path returns
early on an unsealed batch. It now says the batch cannot be resumed.

Rate limiting is no longer the reason a batch strands, so the reaper's
default stays at 30 minutes, comfortably above the SDK's worst-case
stream-retry budget.

## Verification

Unit and container tests cover the grant cap, the bypass ordering (it
runs after the authorization check, so it can never skip
authentication), and the reaper's abort, seal race, idempotency, and
no-waitpoint cases.

Also verified end-to-end against a running stack. With the general limit
exhausted, batch creation and other API calls returned 429 while a
granted batch still streamed and sealed; an ungranted batch id was rate
limited rather than bypassed; and the grant cut off exactly at its
configured attempt count. Reproducing the stranded state on a real
parent run, the batch was aborted at the timeout, the waitpoint
completed with an error, and the parent resumed and finished instead of
hanging. A parentless batch left unsealed was untouched well past the
reaper window.

## Verified against deployed runs

The reaper was proven end to end with a real deployed run (locally-run
supervisor, containerised
run) and a real network fault, rather than a simulated one: toxiproxy
severs the phase 2 item
stream mid-flight so every SDK stream retry genuinely fails, while phase
1 still succeeds. Only
the batch calls traverse the fault, so control-plane traffic is
untouched.

The reproduction is the shape that actually strands a parent: the task
catches the
`BatchTriggerError` the SDK throws and carries on, so the phase 1 block
outlives the thrown error
and the parent hangs at its next suspension point.

With the reaper disabled, the parent sat in `EXECUTING_WITH_WAITPOINTS`
for over 24 minutes holding
two blockers, and stayed stuck across a full infrastructure restart:

```
 type     | status    | has_timeout
 BATCH    | PENDING   | f            <- orphan, completedAfter NULL
 DATETIME | COMPLETED | t            <- the wait already elapsed
```

With the reaper enabled the same task under the same fault completed in
about 75 seconds with zero
blockers left, the batch `ABORTED`, and its waitpoint completed carrying
the error.

Two conditions are required to observe this at all, which is worth
knowing for any future test:
the run must be deployed rather than `trigger dev` (dev runs execute in
process and finish while
still holding blocker rows), and the wait after the caught error must
exceed the checkpoint
threshold, or it is served in process and never suspends.

### Why completing the batch waitpoint is sufficient

`batchTriggerAndWait` runs create, then stream, then wait. A phase 2
failure throws before the wait
is ever reached, and the reaper only fires on an unsealed batch, so the
parent is never suspended
awaiting the batch when it runs. The parent therefore does not need a
synthetic result, only to stop
being blocked. Note this reasoning depends on that ordering: if the wait
were ever reached with an
unsealed batch, completing the batch waitpoint alone would not settle
the caller.

## Follow-ups

- Batches stranded before this ships still need a one-off recovery; the
reaper only schedules at creation time.
- That same property leaves a gap if the process dies between creating
the batch and scheduling the job. A periodic sweep would close it, but
wants a supporting index.
- When a partially streamed batch aborts, children already enqueued keep
running while the parent fails. Left as-is deliberately, since
cancelling triggered work is a bigger semantic call.
2026-07-31 11:55:25 +01:00
Wes Mason efcb89ac26 fix(webapp): add hasAdminDisplayAccess to the env param test mock (#4430)
`test/envParamRoute.ownership.test.ts` fails on main: 3 of its 4 tests
throw

```
Error: [vitest] No "hasAdminDisplayAccess" export is defined on the
"~/services/session.server" mock. Did you forget to return it from "vi.mock"?
```

#4421 added a `hasAdminDisplayAccess(user)` call to the `env.$envParam`
loader, and the test's `vi.mock` of `session.server` only returns
`requireUser`, so the call blows up. Both changes were green in their
own PR and only conflict once merged together, which is why nobody
caught it.

The mock now mirrors the real implementation rather than returning a
constant, so it stays correct if the test's user fixture is ever varied.
No assertions were changed: the tests were right, the mock was stale.

Worth flagging separately: no workflow runs on push to main, so this has
been red since #4421 landed without showing up anywhere. Every PR opened
since has inherited the failure.
2026-07-31 09:44:16 +01:00
claude[bot] debfa2b733 feat(webapp): impersonation consent page and a view-as-user toggle (#4421) 2026-07-30 21:28:44 +01:00
Oskar Otwinowski 4efe0a07c4 fix(webapp): create dev environments for SSO and Directory Sync members (#4426)
Members added by SSO just-in-time provisioning or Directory Sync never
got
their per-member DEVELOPMENT environments - only invite acceptance and
project creation created them. `trigger dev` returned "Environment not
found" for those members and the dashboard had no dev view.

ensureOrgMember now queues provisioning for every membership it settles,
so
both paths are covered and members missing environments are repaired on
their next sync. Provisioning runs as a common-worker job to keep
sign-in
and directory webhooks off the per-project write loop. A failed enqueue
surfaces for Directory Sync, whose worker retries the idempotent effect,
and is swallowed for sign-in, where the next login enqueues again.
Environment creation now tolerates a concurrent creator so the
project-creation loop and the job cannot collide on the unique index.

Also fixes environment resolution ignoring dev-environment ownership: a
member without their own dev environment could be handed a colleague's
and
have it persisted as their dashboard preference.
2026-07-30 21:50:15 +02:00
Eric Allam 6e5f0f0fe7 fix(webapp,clickhouse): stop invalid customer queries alerting, and isolate Sentry scope per request (#4372)
## Summary

A query sent to the query API with a typo in it, like a column name that
does not exist, was being reported as a server error. That put customer
SQL mistakes into our error alerting, where they made up almost all of
the volume on one of our noisiest alerts, and it drowned out the
failures that are actually ours to fix. This makes the level match who
is at fault, and fixes two related problems found alongside it.

## Invalid queries are the caller's, not ours

The query API route already got this right. It checks for `QueryError`,
logs at warn, and returns a 400, with a comment saying the system
handles it gracefully and no alert is needed.

The layer underneath ignored that. `executeTSQL` logged every exception
out of its catch block at error, including the compile failures the
route was about to turn into a 400, and error-level logs are forwarded
to error reporting.

The TSQL package already draws the line we need:

```ts
export class ExposedTSQLError extends BaseTSQLError {
  /** An exception that can be exposed to the user. */
}

export class InternalTSQLError extends BaseTSQLError {
  /** An internal exception in the TSQL engine. */
}
```

`SyntaxError` and `QueryError` extend the first. So the catch block now
branches on `ExposedTSQLError` and logs those at warn, keeping error for
`InternalTSQLError` and anything unanticipated, which is a genuine
compiler bug.

## SQL the caller wrote is their mistake, not ours

The same asymmetry showed up one level down. A query that compiles fine
can still be rejected by ClickHouse at execution, and most of those
rejections mean the caller's SQL is wrong rather than that we generated
something bad.

This is where the volume actually is. Checking production, one error
group alone, a missing `GROUP BY` on the public query API
(`NOT_AN_AGGREGATE`), accounts for over a million events across hundreds
of users. It is by far the largest error group in the project, and
classifying only by resource limit would have left every one of those at
error level.

So rejections are split three ways in `ClickhouseClient`, which is the
only place holding the parsed `ClickHouseError` and its symbolic type.
By the time the error reaches `executeTSQL` it has been wrapped and the
type is gone, and the type never appears in the message text, so it
cannot be recovered by string matching.

- **Resource limits** (memory ceiling, timeout, row/byte caps) log at
warn. The query is valid, it just asked for more than it is allowed to
spend.
- **Invalid SQL** (`NOT_AN_AGGREGATE`, `UNKNOWN_IDENTIFIER`,
`SYNTAX_ERROR`, the type and parse families) logs at warn **only when
the caller wrote the SQL**.
- **Everything else** keeps alerting.

That gate matters. The client is shared, so the identical rejection on
TRQL *we* generated is our bug and has to stay at error. Callers opt in
with `userAuthoredQuery`:

| caller | who wrote the SQL | opts in |
| --- | --- | --- |
| public query API | the customer | yes |
| query editor | the customer | yes |
| agent charts | the agent's model | yes |
| built-in dashboard tiles | us, in code | no |
| queue metric cards | us, in code | no |
| health report | us, in code | no |

The agent is the one judgement call. Its TRQL is not typed by a person,
but it is also not something a code fix makes correct, so a query it
gets wrong is not worth waking anyone for. The same endpoint serves
built-in tiles whose TRQL we do write, so the opt-in lives with the
caller rather than the route.

Separately, when one of these queries did fail, the log recorded the
generated ClickHouse SQL but not the query the caller actually wrote,
which made the reports hard to act on. `queryWithStats` takes an
optional `logFields` that `executeTSQL` uses to attach the original
TSQL.

## Events were attributed to the wrong request

Chasing the above turned up something broader: only a tenth of the
events on that alert pointed at the query API. The rest were pinned to
unrelated requests that happened to be in flight at the same time, so
the alert looked like the trigger endpoint was failing.

`Sentry.init` runs with `skipOpenTelemetrySetup: true`, because we
register our own OTel pipeline. That skips `initOpenTelemetry`, and one
of the things it does is:

```js
api.context.setGlobalContextManager(new SentryContextManager());
```

The async-context strategy is still installed, but `withIsolationScope`
only marks the OTel context and delegates the actual fork to that
context manager:

```js
// "We depend on the otelContextManager to handle the context/hub"
return api.context.with(ctx.setValue(SENTRY_FORK_ISOLATION_SCOPE_CONTEXT_KEY, true), ...)
```

`provider.register()` installed a plain
`AsyncLocalStorageContextManager`, which does not know that key. The
lookup found no scopes on the context and fell back to the
process-global default isolation scope, so every request wrote its
request data into the same object and the last writer won.

The tracer now registers `SentryContextManager`, which subclasses
`AsyncLocalStorageContextManager`, so OTel behaviour is unchanged. It is
also registered on the path where tracing is disabled, which previously
never called `register()` at all and so had no context manager of its
own.

Tenant tags were always correct, because those come from our own async
local storage rather than the isolation scope. That is why the
attribution being wrong was not obvious.

This affects every error report the webapp sends, not just the query
API.

## Verification

`internal-packages/clickhouse`: 76 tests pass, including eight covering
each level decision against a real ClickHouse container. Three pairs pin
the gate open and shut at both layers: an invalid query, a compile
failure, and a real limit breach driven with `max_rows_to_read` each log
at warn with `userAuthoredQuery` and at error without it.

The isolation fix has a test that reproduces the leak before asserting
the fix. Two overlapping requests each tag their own isolation scope;
with the plain context manager the slower one reads back the other's
tag, and with `SentryContextManager` each reads back its own.

Measured separately against a faithful reproduction of the server's
wiring (own OTel pipeline, CommonJS entry) at 200 concurrent requests:
per-request attribution goes from 0.5% to 100%, while span nesting,
context propagation across awaits, and distinct trace IDs are identical
before and after.
2026-07-30 09:04:15 +01:00
Chris Arderne 2f1734c858 fix(core,webapp): redact sensitive fields in logs by default and cap their size (#4401) 2026-07-29 17:59:47 +01:00
Eric Allam 4eb9292cbe feat(webapp,run-engine): queue metrics and health dashboard (#4131)
## Summary

Three related changes, each independently gated:

**Queue metrics and health.** Per-queue depth, throughput (enqueued,
started, completed), concurrency, whether a queue is throttled, and
scheduling delay (how long a run waits between becoming eligible and
actually starting), plus a per concurrency-key breakdown for keyed
queues. Collected from inside the run queue itself, stored in
ClickHouse, and surfaced on the Queues list, a new per-queue detail
page, the task pages, and the run inspector. The question it answers is
"does this queue have enough concurrency to keep up, and if not, which
key or which limit is the constraint".

**Percent-based queue concurrency limits.** A queue's concurrency
override can now be expressed as a percentage of the environment limit,
stored as the source of truth and re-materialized whenever the
environment limit changes. Absolute overrides above the environment
limit are now **rejected with a 400** instead of being silently capped,
which is a behavior change on `POST
/api/v1/queues/:queue/concurrency/override`.

**The `health` report.** A server-computed verdict on whether work is
flowing, whether the runs that do start are healthy, and whether
telemetry is fresh, rendered as text with sparklines. Available as `GET
/api/v1/reports/:key`, `trigger report`, and the `get_report` MCP tool
(plus a `report` MCP prompt, which shows up as a slash command in hosts
that support prompts).

With the flags off, the Queues page renders the pre-metrics component
verbatim, nothing is emitted, and nothing is written to ClickHouse.

## Configuration

Two independent gates, on purpose. Emission is global so data accrues
for everyone before anyone can look at it; the view is per organization
so it can be turned on for one org at a time without a deploy.

**Runtime flags (no restart)**

| Flag | Store | Gates |
| --- | --- | --- |
| `queue_metrics:enabled` | run-queue Redis key (`"1"`/`"0"`, off by
default) | All emission, gauges and counters. Cached in-process for 10s
with stale-while-revalidate, warmed eagerly at boot so the first op
after a deploy is not dropped. |
| `queue_metrics:gauge_sample_rate` | run-queue Redis key, `0..1` |
Fraction of queue ops that emit a gauge. Counters are never sampled, so
throughput stays exact at any rate. |
| `queueMetricsUiEnabled` | feature-flag catalog: global `FeatureFlag`
row, per-org `Organization.featureFlags` override wins | Whether an org
sees the metrics view at all: the Queues list variant, the queue detail
route, the built-in Queues dashboard, the concurrency-keys endpoint, and
the metrics blocks on task pages and the run inspector. Off by default;
a gated org gets a 404 on the detail route rather than an empty page. |

Both Redis keys are readable and writable from `/admin/queue-metrics`
(super-admin UI, with a live per-shard stream-health table) and
`GET`/`POST /admin/api/v1/queue-metrics` (admin PAT). The admin surface
uses its own Redis client, so it works on any instance regardless of
whether that instance runs the emitter or the consumer.

**Environment variables (boot time)**

| Variable | Default | Notes |
| --- | --- | --- |
| `QUEUE_METRICS_EMIT_ENABLED` | `0` | Constructs the emitter and
injects it into the run engine. Without it the run queue has no emitter
at all. |
| `QUEUE_METRICS_CONSUMER_ENABLED` | `0` | Boots the stream consumer on
this instance. Independent of emission, so consumers can be sized
separately from the API. |
| `QUEUE_METRICS_STREAM_SHARD_COUNT` | `4` | Stream shards, hashed per
queue. |
| `QUEUE_METRICS_CONSUMER_BATCH_SIZE` | `1000` | Poll batch equals
insert batch, so an ack can never outrun a write. |
| `QUEUE_METRICS_REDIS_{HOST,PORT,USERNAME,PASSWORD,TLS_DISABLED}` |
falls back to the run-queue Redis | Set `HOST` to move the metrics
stream onto a dedicated instance so a metrics backlog cannot compete
with the run queue for memory. Self-hosters can leave it unset and get a
single-Redis deployment. |
| `QUEUE_METRICS_COUNTER_STREAM_MAXLEN` | `2000000` shared, `8000000`
dedicated | Bound on how much a stalled consumer can hold. The default
is deliberately lower when the stream shares the queue-critical Redis. |
| `QUEUE_METRICS_COUNTER_ODOMETER_TTL_SECONDS` | `604800` | TTL on the
per-queue cumulative counter key, refreshed on every write, so only
queues idle for the whole window are purged. |
| `QUEUE_METRICS_MAX_QUEUE_NAMES_PER_ENV` | `1000` | Distinct queue
names tracked per environment; overflow collapses into `__overflow__`. |
| `QUEUE_METRICS_MAX_CONCURRENCY_KEYS_PER_QUEUE` | `10000` | Same idea
one level down, per queue. |
| `QUEUE_METRICS_GAUGE_SAMPLE_RATE` | `1` | Default for the live
sample-rate key above. |
| `QUEUE_METRICS_QUERY_TABLES_VISIBLE` | `0` | Lists the queue-metrics
tables in the Query page, its schema docs, the schema API and the AI
query context. Off keeps them unlisted while the feature is dark; a
query naming them still runs either way. |
| `QUEUE_METRICS_CLICKHOUSE_URL` | falls back to the shared wiring |
Runs queue metrics on their own ClickHouse service: the consumer's
inserts and every queue-metrics read go through it, so a metrics-heavy
chart refresh never competes with runs-list or trace reads. Unset
reproduces the previous split exactly (inserts on `CLICKHOUSE_URL`,
reads on the query pool). |
| `QUEUE_METRICS_CLICKHOUSE_READER_URL` | the write URL | Reader split,
so the consumer's inserts can never land on a read endpoint. |
|
`QUEUE_METRICS_CLICKHOUSE_{KEEP_ALIVE_ENABLED,KEEP_ALIVE_IDLE_SOCKET_TTL_MS,MAX_OPEN_CONNECTIONS,LOG_LEVEL,COMPRESSION_REQUEST}`
| `1`, unset, `10`, `info`, `1` | Pool tuning, matching the other
per-workload ClickHouse clients. |

Migrations to apply: ClickHouse `036_create_queue_metrics_v1.sql`, and a
Postgres migration adding the nullable
`TaskQueue.concurrencyLimitOverridePercent`. Both are additive.

## How collection works

Queue operations produce two kinds of signal, and they have opposite
failure modes, so they are handled differently.

**Gauges** (queued, running, queue limit, env queued, env running, env
limit, throttled, plus keys-with-backlog and worst-key wait on keyed
queues) are read *inside* the same Redis script that performs the
enqueue or dequeue, so the reading is atomic with the operation it
describes rather than a racy follow-up read. The script returns them on
its reply and the app forwards them to the stream. Gauges are sampled
and drop-tolerant: they are aggregated with `max`, so a lost reading
costs resolution, never correctness.

**Counters** (enqueued, started, completed, plus nack and dead-lettered)
are cumulative odometers. Each event increments a per-queue key on the
metrics Redis and emits the absolute total, and ClickHouse takes the
difference across buckets at read time. This is the important property
of the design: a summed-delta counter undercounts permanently on any
lost event, while a cumulative one self-heals, because the next
surviving reading restates the whole total. Only bucket granularity can
be lost, never the total. A queue returning after its odometer TTL
expired restarts at 1 and reset detection handles it, which is safe
precisely because expiry only spans a window with no activity.

Both land on one sharded Redis stream. A consumer reads it with a
consumer group, reclaims stale pending entries on a 15s interval rather
than on every poll, maps one entry to one or two ClickHouse rows
(whole-queue and, for keyed queues, per-key), and acks only after the
insert lands. Each batch carries a dedup token derived from its
stream-entry ids, and the target tables set
`non_replicated_deduplication_window`, so a retried batch cannot
double-count either the raw rows or the aggregates that hang off them.
Consumer and emitter both emit OTel metrics
(`queue_metrics.emitter.emitted`,
`queue_metrics.consumer.{entries,rows_inserted,insert_errors,insert_duration,stream_depth,group_lag,pending,lag_unknown}`);
stream depth and group lag are the two worth alerting on, and
`lag_unknown` exists because Redis can report a null lag after a trim,
which must not be read as zero.

## Storage and read path

`queue_metrics_raw_v1` is a short landing table with a 6 hour TTL. Four
aggregate tiers are materialized straight from raw, never cascaded off
each other, each with a 30 day TTL:

- `queue_metrics_v1`, 10 second buckets per queue, the default read path
- `queue_metrics_5m_v1`, 5 minute buckets per queue, for wide ranges and
cross-queue ranking
- `env_metrics_v1`, 10 second buckets per environment, queue-independent
so it stays cheap at any range
- `queue_metrics_ck_v1`, 10 second buckets per concurrency key

Every tier is an MV from raw because the counter states do not survive a
cascade: their merge is order sensitive, so a `-MergeState` chain off
the 10s table inflates the result, and the same property means an
aggregate state may only be merged inside one queue. That constraint is
now enforced by the query engine rather than by reviewer discipline: a
column can declare a `mergeGroupKey`, and any query that references it
without grouping by, or pinning to a single value of, every named key
fails to compile with an actionable message.

On the read side, TRQL gains three tables (`queue_metrics`,
`env_metrics`, and a `queue_metrics_by_key` that is hidden from the
editor, schema docs and schema API but still queryable, so per-key rows
can never silently merge into a plain per-queue query), plus
`deltaSumTimestampMerge` and `quantilesTDigestMerge`. Two schema-level
optimizations ride along: a table can declare coarser rollups, so a
query whose bucket interval is 5 minutes or wider is routed to the 5m
table with no change to the query itself, and it can opt into the
ClickHouse query cache with time bounds floored to a fixed grid, so the
auto-refreshing dashboards actually share cache entries instead of
missing on every tick. Both are caller-side substitutions, so the
printer stays unaware of physical layout.

All of this can also live on its own ClickHouse service. A table
declares the pool its reads run on, the three queue-metrics tables name
the dedicated one, and the ingestion consumer writes through the same
client, so both directions move together with one env var and nothing
else routes differently.

The other engine change is opt-in gap filling: charts can request rows
for empty buckets, where counters zero-fill and gauges carry forward.
Grouped gauge series are densified per group and carried inside a
partition, so a quiet queue's line holds its last value without bleeding
another queue's value into it.

## Queue concurrency limits

`concurrencyLimitOverridePercent` on `TaskQueue` is the source of truth
when an override is set as a percentage; the absolute `concurrencyLimit`
is materialized from it (floored, clamped to at least 1 so a percentage
can never act as a pause, and never above the environment limit). Every
path that changes an environment limit now recalculates the
environment's percent-based overrides afterwards, outside the
transaction, and pushes changed limits to the engine. The push is
attempted even when the stored value did not change, so a previously
failed sync self-heals rather than leaving the database and the engine
diverged; paused queues are skipped so a recalculation cannot
effectively unpause one.

The API accepts exactly one of `concurrencyLimit` or `percent`, and the
reject-instead-of-clamp change above means a request asking for more
than the environment allows now fails loudly. The percent bound (greater
than 0, at most 100) is defined once and shared by the zod schema, the
dashboard mutation handler and the service, so the three cannot drift.

The concurrency-keys table on a queue is now paginated against the
ClickHouse per-key tier, ranked by peak backlog with the total on every
row from a single scan, and only the keys on the current page are
enriched with live counts from Redis. That replaces a hard top-50 cap
with something whose cost is a function of page size rather than key
cardinality.

## The health report

`GET /api/v1/reports/:key?period=&format=markdown|ansi|json`. The
verdict is computed on the server and is deterministic, not
model-generated. Three independent analyzers run over one input
snapshot: flow (is work moving, and if not, is the cause a limit,
throttling, one bad queue, or dead-lettering), execution (are the runs
that start succeeding, and at what latency), and liveness (how fresh is
the telemetry). When telemetry is genuinely stale, the first two are
forced to unknown and every actionable field is stripped, so no surface
ever advises action off stale data.

Authorization is per query table rather than a blanket query grant: a
JWT must be scoped to every table the report reads (`runs`,
`env_metrics`, `queue_metrics`), so a narrowly scoped token cannot pull
a report that reads more than it was granted. `period` is validated as a
shorthand with a 90 day ceiling at the edge. The report catalog is a
registry of `{ load, interpret }` entries, so the next report is a new
entry and no change to the route, the view model, the renderers, the CLI
or the MCP tool.

`trigger mcp` no longer launches the install wizard when stdout is a
TTY, which fixed a real failure: hosts spawn the server over a PTY, so
the wizard would open and the client would time out waiting for a server
that never started. The wizard now needs `trigger mcp --install`.

## The part that is live regardless of every flag

The enqueue and dequeue scripts now return a 2-tuple so a gauge reading
can ride back on the reply. Every return site in the eight affected
scripts is wrapped, and a `nil` original is converted to `false` on the
way out, because a raw `nil` in the first slot would make Lua truncate
the multi-bulk reply and silently drop the gauge on the throttled and
empty-queue paths. The reply shape and the destructuring on the app side
are exercised on every queue operation whether or not metrics are
enabled, so that is the part of `run-engine` worth the closest review.

One behavior fix in the same area: the scheduling-delay anchor is set
only on a run's first entry into the queue. Anchoring it to trigger time
on re-enqueues made waitpoint and checkpoint resumes report the entire
wait as scheduling delay. Queue ordering is untouched, so a re-enqueued
run keeps its position, and nacks deliberately keep the original anchor
because a rolled-back dequeue is the same continuous wait.

A pending-version promotion still anchors to trigger time, on purpose:
that promotion is the run's first real entry into the queue, since the
trigger deliberately held it back waiting for a worker version, and the
TTL is armed at the same point for the same reason. The consequence is
worth naming, because it is a judgement call: a run that waits on a
deployment reports that wait as scheduling delay on its queue, which is
time unrelated to queue capacity.

## Verification

Unit and integration suites across the new package, the run queue, the
mapping layer, the query engine and ClickHouse (including a test that
applies migration 036 through the same splitter CI uses, and a
regression test that inserts the same batch three times to prove the
aggregates do not inflate). Beyond that, the whole path was driven end
to end against a live stack with real runs: emitter to Redis stream to
consumer to ClickHouse to the dashboards, for both the local dev path
and the deployed path where a supervisor drives the dequeue, with
assertions on exact counter reconstruction per queue and per concurrency
key, throttling, environment saturation, scheduling delay, and a
deliberate mid-stream reading drop to confirm the cumulative counters
still reconstruct the correct total. The gated-off state was checked on
every touched surface.

The dedicated ClickHouse service was verified against a second,
separately-schema'd instance: with it configured, the driven counters
reconstruct exactly on the dedicated instance, the shared instance gains
no rows for that window, a read through the query API returns the value
that exists only on the dedicated instance, and a `runs` query still
succeeds (it would fail outright if it were mis-routed to a service
without that table). With the variable unset, the full suite passes
unchanged.

---------

Co-authored-by: Katia Bulatova <katia@trigger.dev>
Co-authored-by: Katia Bulatova <katherine.bulatova@gmail.com>
Co-authored-by: James Ritchie <james@trigger.dev>
2026-07-29 16:45:24 +01:00
claude[bot] 639eaf6e82 fix(webapp): don't apply an invite's role to an existing org member (#4409)
<!-- ccr-slack-attribution -->
_Requested via [Slack
thread](https://triggerdotdev.slack.com/archives/C097ZHVKZFA/p1785249693523749)_

## Summary

Accepting an old invitation could change the role of someone who was
already in the organization. A long-pending invite can carry a lower
role than the member has since been promoted to, so accepting it was a
silent demotion. When the accepting user was the organization's only
Owner, the role layer refused that demotion, and the refusal (an
expected, protective outcome) was logged as an error.

An invitation now only sets a role on a membership the accept actually
created, and people who are already in an organization are skipped when
invitations are sent.

## How

`acceptInvite` already skipped the `OrgMember` create when it found an
existing membership, but the `rbac.setUserRole` call below it was gated
only on `invite.rbacRoleId`. It now also tracks whether this accept
created the membership. A create that loses the unique-constraint race
counts as pre-existing, since whichever flow won it owns that
membership's role.

Skipping existing members outright would regress one case: a member with
no RBAC role at all would never receive the invitation's role.
`ensureOrgMember` handles that with `healMissingRoleAssignment`, which
fills in a null role but never overwrites a real one, so
`assignInviteRbacRole` takes the same gate. An established role is never
touched; an absent one is filled in.

`assignInviteRbacRole` branches on the result's machine-readable `code`
instead of logging every refusal at `error`. `last_owner` goes to
`logger.info`, matching the two directory-sync role paths; everything
else, including a refusal that carries no code, goes to `logger.warn`.
The helper is best-effort and never throws, so no outcome it produces
warrants `error`. No string matching on the error text is involved.

`inviteMembers` resolves the organization's members by email and skips
those addresses before creating invites. The invite table's
`@@unique([organizationId, email])` only dedupes *pending invites*, so
it could never catch this.

## Invite surfaces

Skipping addresses means a batch can now come back empty, and neither
caller handled that:

- The dashboard action built its redirect from
`invites[0].organization`, so a batch where every address was skipped
threw a `TypeError` that reached the admin as a raw error string. It
also reported the submitted count rather than the created one. It now
names what it skipped ("No invitations sent: 1 already a member of this
organization") and counts what it actually created.
- The invites API derived `alreadyInvited` as "everything not created",
so an existing member was reported as though they had already been
invited. `inviteMembers` now returns the two groups separately and the
endpoint reports `alreadyMembers` alongside `alreadyInvited`.

## Testing

`apps/webapp/test/member.server.test.ts` passes 16/16 locally, up from
12.

Getting there needed a harness fix. The `~/db.server` mock did not
export `Prisma`, so any code reaching
`PrismaNamespace.PrismaClientKnownRequestError` threw before it could
branch, leaving every duplicate-key path in `member.server.ts`
unreachable from tests. The mock now re-exports the real `Prisma`, and
there is a case covering the pending-invite skip.

New cases: the invite role is applied when the accept creates the
membership; it is not applied when the member already has a role; it is
applied when an existing member has no role assigned; the organization
is still joined when the assignment is refused with `last_owner`; and
`inviteMembers` reports members separately from pending invites. Forcing
the gate off fails exactly the "already has a role" case, so the
coverage is load-bearing.

`pnpm run typecheck --filter webapp` and `oxfmt --check` both pass.

## Changelog

Accepting an old invitation could change the role of someone who was
already in the organization. An invitation now leaves an existing
member's role untouched, people who are already in an organization are
no longer sent invitations to it, and the invite form says which
addresses it skipped instead of failing with an unhelpful error.

---

##  Checklist

- [x] I have followed every step in the [contributing
guide](https://github.com/triggerdotdev/trigger.dev/blob/main/CONTRIBUTING.md)
- [x] The PR title follows the convention.
- [x] I ran and tested the code works.

## Screenshots

No visual changes. The invite form's toast copy changes, as described
above.

---------

Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Matt Aitken <matt@mattaitken.com>
2026-07-29 15:31:59 +01:00
Chris Arderne 38bf82aebe feat(cli,webapp): target notifications by minimum CLI version (#4407) 2026-07-28 14:23:41 +01:00
Saadi Myftija 44eca4d166 feat(webapp): org-gated internal API origin in run env vars (#4366)
Adds an opt-in way for operators to route deployed runs' API traffic
through a different origin than the public one, per organization. Set
`INTERNAL_API_ORIGIN` on the webapp and enable the
`internalApiOriginEnabled` feature flag (globally or per org, with the
org override winning in both directions): deployed runs for enabled orgs
then get `TRIGGER_API_URL` set to the internal origin instead of
`API_ORIGIN`. Useful for gradually moving run traffic onto a private
network path.

## Design

The origin is resolved when an attempt starts, so flag changes take
effect on the next attempt and roll back the same way, with no task
redeploys. The org override is read fresh per attempt; the global
default comes from the cached flags registry (a cold read fails safe to
the public origin). When `INTERNAL_API_ORIGIN` is unset the flag is a
no-op and no extra queries run, so existing deployments are unaffected.
Dev runs always use the public origin, and `TRIGGER_STREAM_URL` remains
unchanged.
2026-07-28 11:28:09 +02:00
claude[bot] ec562c0e68 fix(webapp): remove unused Electric sync trace routes (#4400)
<!-- ccr-slack-attribution -->
_Requested by **Eric Allam** · [Slack
thread](https://triggerdotdev.slack.com/archives/C0AU83M3136/p1785222101937829?thread_ts=1785207509.304669&cid=C0AU83M3136)_

Removes two dead Remix routes and the helpers only they used.

`app/routes/sync.traces.runs.$traceId.ts` (`/sync/traces/runs/:traceId`)
and `app/routes/sync.traces.$traceId.ts` (`/sync/traces/:traceId`) were
added with the original ElectricSQL run page and lost their only
consumers when the dashboard hooks that called them were deleted.
Nothing in the repo references either route today.

Also removed, because the deleted routes were their only callers:

- `OtelTraceIdSchema`, `RESERVED_ELECTRIC_SHAPE_PARAMS`, `TraceScope`,
`buildElectricTraceWhereClause` from `app/v3/electricShape.server.ts`
(the file stays — `UNSAFE_REALTIME_TAG_CHARS` /
`sanitizeRealtimeTagForSql` / `sanitizeRealtimeTagsForSql` are still
used by `realtime.v1.runs.ts` and `realtimeClient.server.ts`)
- the loader-specific cases in
`apps/webapp/test/spanTraceRoutes.replicaLag.test.ts` and
`internal-packages/run-store/src/runOpsStore.routesSpanTraceReadView.replicaLag.test.ts`

`app/utils/longPollingFetch.ts` is untouched —
`realtimeClient.server.ts` still uses it. `runOpsStore.ts` /
`PostgresRunStore.ts` are untouched too; the unrouted-lookup mechanism
there is generic and stays.

As a plain code fact: the run lookup these loaders performed keyed on
`TaskRun.traceId` alone, which is not an index-backed query shape. That
is noted only as context for why the code is not worth keeping around
unused.

### Judgement call worth a maintainer's opinion

The request was specifically about `/sync/traces/runs/:traceId`, the
route that looks up a run by `traceId`. This PR **also** deletes its
sibling `/sync/traces/:traceId`. The reasoning:

- both routes came in with the same ElectricSQL run-page work
- both lost their only consumers in the same later commit
- neither has any caller anywhere in the repo
- they share the same helper module, so keeping one means keeping the
helpers half-used

If you would rather keep the sibling, reverting just that one file
deletion is easy and does not affect the rest of this PR — say the word
and I will restore it along with the helpers it needs.

##  Checklist

- [x] I have followed every step in the [contributing
guide](https://github.com/triggerdotdev/trigger.dev/blob/main/CONTRIBUTING.md)
- [x] The PR title follows the convention.
- [x] I ran and tested the code works

---

## Testing

Verification run locally from the repo root:

| Command | Result |
| --- | --- |
| `pnpm run format` | clean, no changes produced |
| `pnpm run lint:fix` | clean |
| `pnpm run lint` | pass (exit 0, no findings) |
| `pnpm run typecheck --filter webapp` | pass |
| `pnpm run typecheck --filter @internal/run-store` | pass |

A ripgrep sweep for `sync.traces`, `sync/traces`, `syncTraceRunsLoader`,
`buildElectricTraceWhereClause`, `OtelTraceIdSchema` and
`RESERVED_ELECTRIC_SHAPE_PARAMS` (excluding `node_modules`) returns zero
hits.

**Not fully verified:** both edited test files are testcontainers suites
and need a Docker runtime, which was not available in my environment. I
confirmed each file *collects* correctly with exactly the three intended
remaining tests and no import errors — notably, dropping the
`session.server` / `controlPlaneResolver.server` / `longPollingFetch` /
`env.server` mocks does not break module loading for the surviving
loaders. The assertions themselves then failed only on `Could not find a
working container runtime strategy`. CI should be the real signal here.

Per `apps/webapp/CLAUDE.md`, `pnpm run build --filter webapp` was
deliberately not run.

---

## Changelog

Removed two unused sync routes left over from the original ElectricSQL
run page, along with the helpers and tests that existed only to serve
them. No behaviour change — neither route had any caller.

---

## Screenshots

_n/a — no user-visible surface changes._

💯

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-07-28 09:00:48 +01:00
Matt Aitken 269470fd87 feat(webapp): gate SSO on an entitlement instead of the Enterprise plan (#4393)
The SSO & Directory Sync settings page decided access by comparing the
organization's plan code against the literal string `"enterprise"`. The
webapp now reads a `hasSso` entitlement from plan limits.

## Changes

- **`settings.sso` route** — `planAllowsSso` reads `limits.hasSso`
rather than the plan code; the loader and the action gate on a shared
`getSsoEntitlement` helper.
- **`platform.v3.server`** — new `getSsoEntitlement(orgId)` returning
`entitled | not_entitled | unknown`, behind a new SWR cache namespace
(60s fresh / 120s stale, memory + Redis). This replaces an uncached
billing round-trip that previously ran on every settings load, so the
page gets cheaper than it was.
- **`directorySyncEffects`** — the entitlement is now checked before
applying membership effects, per organization and memoised across a
batch.
- **`@trigger.dev/platform` 1.2.0 → 1.3.0** — required, see below.

## Behaviour worth reviewing

**Revocation now stops SCIM.** Previously the plan check existed only on
the settings page, so an org that lost access kept receiving
directory-sync pushes indefinitely; only the config UI froze. Provision
*and* deprovision are gated, so a revoked entitlement can't remove
members either.

**An unreadable entitlement throws instead of skipping.** Effects are
idempotent and the worker retries, so retrying is lossless where
dropping would silently lose a directory change. It's raised at `warn`
level so a transient billing blip doesn't page anyone.

**The login path is deliberately untouched.** A hard entitlement check
there turns a billing outage into a login outage. Consequence: an org
that loses the entitlement keeps its existing SSO logins working until
the connection is removed. Gating sign-in is a separate decision.

**Self-hosted is unaffected.** With no billing service configured the
helper returns `entitled`, leaving plugin presence and the kill switch
as the only gates — a self-hoster who installed the plugin isn't locked
out of it.

## The dependency bump is load-bearing

The `Limits` schema is a plain `z.object`, so it *strips* unknown keys.
On 1.2.0 the `hasSso` field was silently discarded during parsing and
read as `undefined` no matter what billing sent — a structural accessor
would not have helped. Verified against both builds:

```
1.2.0 → parsed: true | hasSso survives: false
1.3.0 → parsed: true | hasSso survives: true
```

This PR therefore cannot merge before 1.3.0 is published, which it now
is.

## Testing

`apps/webapp/test/directorySyncEffects.server.test.ts` — 7 tests over
the gate: applies when entitled, skips provision and deprovision when
not, throws a warn-level retryable error when unreadable, resolves once
per org across a batch, and gates per org so one unentitled org doesn't
block another.

`pnpm run typecheck --filter webapp` passes (18/18), oxfmt and oxlint
clean.
2026-07-27 13:08:16 +01:00
Eric Allam d3906241a5 feat(webapp): read realtime run rows from the primary, not the replica (#4378)
🦋 Changesets PR / Create Release PR (push) Has been cancelled
🚀 Publish Trigger.dev Docker / 📣 Dispatch main image (push) Has been cancelled
🚀 Publish Trigger.dev Docker / typecheck (push) Failing after 2s
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## Summary

The realtime runs feed hydrates run rows from read replicas, which means
it needs a replica-lag gate to avoid serving a run's previous state
right after a write. Setting
`REALTIME_BACKEND_NATIVE_RUN_READS_FROM_PRIMARY=1` reads those rows from
each run store's primary instead, so there is no lag to gate against: no
probe, no wake delay, no stale-read retries. Off by default, so nothing
changes unless you set it.

## Design

The run stores already decide replica-vs-primary from the *brand* on the
read client they are handed: a branded replica keeps the read on the
owning store's replica, an unbranded writer escalates it to that store's
own primary. So this is a one-line choice at the hydrator, and it stays
correct across topologies. With the run-ops split on, each leg lands on
its own writer and the caller's client is never forwarded across
databases; with the split off, it is the single database's primary.

```ts
const runReader = new RunHydrator({
  readClient: runReadsFromPrimary ? prisma : $replica,
  runStore,
});
```

The same flag skips constructing the lag estimator, since probing a
replica the feed no longer reads would be measuring the wrong thing.

Independently, `AuroraReplicaLagSource` detected Aurora by letting
`aurora_replica_status()` fail, on the assumption that the app-level
catch made that free. It isn't: an unresolvable function is a query
error the driver reports to the error log on every sample, so a
non-Aurora replica produced a continuous stream of error events while
the estimator quietly fell through to its next candidate. It now
resolves the function with `to_regproc` and memoizes the answer, so the
unparseable call never reaches the wire.
2026-07-26 19:43:41 +01:00
Eric Allam e9ac98b7a1 perf(run-store): route id-set reads to the owning store, not both DBs (#4342)
📚 Publish docs / publish (push) Has been cancelled
## Summary

The split run-store's id-set read path (`#findRunsByIdSet`, used by the
runs-list hydrate, the realtime hydrator, and engine sweeps) queried the
new store for the entire id set and then probed the legacy store for the
misses. A run's residency is a total function of its id (run-ops ids
live in the new store, every other id in legacy), so each id belongs to
exactly one store. Route each id to its owner and query each store only
for its own ids, in parallel. Same result set, and while a split is
active with most runs still on legacy it removes a wasted new-store
query from every id-set read.

## Change

`#findRunsByIdSet` now partitions the ids by `classifyResidency` and
runs one bounded query per store (skipping an empty side), in parallel,
mirroring `expireRunsBatch` and the single-run `#route`. `finalizeRows`
still applies orderBy/take/skip globally over the merged set.

This drops the id-set path's cross-store fallback, which existed to
prefer the new-store copy when the same id was present in both stores.
That collision cannot arise when each id maps to exactly one store
(nothing writes a legacy-shaped id into the new store), so the fallback
is dead code. The two id-set tests that asserted "new copy wins on
collision" now assert the routing invariant: a legacy-shaped id resolves
to the legacy store and the path never consults the new store.

The open-predicate path (`#findRunsOpen`) is unchanged: an open `where`
has no id to route on, so it still unions both stores and dedupes.
2026-07-22 23:03:24 +01:00
Katia Bulatova 23d5771d56 feat(webapp): unconfigured billing limit UX and default billing alerts (#4328)
## Default billing alerts + billing limit page UX

- New orgs get default billing alerts: $5, $100, $500, $1000, $2500.
Existing orgs are backfilled by a billing-side data migration (companion
[PR](https://github.com/triggerdotdev/cloud/pull/1657)).
- The billing limit form starts with nothing selected for orgs that
never set a limit — the save button appears once an option is picked.
- The yellow banner now also shows on the billing limits page itself,
asking to configure a limit. Hidden everywhere for members who can't
manage billing.
- Also fixes billing limit alert preview.

Tests
- `apps/webapp/test/billingLimitsRoute.test.ts` — dirty logic for
empty/selected mode
- `apps/webapp/test/billingAlertsDefaults.test.ts` — default values
- `apps/webapp/test/billingAlertsFormat.test.ts` — preview after a limit
change
2026-07-22 21:23:52 +02:00
Chris Arderne bb34a2e224 fix(webapp): scope development branches to each member (#4323)
## Summary

Allow each organization member to use the same development branch name
without colliding with another member's environment. Fixes #4320.

## Fix

Development branches now use the existing member-scoped project, slug,
and organization-member key for upserts. Preview branches retain their
project-wide shortcode behavior.

New development branches receive distinct shortcodes while keeping their
readable, member-scoped slugs. Existing branches continue to resolve
through the member-scoped key, so this requires no migration or
backfill.
2026-07-22 08:20:43 +01:00
Katia Bulatova d05f1a7398 chore(webapp): migrate from Remix compiler to Vite (#4188)
Replaces Remix compiler with the Vite plugin. The Express server
(cluster, socket.io, ws) and the Docker image contract are unchanged.
2026-07-21 15:57:13 +02:00
Chris Arderne 6997aeb05e fix: security release 2026-07-08 (#4316)
⚒️ Publish Worker (v4) / build (supervisor) (push) Has been cancelled
2026-07-21 12:00:58 +01:00
Chris Arderne cc748422d8 test(webapp): replace slow metadata replica guard with unit test (#4312) 2026-07-20 19:17:44 +01:00
Daniel Sutton a7c734c223 test: caller-driven replica-lag + idempotency guards (stacked on #4284) (#4285)
## Stacked on #4284 — tests only

This PR contains **only the tests** that guard the production fixes in
#4284 (its base). Review #4284 first; this branch adds no production
code.

## What

Caller-driven replica-lag and idempotency guards for every fixed site:
- Each guard **drives the real exported caller** (route loader/action,
presenter `.call()`, service, or engine method) against a **real
Postgres** with the owning replica frozen via the shared
`laggingReplica` testcontainer primitive — never a store-seam
reimplementation.
- For a **fixed** site the guard goes **RED when the production change
is reverted**; for a **tolerated read-view** site it's a caller-driven
**GREEN** proof the miss self-heals (returns null/empty, no mutation,
row live on primary).
- The **global-scope idempotency** guard drives the real dedup + claim
path through a **real `MollifierBuffer` over a Redis testcontainer**
(real SETNX/poll/publish), and covers the cross-DB **andWait** waitpoint
wiring and the **expired/failed clear-and-recreate** reacquire cases.

Run with `vitest --no-file-parallelism` (testcontainers). Verified
GREEN, and revert→RED verified per fixed site.
2026-07-19 17:06:45 +00:00
Daniel Sutton ae96b6c175 fix: read-your-writes + global-scope idempotency correctness under the run-ops split (#4284)
## What & why

Two related correctness fixes for the run-ops DB split. Under the split,
run-store reads can route to a **lagging read replica**; a just-written
run/waitpoint/batch can then be missed, causing a wrong decision.

**1. Read-your-writes → owning primary.** Surfaced first as an
intermittent `wait.until({ idempotencyKey })` re-wait on retry. Auditing
the run-store read surface found the same class at sibling sites (some
gating mutations or returning spurious 404s, others
tolerable/self-healing). Reads that must observe their own writes now
route to the owning **primary**
(`findRun`/`findWaitpoint`/`findBatchTaskRunByFriendlyId` →
`*OnPrimary`, a primary re-read on a miss, or a retryable 404 where the
SDK polls). Read-view reads stay on the replica. All additive — the
happy path is unchanged.

**2. Global-scope idempotency across the split.** A `global`-scope key
carries no per-run salt, so the same `(env, task, key)` triggered
concurrently from parents resident on **different** run-ops DBs could
dedup-miss on each DB and create a duplicate (the per-DB unique index
can't enforce cross-DB uniqueness). Such triggers (global scope, or
scope-absent, while split is active) are serialized through the existing
Redis idempotency claim, the loser resolves the winner by id across both
DBs, and the claim is reacquired on the expired/failed
clear-and-recreate path. `run`/`attempt` scope embed the run id and
never contend.

## Stacked for review

This is the **base** of a 2-PR stack, split so review is easier:
- **This PR** — production code only (34 files).
- **Stacked tests PR →
https://github.com/triggerdotdev/trigger.dev/pull/4285** — the
caller-driven guards (55 test files) on top of this branch.

## Validation

Local run-ops split, **both 2-DB and 3-DB**, fresh boot on this branch:
SDK canary 64/71 (only the known concurrency/input-streams/s3 failures),
quarantine sweep **0 unexpected** (340 pass / 16 known / 4 local) in
each topology, dashboard e2e 0 failed. No product regressions.
2026-07-19 17:57:41 +01:00
Daniel Sutton 821972176d fix(run-store,webapp): correct split-database read routing, write residency, and batches list ordering (#4272)
## Summary

Correctness and performance fixes for deployments that split run data
across more than one database. Single-database / self-hosted deployments
are unaffected (they collapse to a single read/write path).

- **Batches list (dashboard):** for some organizations the Batches list
could hide older batches or show them out of order. It now orders and
paginates by creation time (with the id as a stable tiebreak), so every
batch appears exactly once, newest first. The pagination cursor format
changes; older in-flight cursors simply restart from the first page.
- **Reads:** waitpoint and snapshot lookups that are keyed by a single
run now read only the database that holds that run instead of querying
both, removing redundant queries on hot paths (unblock, snapshot reads).
- **Writes:** environment-scoped writes with no owning run (standalone
wait tokens, waitpoint tags, idempotency-key resets) now land in the
same database as that environment's runs, rather than defaulting to the
other one. An idempotency-key reset also falls back to the other
database when it matches nothing, so a reset still clears the key
wherever the run actually lives.

## Notes

Verified end-to-end against multi-database setups: run-keyed reads and
env-scoped writes land on the correct database with no cross-database
writes, and the batches list surfaces every batch in creation order. New
tests cover the batches ordering/reachability and the write-residency
routing.
2026-07-17 16:26:56 +01:00
nicktrn 976171ea16 feat(webapp): management API for orgs, projects, members, and settings (#4146)
## Summary

Adds a set of PAT-authenticated management API endpoints so orgs,
projects, members/invites, environment variables, and a few
project/environment settings can be managed programmatically (scripting,
automation) rather than only through the dashboard. Each route is a thin
wrapper over the **existing** service the dashboard already uses, with
the same authorization applied at the route layer - no new business
logic.

## Endpoints

**Organizations**
- `POST /api/v1/orgs` - create an org (`createOrganization`)
- `PATCH /api/v1/orgs/:orgParam` - rename (title)
- `DELETE /api/v1/orgs/:orgParam` - soft-delete
(`DeleteOrganizationService`; keeps the active-subscription guard)

**Members & invites**
- `GET /api/v1/orgs/:orgParam/members` - list members + pending invites
- `DELETE /api/v1/orgs/:orgParam/members/:memberId` - remove a member
(last-member guarded)
- `POST /api/v1/orgs/:orgParam/invites` - invite by email
(`inviteMembers`, sends the invite email)
- `DELETE /api/v1/orgs/:orgParam/invites/:inviteId` - revoke an invite

**Projects**
- `PATCH /api/v1/projects/:projectRef` - rename
(`ProjectSettingsService`)
- `DELETE /api/v1/projects/:projectRef` - soft-delete
(`DeleteProjectService`)
- `PUT /api/v1/projects/:projectRef/default-region` - set the default
region by worker-group name (`SetDefaultRegionService`)
- project GET/list now return `defaultRegion` (worker-group name, or
null when unset)

**Environments**
- `POST /api/v1/projects/:projectRef/:env/pause` and `/resume`
(`PauseEnvironmentService`)
- `POST /api/v1/projects/:projectRef/:env/regenerate-api-key` - rotate
the env secret key (`regenerateApiKey`, RBAC `write:apiKeys`)
- env var create now accepts an optional `isSecret` flag

## Auth & authorization

- All routes authenticate with a **Personal Access Token**
(`Authorization: Bearer tr_pat_...`).
- Org/project routes are built on the PAT route builders in
`apiBuilder.server.ts`: `createLoaderPATApiRoute` (already existed) and
**`createActionPATApiRoute`** (added here - the loader builder had no
mutation counterpart). The builder runs auth, resolves the org/project
role-floor via `context`, and enforces a declarative `authorization`
block using the same RBAC actions the dashboard applies
(`manage:organization` / `read:members` / `manage:members` /
`manage:project`). Handlers keep a membership-scoped query as the floor,
so a non-member gets a 404. This also gives these routes `tenantContext`
user attribution (Sentry) and `ServiceValidationError`-to-status mapping
for free.
- **Membership floor (important).** The OSS RBAC fallback grants a
permissive ability, so `ability.can(...)` can't reject a non-member on
self-hosted. Every handler therefore resolves the target scoped to the
caller's membership (`members: { some: { userId } }`) → 404 for
non-members. `authorization` is the *role* gate; this is the *tenant*
gate. `resolveOrganizationForApiUser`
(`organizationApiAccess.server.ts`) is the org-tier version of the
existing `findProjectByRef` - org-addressed PAT routes are new, so no
such helper existed before.
- Env-tier routes reuse the existing `authorizePatEnvironmentAccess`
(`write:apiKeys`).

### What `createActionPATApiRoute` gives you

A route is pure declaration - the builder handles auth, RBAC,
validation, tracing, and error mapping:

```ts
export const action = createActionPATApiRoute(
  {
    method: "PUT",                          // one verb, or ["PATCH", "DELETE"] for multi-verb routes
    params: ParamsSchema,
    body: SetDefaultRegionRequestBody,      // zod-validated
    context: async ({ projectRef }) => {    // resolve the org for the RBAC role-floor
      const project = await prisma.project.findFirst({
        where: { externalRef: projectRef, deletedAt: null },
        select: { organizationId: true },
      });
      return project ? { organizationId: project.organizationId } : {};
    },
    authorization: { action: "manage", resource: () => ({ type: "project" }) },
  },
  async ({ params, body, authentication, ability }) => {
    // auth + authz already enforced. Just do the work.
    // `throw new ServiceValidationError("Region not found", 400)` → mapped to that status.
    return json({ ok: true });
  }
);
```

Handled for you, so handlers stay thin:

- **Method allowlist** - `method` accepts a verb or an array; any other
verb → `405` with an `Allow` header, *before* auth runs:
  ```ts
const allowedMethods = method ? (Array.isArray(method) ? method :
[method]) : undefined;
if (allowedMethods && !(allowedMethods as
string[]).includes(request.method.toUpperCase())) {
return json({ error: "Method not allowed" }, { status: 405, headers: {
Allow: allowedMethods.join(", ") } });
  }
  ```
- **PAT / user-actor auth** in a single roundtrip → `401` on
missing/invalid/revoked token.
- **RBAC** - `context` computes the caller's role-floor for the target
org/project; `authorization` gates it → `403` with a structured error
body.
- **Sentry attribution** - `tenantContext.enrich({ userId })` so events
from the handler carry the acting user.
- **Typed errors** - a thrown `ServiceValidationError` is mapped to its
`.status` (default 400); anything else → `500`, and expected boundary
errors are logged as `warn` (kept out of Sentry).
- **Validation** - params / query / headers / body are all zod-checked →
`400` with details.

## Notes for reviewers

- Everything wraps an existing service; the intent is API parity for
things that are currently dashboard-only, not new behaviour.
- `createActionPATApiRoute` is new shared infra (the PAT + RBAC mutation
builder that didn't exist). It's self-contained - the loader builder and
existing routes are untouched.
- `@trigger.dev/core` gets one additive field (`defaultRegion` on the
project response, optional/nullable for client-server version skew) -
changeset included, patch.
- `removeTeamMember`'s last-member guard is now atomic (Serializable
transaction via the `$transaction` helper, with retry), so the dashboard
and API both get it server-side. Added a `## Transactions` rule to
`apps/webapp/CLAUDE.md` (always use the `$transaction` helper);
migrating the remaining direct usages is tracked in TRI-11698.

## Open questions

- ~~Is PAT the right auth (vs OAT for automation)?~~ **Resolved: PAT.**
Organization Access Tokens are currently internal-only (used by the
image builder) and not user-accessible, so they can't back this yet.
- Should any of these be gated behind a flag or scope?
- Naming/shape of the routes.
2026-07-15 10:20:08 +01:00
Daniel Sutton a1ca64613b fix(webapp): reuse the primary db pool for legacy run-ops when DSNs match (#4253)
## Summary

When the run-ops split is enabled, the legacy run-ops database client
was always constructed as its own connection pool, even when it points
at the same database as the primary (control-plane) client. On setups
where those two DSNs resolve to the same physical database, this opened
a second, redundant pool and doubled the number of connections used
against that database. This change makes the legacy client reuse the
primary client's pool whenever their DSNs point at the same database,
and only open a separate pool when they genuinely differ.

## Fix

A small `sameDatabaseTarget` comparison (host, port, database name,
user) decides whether the legacy DSN points at the same database as the
primary. When it does, the legacy handle reuses the primary client by
reference, so no second pool is opened. When the DSNs diverge, the
legacy client is built independently as before, so the split still works
once the databases are actually separate.

Two smaller changes ride along:

- An optional per-pool limit for the run-ops read replica, which
connects unpooled and so draws raw backend connections; unset, it falls
back to the existing default and behaviour is unchanged.
- A startup warning about a missing legacy replica URL is now suppressed
when the legacy client shares the primary pool, where it would be
misleading.

## Verification

Booted the webapp end-to-end in three modes and confirmed the pools
opened as expected via the client's own startup logs and live backend
connection counts: split off (single pool), split on with a shared
database (legacy reuses the primary pool, no doubling), and split on
with separate databases (legacy opens its own pool).
2026-07-14 11:20:21 +01:00
Chris Arderne 703a6dcb4c chore(ci): optimise runners, distribute test shards (#4240)
- Use bigger/smaller runners as recommended by warpbuild
- Distribute test shards more evenly, move internal tests single big
shard
2026-07-13 15:58:33 +01:00
Daniel Sutton bea7e2be90 feat(webapp,run-store): route run-graph reads and writes through the run-store router (#4237)
## Summary

Run-graph data (runs, batches, waitpoints, and their related tables) can
now live in a database separate from the control plane, with every read
and write routed to the correct database by each run's residency. This
makes reading and writing run data more reliable once the two are split,
and is a no-op for single-database installs.

## Design

- Run-graph table access goes through the run-store router, which
selects the legacy or the new run-ops store per run instead of assuming
one shared client.
- The legacy run-ops client is now independently pointable, so legacy
run data can be served from its own database (and replica) rather than
the control-plane connection.
- Run-graph writes go straight to the run-graph database instead of
being forwarded through the control plane, and replication targets are
split so runs in the new database still replicate to analytics without
under-counting.
- Read-through slots refuse the control-plane client, so a missing
residency fails loudly instead of silently reading the wrong database.
- Migration `20260710120000_drop_remaining_run_graph_seam_foreign_keys`
drops the foreign keys that still crossed the run-graph / control-plane
seam, which is what lets the two live in separate databases.

The split stays off unless explicitly enabled and the two databases are
confirmed physically distinct; startup fails closed otherwise.

Verified by running the full dashboard end-to-end suite against both a
single-database configuration and a three-database configuration
(control plane, the new database, and a physically separate legacy
database), with runs on both residencies. No misrouted reads in either
configuration.
2026-07-13 13:54:54 +01:00
Eric Allam 5ba8557a51 chore(webapp,core): remove the end-of-life v3 (engine V1) execution stack (#4236)
## Summary

v3 (the engine that ran the SDK v3 era, internally
`RunEngineVersion.V1`) is end-of-life. Following the removal of the v3
execution apps
([#4194](https://github.com/triggerdotdev/trigger.dev/pull/4194)) and
the legacy dev websocket
([#4198](https://github.com/triggerdotdev/trigger.dev/pull/4198)), this
removes the remaining v3 execution stack from the server.

Clients still on v3 (an old SDK or CLI that has not upgraded) keep
getting a clear "upgrade to v4" response. Triggers, batch triggers,
reschedules, and deploys that resolve to v3 are rejected with a graceful
4xx pointing at the migration guide, never a 5xx, so a stale client
cannot affect server health. Self-hosted instances still running v3
should stay on the 4.5.x release line until they migrate.

## What is removed

- The MarQS queue and its shared/dev queue consumers.
- The v3 socket.io namespaces (coordinator, provider, shared-queue) and
the v3 run lifecycle services (attempt, checkpoint, and batch-resume).
- The graphile-worker background job system; all live jobs already run
on `@trigger.dev/redis-worker`.
- The `DEPRECATE_V3_ENABLED` flag: v3 is now rejected unconditionally,
so the flag is gone.
- Unused v3 exports from `@trigger.dev/core` (the `v3/zodNamespace`
subpath and the legacy socket message catalogs) and the now-dead MarQS
environment variables.

## What stays

The v4 engine is untouched. The graceful v3 rejection boundary stays,
`determineEngineVersion` still detects a v3 project so it can reject it,
and the batch service plus batch-completion worker stay for current
clients. Live queue concurrency limits and metrics now read from the v4
run engine instead of MarQS, and a brand-new dev environment now
defaults to v4.



## Dependency cleanup

Removes webapp dependencies left unused by this change: `seedrandom` and
`semver` (only the removed v3 code used them) plus a set that was
already dead, their orphaned `@types` packages, and two dead files. Adds
a `knip:deps` script and a `knip.json` config so unused dependencies can
be found the same way going forward.
2026-07-13 11:32:06 +01:00
Daniel Sutton c601739d35 perf(webapp,run-store): grouped run-ops reads + mint-kind flip grace (#4227)
## Summary

Two threads on the run-ops split path.

Read path: per-item run reads are batched into grouped queries, a
waitpoint's connected-run reads are bounded, and the dedicated-schema
relation hydrators fetch only the requested columns instead of whole
rows. Retrieve also falls back to the other database when a routed read
misses, so a run whose physical residency diverges from its id shape is
still found rather than returning a spurious not-found. Fewer and
lighter queries on the run read path, with no change to results.

Mint-kind flip safety: flipping which database new runs mint to is now a
deterministic wall-clock cutover, for both per-org and global flips. For
a grace window every process resolves the same database, so a flip
cannot route two concurrent triggers that share an idempotency key to
different databases (which would bypass the per-database unique
constraint and create a duplicate run).

Supersedes the earlier #4205 and #4208.

Draft: validation in progress.
2026-07-13 10:17:12 +01:00
Eric Allam 45527e317a feat(webapp): opt-in worker pool for OTLP ingest transform (#4232)
## Summary

Under high OTLP ingest volume, the whole decode, transform, and enrich
pipeline runs on the request event loop, so a single CPU core becomes
the ceiling while the rest sit idle. This adds an opt-in worker pool
that moves decode, transform, and LLM-cost enrichment onto worker
threads, keeping the main thread free for I/O. It is off by default
(`OTEL_TRANSFORM_WORKER_POOL_ENABLED`), so behavior is unchanged unless
enabled.

## Design

Workers do decode, filter, convert, and enrich (including LLM pricing
match). The main thread stays the single database reader: it loads the
pricing registry and broadcasts the compiled model rows to the workers
(re-broadcasting on every reload), so workers never touch the database.
The pure transform is extracted into a dependency-light module (no
Prisma/Redis/ClickHouse imports) so it can run inside a worker.

Importantly, the main thread keeps the existing single consolidated
insert path, so ClickHouse insert batching and part count are unchanged.
The parallelism buys CPU headroom, not more insert streams (which would
add merge pressure).

The worker is bundled as a standalone file at build time and ships in
the existing image with no Dockerfile change. In local load testing the
pool sustained roughly 2.6x the throughput of the single-thread path and
kept the main thread responsive under load.
2026-07-11 13:38:12 +01:00
Matt Aitken 2cac63f13a fix: improve error labelling, grouping, and stack traces in the Errors feature (#4225)
## Problem

Several display/grouping issues in the **Errors** feature, all rooted in
how the ClickHouse error materialized views (`errors_mv_v1`,
`error_occurrences_mv_v1`) read the stored error JSON produced by
`parseError`:

1. **Messageless errors show "Unknown error".** An empty message falls
straight through `coalesce(nullIf(message,''), 'Unknown error')` to the
literal, even though the error's class `name` is available (e.g. an
Effect tagged error `ListMessagesError` with no message).
2. **Unrelated errors collapse into one group.**
`calculateErrorFingerprint` keys on `type : message : stack`, where
`type` is always the union tag (`BUILT_IN_ERROR`, …), `message` is
empty, and the stack isn't read — so every messageless built-in error
(and every string/custom error) hashes to the same constant input → one
fingerprint.
3. **error_type shows the internal tag.** `coalesce(type, name, …)`
always resolves to `type` (always present), so the column shows
`BUILT_IN_ERROR` instead of the real class name.
4. **Stack traces never populate.** The MVs read `error.data.stack`, but
the serializer stores the trace under `stackTrace` — so the column is
always empty.

## Fix

All display changes are `ALTER TABLE … MODIFY QUERY` on the two views
(migration `035`); the fingerprint change is in the webapp.

- **Fingerprint** (`errorFingerprinting.ts`): fall back **message → name
→ raw**. Messageless errors now group by class name (or raw value for
non-Error throws); message-bearing errors are **unchanged**
(short-circuits at `message`), so existing groups don't split — only
currently-messageless errors get their own group going forward.
- **error_message**: same `message → name → raw` fallback before
`'Unknown error'`.
- **error_type**: coalesce `name → code → 'Error'` (drops the reliance
on the union tag). Built-in → class name, internal → `code`,
string/custom → `Error`.
- **stack trace**: read `error.data.stackTrace`. Bounded as before
(serializer caps 50 frames / 1024 chars per line; MV clips to 2000
chars).

## Migration notes

- `MODIFY QUERY` swaps the view query in place (no drop/recreate gap);
Down restores the previous query.
- **Existing rows are left unchanged** — changes apply only to rows
inserted after the migration. No backfill.

## Tests

`errorFingerprinting.test.ts` — 57 pass, incl. new cases for messageless
class names, string/custom raw values, and stability of message-bearing
fingerprints.

Fixes the display-derivation half of TRI-11938 (error_type + stack
trace); relates to TRI-9254 and TRI-9250.
2026-07-10 18:30:02 +01:00
Eric Allam 1a0198cc5e perf(webapp,clickhouse): move runs empty-state check to ClickHouse (#4202)
## Summary

The runs page's empty-state check (whether an environment has ever had a
run, which decides between the "getting started" and "no runs match your
filters" states) ran a `findFirst` against the Postgres `TaskRun` table.
This moves it to ClickHouse, the same store the runs list itself reads
from, so the check no longer queries `TaskRun`.

## Design

Only the runs list triggers the check now (via an `includeHasAnyRuns`
flag); the other presenters that reuse `NextRunListPresenter` (API,
schedule detail, waitpoint detail, error group) no longer issue it. When
the list is empty it runs `SELECT 1 FROM task_runs_v2 ... LIMIT 1`
filtered on the full `(organization_id, project_id, environment_id)`
sort-key prefix with a configurable `created_at` lower bound
(`RUN_LIST_HAS_RUNS_LOOKBACK_DAYS`, default 30), so it hits the primary
index and reads minimal granules.

Results are cached in a tiered memory + Redis SWR cache. Only positive
("has runs") results are cached, so an environment with no runs is
always re-checked and its first run shows up immediately.
2026-07-09 15:24:31 +01:00
Chris Arderne 34b1a181c2 fix: security release 2026-07-06 (#4199) 2026-07-09 11:58:33 +00:00
Daniel Sutton 80d4819a03 fix(webapp): stop slow database cleanup on project deletion (#4191)
## Summary

Deleting a project triggered an unbounded database cleanup that scanned
the project's entire run history, so deleting a project with many runs
could be very slow. Project deletion is a soft delete again: run data is
retained and the deletion completes quickly.

## Fix

Project deletion ran a cascade hard-delete whose `BulkActionItem` step
filtered through a relation to `TaskRun` scoped by `projectId`. Prisma
compiles that to an `EXISTS`-join over the project's entire `TaskRun`
set (a large, hot table with no `projectId` index), and it ran on every
project deletion unconditionally.

Removing the cascade-cleanup call restores the prior soft-delete
behaviour: queues are removed, the project is marked deleted, and run
data is retained. The cascade-cleanup service (added in
[#4117](https://github.com/triggerdotdev/trigger.dev/pull/4117)) had no
other callers, so it and its test are deleted.
2026-07-08 16:53:24 +01:00
nicktrn 94b30fc1a6 fix(webapp): reject deploy images with runtime-incompatible zstd layers (#4184)
Container runtimes (cri-o / containerd / podman) can't pull
zstd-compressed layers carried in a Docker v2s2 manifest
(`application/vnd.docker.image.rootfs.diff.tar.zstd`). A deploy built
with an outdated CLI can produce exactly that combination - and today
it's promoted to current and then fails every run at image-pull time.

This extends the pre-promotion image check (#4049) to also inspect the
manifest's layer media types. If any layer uses the unpullable zstd/v2s2
media type, the deploy is rejected at finalize with a clear message to
upgrade the CLI and re-deploy, instead of silently shipping a version
that can't start.

The manifest is already returned by the existing ECR `BatchGetImage`
call, so there's no extra registry request for single-arch images.
Parsing is a lenient Zod schema and **fails open** - a manifest we can't
read never blocks a deploy. Manifest lists / OCI indexes (no top-level
`layers[]`) and OCI zstd (`...tar+zstd`, which runtimes support) pass
unaffected.

Also clarifies in the contributor docs that changesets and
`.server-changes/` notes are user-facing and should be written for
users, not maintainers.

refs TRI-11702
2026-07-07 17:20:07 +01:00
claude[bot] 8bf5879b60 test(webapp): poll for replicated rows instead of fixed sleeps in runs replication tests (#4181)
<!-- ccr-slack-attribution -->
_Requested by **Matt Aitken** · [Slack
thread](https://triggerdotdev.slack.com/archives/C032WA2S43F/p1783430373189849?thread_ts=1783430373.189849&cid=C032WA2S43F)_

##  Checklist

- [x] The PR title follows the convention.
- [x] I ran and tested the code works (typecheck of the edited files is
clean; see Testing)

---

## Testing

**Before:** the webapp run-replication test shard failed on nearly every
PR because assertions waited a fixed 1s for rows to replicate from
Postgres → ClickHouse and intermittently checked before the row arrived
under CI load.

**After:** those assertions poll (up to 30s, 250ms interval) until the
rows land, so they pass as soon as replication completes and stop
flaking, without slowing the happy path.

These tests are testcontainers-backed (need Docker + Postgres +
ClickHouse), so the full suite is exercised in CI. Locally I confirmed
the edited `runsReplicationService.part1..part8.test.ts` files
type-check with no new errors.

---

## Changelog

**How:** wrapped the ~21 present-row assertions across
`runsReplicationService.part1..part8.test.ts` in `vi.waitFor`, matching
the existing poll pattern in `part9.test.ts`. Left absence assertions
(expecting 0 rows / no spans) on a fixed settle delay since there is
nothing to poll for. Tests only — no production code changed.

Note: this does NOT touch the `subscribe()` startup race in
`internal-packages/replication/src/client.ts` (a riskier, separate
follow-up).

💯

---
_Generated by [Claude
Code](https://claude.ai/code/session_01KtUdSLKrK17eFVuRYXT6uj)_

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-07-07 16:15:15 +01:00
Chris Arderne aa74e68c71 feat(sdk): add bulk replay to api and sdk (#4105)
## Summary

Adds SDK and API support for run bulk actions. You can now create bulk
cancel or replay actions from `@trigger.dev/sdk` using run IDs or the
same filters as `runs.list()`, then retrieve, list, poll, or abort the
action by its `bulk_` handle.

Tests, docs, changesets added.

## Design

The dashboard bulk action service now accepts structured filters instead
of reading directly from a dashboard request, so the dashboard and API
share the same creation path. Replay actions created through the API are
attributed with the existing `api` trigger source, while
dashboard-created actions keep `dashboard`.

The SDK exposes the new surface under `runs.bulk.*`, including
`targetRegion` for replay region overrides and cursor pagination for
listing bulk actions.

## Filters and runIds

Nuance on filters. If `filter` is provided, it MUST have at least one
key. This is to remove the footgun of passing no filter and selecting
all runs.

```typescript
   { action: "cancel", runIds: ["run_1"] } // valid
   { action: "cancel", runIds: [] } // invalid, min(1)
   { action: "cancel", filter: { status: "FAILED" } } // valid
   { action: "cancel", filter: {} } // invalid
   { action: "cancel", filter: {}, runIds: ["run_1"] } // invalid
```
2026-07-07 15:43:30 +01:00
Daniel Sutton d59743bd35 fix(webapp,run-ops-database): keep run-ops batch items co-resident with their batch (#4178)
## Summary

Three fixes to the run-ops database split (the Cloud-only mode where
run-lifecycle rows live on a dedicated Postgres). All are inert in the
default single-database deployment.

The main fix: on the batch trigger paths, a parentless batch's item runs
chose their physical store from a fresh per-org mint-flag read at
processing time, so flipping an org's flag mid-batch could land an item
in a different store than its batch, breaking the `TaskRun.batchId`
foreign key (or silently orphaning the item). The other two harden the
split's safety nets: the schema-parity test now actually compares
columns, and the read fan-out gate now signals when it has been silently
disabled.

## Batch item residency

`RunEngineBatchTriggerService` (api.v2) and the BatchQueue item callback
(api.v3) now anchor each item's id mint on the batch's own friendlyId,
mirroring the already-safe `BatchTriggerV3Service`. Residency is a pure
id-shape check, so an item can no longer diverge from its batch across a
mid-batch flag flip. The pre-failed-run fallback is anchored the same
way (it also sets `batchId`), and the shared mint branch is consolidated
into one helper so every mint path stays in lockstep. No new database
queries; single-database mode is unchanged (a cuid-shaped batch
friendlyId yields a cuid item).

## Schema parity test

The parity test previously read only the dedicated schema and matched
model headers with regexes, so it never compared columns and could not
catch a run-subgraph column that diverged between the two physical
schemas. It now parses both schemas and asserts bidirectional
scalar-column parity (type, nullability, array-ness, default) across the
run-subgraph models, and fails on any field line it can't parse. Scoped
to the run-subgraph models so unrelated control-plane edits don't break
it.

## Read fan-out signal

The split read fan-out gate is decided by the object identity of the NEW
vs control-plane clients. It now warns when both run-ops URLs are set
but the NEW client isn't a distinct instance (fan-out silently off), and
a new test exercises the real topology-into-gate wiring so a future
refactor that aliases the clients can't disable fan-out unnoticed.

## Verification

New unit and glue tests cover all three changes; the DB-backed
residency, store-routing, and topology suites pass against real
Postgres; `typecheck` is clean for both packages.
2026-07-07 14:17:23 +01:00
Daniel Sutton 4c2c25511b test(webapp): split triggerTask engine test into per-concern files (#4167)
The engine `triggerTask` suite was a single 2447-line file with 23
`containerTest` cases, each spinning its own Postgres + Redis. vitest
shards by whole file, so all 23 container setups landed on one shard and
dominated its wall-clock. The recorded entry in `test-timings.json`
badly under-counts the real cost (it does not capture the
per-`containerTest` container startup that dominates on CI), so the
duration-sharding sequencer treated the file as light and stacked it,
producing one ~21 minute shard.

Splitting does not reduce the number of container setups; it lets those
23 cases distribute across shards instead of stacking on one. The webapp
unit-test stage is gated by its slowest shard, so this cuts the stage's
wall-clock roughly in half.

## CI timing (before vs after)

Real CI wall-clock of the `Unit Tests: Webapp` shards (`--shard=i/10`).
"Before" is sampled from recent runs on other branches (unsplit file,
from `main`); "after" is this PR.

| Shard | Before (s) | After (s) |
|------:|-----------:|----------:|
| 1  | 250 | 359 |
| 2  | 444 | 411 |
| 3  | 497 | 659 |
| 4  | **1257** | 284 |
| 5  | 545 | 641 |
| 6  | 284 | 644 |
| 7  | 244 | 214 |
| 8  | 340 | 445 |
| 9  | 188 | 395 |
| 10 | 234 | 567 |
| **Slowest shard (gates the stage)** | **~1247s (≈21m)** | **659s
(≈11m)** |
| Sum of all shards | 4283 | 4619 |

Before: shard 4 is the long pole at 1237s / 1247s / 1257s across three
sampled runs (the `triggerTask` file plus whatever else the packer put
with it). After: the six pieces spread across shards, the slowest drops
to 659s. The small rise in summed time is the extra per-file container
startup, paid in parallel across shards, so the gating number still
falls by about 10 minutes.

## Change

Split into six per-concern files that share a `triggerTaskTestHelpers`
module (the `vi.mock` calls stay per-file, since vitest hoists them):

- `triggerTask.test.ts` (3): trigger + concurrencyKey coercion
- `triggerTask.idempotency.test.ts` (4): idempotency + queue resolution
- `triggerTask.debounce.test.ts` (4): retries + debounce validation
- `triggerTask.mollifier.test.ts` (4): mollifier call-site behaviour
- `triggerTask.metadataCache.test.ts` (4): DefaultQueueManager task
metadata cache
- `triggerTask.residency.test.ts` (4): child run residency inheritance

All 23 cases are preserved. The file's `test-timings.json` entry is
split across the new files so bin-packing stays balanced.

While rewriting these files, cleanup was moved to `onTestFinished(() =>
engine.quit())` so an `engine`/`Redis` leaked on a failing assertion no
longer persists on the worker-scoped Redis and cascades into later cases
(`hookTimeout` raised to 60s so the after-cleanup gets the full budget).
Prisma lookups switched from `findUnique` to `findFirst` to match the
repo convention.

Verified: all six files run green locally (23/23), oxlint and oxfmt
clean.
2026-07-06 13:03:27 +01:00
Daniel Sutton e4ae8cbcd4 fix(run-engine,run-store,webapp): stop split-mode waits hanging on resume (#4164)
## Summary

On the run-ops database split, a run that waits (`triggerAndWait`,
`batchTriggerAndWait`, `wait.forToken`) could hang forever after its
wait had already completed. The runner reads a resume from
`/snapshots/since` exactly once: if that read returned the resume
snapshot without its completed-waitpoints, the runner logged "executing
without completed waitpoints", advanced its cursor, and never re-read
it, so the awaiting run never continued.

## Root cause

The resume snapshot and its completed-waitpoint rows were written as two
separate commits. This regressed when the split replaced Prisma's atomic
nested `connect` with an FK-free insert (in
[#4163](https://github.com/triggerdotdev/trigger.dev/pull/4163)), and
`/snapshots/since` is served from a read replica. A fetch landing in the
sub-millisecond gap between the two commits, or a multi-reader replica
serving the snapshot from a different point in time than its join rows,
delivered an empty resume. Because the runner consumes each snapshot
once and treats an empty resume as terminal, a single stale read was
fatal and produced a permanent, nondeterministic hang.

## Fixes

- Commit a snapshot and its completed-waitpoint links in one
transaction, restoring the atomicity the split removed.
- Repair the completed-waitpoints from the owning primary when a
multi-reader replica serves the snapshot without its join rows. This
covers single-waitpoint resumes, which carry no
`completedWaitpointOrder` and so were missed by the count-based repair.
- Read the primary in the checkpoint `WAIT_FOR_BATCH` pre-check, so a
batch that already resumed is not re-suspended into a stall.
- Fall back to the primary when a waitpoint token misses both read
replicas, so a token completed immediately after it was minted no longer
returns a spurious 404.
- Route batch-item creation by `batchTaskRunId`, consistent with the
batch-completion count and the row's foreign key.
- Reject control-plane-only relation selects on the dedicated schema
with a clear error instead of an opaque Prisma failure, and stop
`createDateTimeWaitpoint` bypassing residency routing through a caller
transaction.

Verified against the deployed split topology: a resume snapshot and its
completed-waitpoints are now always delivered together, so the runner
can no longer drop a resume.
2026-07-06 10:55:02 +00:00