Cuts CPU on the `engine/v1/worker-actions/*` routes a managed supervisor
calls, and adds the benchmark harness the numbers come from.
Measured on a local stack: **on-CPU per completed run 9.07ms → 6.59ms
(−27%)**, busy fraction 45.6% → 33.8%, with every worker-action p50 down
23–27%. Load was 5,000 runs / 24 virtual supervisors / 90s window /
30,120 requests / 0 errors.
Query-count work from the same investigation is deliberately **not**
here — it will follow as a separate PR.
## The three changes
**1. Split the event-loop monitor in two (~14% of on-CPU, plus ~5pp of
GC).**
`eventLoopMonitor.server.ts` installs a global `async_hooks` hook:
`init` writes a `Map` entry for *every* async resource the process
creates, `before` calls `process.hrtime()` and `context.active()` on
every one. Enabling any async hook also puts V8 on the slow path for
promise instrumentation process-wide. `EVENT_LOOP_MONITOR_ENABLED`
defaulted to `"1"`, so this was the shipping configuration.
The blocked-loop detector is now opt-in (`EVENT_LOOP_MONITOR_ENABLED`,
default `0`). The event-loop *utilization* gauge — a single interval
timer with no per-request cost — moves to its own flag
(`EVENT_LOOP_UTILIZATION_MONITOR_ENABLED`, default `1`) and stays on, so
the useful half survives without the expensive half.
A/B under identical load:
| | monitor on | monitor off | change |
|---|---|---|---|
| on-CPU per run | 9.08ms | 7.25ms | −20% |
| GC self time | 9.80% | 5.05% | −4.75pp |
| dequeue p50 | 76.6ms | 62.8ms | −18% |
| attempts/start p50 | 56.3ms | 43.5ms | −23% |
**2. Bucket route matching by first static path segment (10.4% → 3.9% of
on-CPU).**
`patches/@remix-run__router@1.23.3.patch` already memoized flattened
branches and compiled path regexes. What remained was the linear scan:
`matchRouteBranch` walked the ranked branch list calling `matchPath` per
branch across 521 route files, so every worker-action request paid a
scan proportional to the whole route table.
Branches are now indexed by their lowercased leading segment, with one
always-considered list for branches whose leading segment is dynamic,
splat or optional (and for root/pathless paths). A request walks only
its own bucket merged with that list. Route-matching self time dropped
64% (3.6s → 1.3s over a 90s window).
Ordering is preserved exactly: both lists hold indexes into the already
rank-sorted branch array and are walked in ascending-index order, so the
first match found is the same branch the full scan would have found.
Bucketing lowercases on both sides, so case-insensitive matching still
resolves and `caseSensitive: true` routes are still rejected by
`matchPath` itself. A pathname whose own leading segment can't be
bucketed falls back to the full scan.
Verified equivalent to the unpatched matcher over 20,050 pathnames
(literal, dynamic, splat, optional, case variants, basenames,
percent-encoded) with zero mismatches.
`apps/webapp/test/routeMatchingPatch.test.ts` pins the matching
semantics rather than the optimisation, so it still passes without the
patch.
**3. Demote per-heartbeat and per-dequeue `info` logs to `debug`.**
These are the two highest-rate engine calls and each wrote a synchronous
structured log line on every request. Synchronous `console` writes can
block the loop when stdout backs up, which costs more than the ~1.3% CPU
share suggests.
## The harness
Two benchmarks, neither in the default suite (they run for minutes,
attach the V8 profiler, and report numbers rather than assert on them).
See `apps/webapp/test/bench/README.md`.
- `apps/webapp/test/bench/engineHttp.bench.test.ts` — spawns a real
webapp against throwaway Postgres/Redis containers, seeds a production
environment with a promoted managed deployment, and drives a closed-loop
supervisor pool through the full lifecycle. Profiling runs over CDP
rather than `--cpu-prof` so it covers only the measured window instead
of being swamped by boot, and `performance.eventLoopUtilization()` is
sampled *inside* the webapp process.
-
`internal-packages/run-engine/src/engine/bench/runEngineLifecycle.bench.test.ts`
— drives `RunEngine` directly, profiling enqueue and lifecycle
separately so engine cost isn't mixed with request-stack overhead.
- `apps/webapp/test/bench/analyzeProfile.ts` — dependency-free
`.cpuprofile` analyzer that symbolicates through the build's source maps
and ranks CPU by package, self time and total time. Percentages are
shares of on-CPU time (V8's `(idle)`/`(program)` excluded).
`startWebapp` gains `overrideEnv`, applied after the worker-disable
defaults, so the HTTP bench can re-enable the run engine worker that
drains the master queue into the worker queues a supervisor dequeues
from.
The local OTel collector gains a traces pipeline. It only defined a
metrics pipeline, so pointing `INTERNAL_OTEL_TRACE_EXPORTER_URL` at it
locally failed and the webapp silently fell back to the console span
logger.
## Configuration
For operators upgrading:
- `EVENT_LOOP_MONITOR_ENABLED` (now defaults to `0`) — the
per-async-resource blocked-loop detector. Set to `1` to restore the
previous behaviour and keep emitting `event-loop-blocked` spans.
- `EVENT_LOOP_UTILIZATION_MONITOR_ENABLED` (new, defaults to `1`) — the
`nodejs.event_loop.utilization` gauge. Unchanged in behaviour; it just
has its own flag now so it survives turning the detector off.
## Notes for review
- `pnpm-lock.yaml` changes only because the router patch content
changed, which changes its patch hash.
- One thing the profile ruled out: with a real OTLP collector receiving
spans, tracing costs ~1.7% of on-CPU at 100% sampling and ~0.8% at the
production rate. Span shipping is not a hidden cost, so nothing here
touches it.
- Caveats on the numbers: a laptop, not production hardware, so DB and
Redis *latency* are unrepresentative (client-side CPU is what's ranked);
single webapp process; throughput varies ~5% run to run, which is why
the claims rest on on-CPU per run rather than req/s.
## Verification
- 20,050-pathname router equivalence check vs the unpatched matcher,
zero mismatches
- `apps/webapp/test/routeMatchingPatch.test.ts` (12 cases) passes
- webapp e2e smoke suite (68 tests) passes through the patched router
- run-engine suites covering the snapshot/attempt paths pass
- `typecheck`, `format`, `lint`, `knip` clean
## Summary
The container entrypoint runs under `set -x`, which echoes every command
to the logs with its variables expanded. Several startup guards
reference full database connection strings, so the DSN (including the
password) was printed to the container logs on every boot. This turns
tracing off around those lines so connection strings are never traced,
while leaving migration behavior and ordinary startup logging unchanged.
## Fix
The leaking lines are the `[ -n "$RUN_OPS_DATABASE_URL" ]` and `[ -n
"$RUN_OPS_LEGACY_DIRECT_URL" ]` guards, and the ClickHouse block (its `[
-n "$CLICKHOUSE_URL" ]` guard plus the lines that build `GOOSE_DBSTRING`
from `CLICKHOUSE_URL`). `set -x` prints each of these with the
credential expanded. Tracing is now disabled around each region and
restored afterward, so non-secret tracing is preserved everywhere else.
The existing legacy-migration subshell already protected its own command
body; this adds the missing protection for the guards and the ClickHouse
block.
```sh
{ set +x; } 2>/dev/null
if [ -n "$RUN_OPS_DATABASE_URL" ]; then
set -x
...
```
## Verification
Built the webapp image and ran it with dummy sentinel connection strings
whose password token is `S3NTINEL_PW_DoNotLog`, then grepped the boot
logs.
Before (unmodified), the token appears in the traced guards:
```
+ [ -n postgresql://user:S3NTINEL_PW_DoNotLog@fake-host:6432/run-ops ]
+ [ -n postgresql://user:S3NTINEL_PW_DoNotLog@fake-host:5432/legacy ]
+ [ -n https://default:S3NTINEL_PW_DoNotLog@fake-host:8443 ]
```
After, `grep S3NTINEL_PW_DoNotLog` on the same run returns nothing, and
the normal "skipping ... migrations" lines still log.
## Summary
Updates the internal development, CI, and runtime-image Node version to
24.18.0. SDK compatibility coverage continues to include Node 20, 22,
24, and 26.
The Node type definitions and the package-manager lockfiles now resolve
against Node 24 types.
## 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.
## Build-blocker hotfix
`publish.yml` on `main` is failing to build the image after #4154
merged:
```
@trigger.dev/database:generate: Error: Cannot find module '/triggerdotdev/scripts/retry-prisma-generate.mjs'
… ERROR: process "/bin/sh -c pnpm run generate" did not complete successfully: exit code: 1
```
## Cause
#4154 (Windows-CI hardening) changed the `generate` scripts of
`@trigger.dev/database` and `@internal/run-ops-database` to call `node
../../scripts/retry-prisma-generate.mjs`. But `docker/Dockerfile`'s
`builder` stage does `COPY docker/scripts ./scripts` (replacing the
scripts dir) and then copies back only the specific root scripts it
needs (`updateVersion.ts`, `bundleSdkDocs.ts`) before `RUN pnpm run
generate` — the new `retry-prisma-generate.mjs` wasn't copied, so `pnpm
run generate` can't find it and the image build fails.
`publish.yml` only runs on push to `main` (not on PRs), so #4154's PR CI
never built the image and this slipped through.
## Fix
One line — copy the retry script alongside the other root scripts before
the generate step:
```dockerfile
COPY --chown=node:node scripts/retry-prisma-generate.mjs scripts/retry-prisma-generate.mjs
```
## Verification
Built locally with `docker build --target builder` (the stage that runs
`pnpm run generate`) to confirm the generate step now passes — result
appended once it finishes.
No changeset / `.server-changes` — Dockerfile/build-only change, no
package or server-runtime change.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## What
Adds the ability to **automatically migrate the dedicated run-ops
database** (the NEW DB in the run-ops split), matching how every other
database in the system is migrated. Follow-up to the run-ops split
activation.
## Changes
- **Migrate runner** — new
`internal-packages/run-ops-database/scripts/migrate.mjs`, exposed as
`db:migrate:deploy` / `db:migrate:status`. Connects via
`RUN_OPS_DATABASE_URL` (the same var the app uses) and expands `${VAR}`
refs like Prisma's dotenv.
- **Self-host** — `docker/scripts/entrypoint.sh` runs the run-ops
migration on boot when the DB is configured, gated by
`SKIP_RUN_OPS_MIGRATIONS`. Single-DB installs never set the URL, so it's
a clean no-op.
- **Single env-var family** — the run-ops DB is now addressed by one
canonical `RUN_OPS_*` family, connect path and migrations resolving the
identical URL:
- `RUN_OPS_DATABASE_URL` (writer) — replaces `TASK_RUN_DATABASE_URL`
- `RUN_OPS_LEGACY_DATABASE_URL` — replaces
`TASK_RUN_LEGACY_DATABASE_URL`
- `RUN_OPS_DATABASE_READ_REPLICA_URL` — replaces
`TASK_RUN_DATABASE_READ_REPLICA_URL`
- the old `TASK_RUN_*` aliases, the `??` coalesce, the
`runOpsNewDatabaseUrl` indirection, and the migrate-only `directUrl` are
all removed (consumers read `env.RUN_OPS_DATABASE_URL` directly).
`directUrl` was dropped because it was only ever used by `prisma
migrate` (never the app runtime) to bypass a pooler for advisory locks —
premature here since the run-ops connection isn't wired to the app yet.
If a pooler is later introduced for the app, a direct URL can be
reintroduced then.
## Safety
- **Pure rename** — nothing deployed sets any `TASK_RUN_*` var (the
split isn't activated anywhere yet; `.env.example`, docker-compose, and
cloud already use `RUN_OPS_*`), so there is no config migration.
- **Single-DB / self-host** — no new required env var; entrypoint and
migrate are no-ops when `RUN_OPS_DATABASE_URL` is unset.
- **Cloud** — runs migrations as pre-deploy ECS tasks (companion cloud
PR), calling these same `db:migrate:deploy` / `db:migrate:status`
commands.
## Verification
- Live migration against a fresh scratch DB with only
`RUN_OPS_DATABASE_URL` set: both migrations applied, no `P1012`/`P1013`;
`${VAR}` expansion, idempotent re-run, `status`, and no-op skip all
pass.
- Schema parity 4/4; `typecheck --filter webapp` 18/18; affected
split/replication tests 34/34.
## Scope
This delivers automatic migrations only. Enabling the app to *use* the
new DB (setting `RUN_OPS_DATABASE_URL` + `RUN_OPS_SPLIT_ENABLED` on the
service) is a separate activation step.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## What
The **dedicated run-ops database** foundation for the split: a
standalone Prisma package plus the infra to run and migrate it.
- **`internal-packages/run-ops-database`** — a new Prisma package
(`@internal/run-ops-database`) whose schema mirrors the run-execution
tables that will live on the dedicated DB, with its own generated
client, migrations, and migration runner.
- **`prisma/schema.parity.test.ts`** — a parity test that guards the
run-ops schema against drift from the control-plane schema for the
mirrored tables.
- **Docker** — a Postgres 17 service (`docker/Dockerfile.postgres17`,
`docker/docker-compose.yml`) so the dedicated DB is available locally
under the run-ops compose profile.
- **Testcontainers** — hetero fixtures (PG14 legacy + PG17 dedicated) so
later PRs can exercise cross-database behaviour with real containers
rather than mocks.
## Why
This is the **second PR in the run-ops split stack**, stacked on the
core primitives. It stands up the dedicated database and its tooling.
There is **no runtime wiring** into the webapp here — the app does not
read or write this DB yet; that arrives in later PRs. On its own this PR
only adds a package, a docker service, and test fixtures.
## Tests
Schema-parity test for the run-ops schema; hetero testcontainer fixture
smoke test.
## Notes
- Draft, **stacked on #4112** (`runops/pr01-core-residency`). Review
that one first; this diff is against it.
- Server-change / changeset note to be added at stack-assembly time.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Bumps the internal/toolchain Node version to the latest 22.x LTS
(`22.23.1`) and standardises it across the repo. Scope is the **platform
toolchain + the repo's own runtime images** (all `20 → 22` *upgrades*,
off the now-EOL node 20).
### Main changes
- Node `20.20.2 → 22.23.1` across all CI workflows, `.nvmrc`,
`CONTRIBUTING.md`, and the OSS `docker/Dockerfile` (digest-pinned).
- `@types/node → 22.20.0` (root dep + pnpm `overrides`, so the whole
workspace resolves to it); lockfile regenerated.
- `sdk-compat` matrix: adds Node 24 + 26 (keeps 20, still in `engines`).
- **App runtime images → node 22** (were on EOL node 20):
`apps/coordinator` → `node:22.23.1-bookworm-slim`;
`apps/docker-provider` + `apps/kubernetes-provider` → `node:22-alpine`
(reusing the exact digest `apps/supervisor` already runs, so all four
worker images are now identical). Stage aliases renamed off `node-20`.
### Possible issues / test notes
- `@types/node` 22.x can surface new TS errors — typecheck (now on 22)
is the gate.
- **Smoke-test the v3 worker path** — `coordinator` (`crictl`/CRI calls)
and the docker/kubernetes providers (talking to their daemons) now run
on node 22 (alpine/musl for the providers). Upgrade off EOL so low-risk,
but it's deployed runtime code with its own `publish-worker.yml`
pipeline.
The supervisor image build has been failing since `@trigger.dev/core`
gained
an `ai` peer dependency. `turbo prune` (2.5.4) generates a pruned
lockfile
that references the `ai@6.0.116(zod@3.25.76)` snapshot without including
the
entry itself, which causes `pnpm fetch --frozen-lockfile` to abort.
Bumping to 2.10.0 fixes the pnpm v9 peer dep snapshot pruning. Updated
both
Containerfiles for consistency.
Example failure here:
https://github.com/triggerdotdev/trigger.dev/actions/runs/28225353375/job/83618124564
Broken since:
c06005b3
## Summary
Adds an in-dashboard AI agent: a chat panel, reachable from any
environment
page, that answers questions about your runs, errors, tasks, and
analytics,
diagnoses why a run failed, charts your data, reads your connected
repo's
source, and answers product and how-to questions. It is gated behind the
`hasDashboardAgentAccess` feature flag (global or per-org, default off),
so
this PR ships disabled: the launcher is hidden unless the flag is
enabled.
## Design
The agent runs as a standalone `chat.agent` Trigger task in its own
internal
package, with no access to the webapp database, Prisma, or ClickHouse.
It reads
the user's data over the public API, acting as the user via a
short-lived
delegated user-actor token minted server-side each turn (never in the
browser),
building on
[#3997](https://github.com/triggerdotdev/trigger.dev/pull/3997). The
error and analytics tools use
[#4005](https://github.com/triggerdotdev/trigger.dev/pull/4005)
and the TRQL query API.
The first turn of a new chat streams from a warm webapp route (Head
Start) while
the durable agent boots in parallel. Structured answers (a run-failure
diagnosis
card, a live chart) render through a small typed view catalog rather
than
arbitrary markup. A knowledge lane forwards product and how-to questions
to the
support assistant.
Conversation history lives in a separate Drizzle-backed store on its own
Postgres schema, kept as a display read-model so it can never corrupt
the
agent's model context.
The SDK changes add an `apiClient` option to
`chat.createStartSessionAction` and
`chat.headStart`, and keep the Head Start tool-approval tail intact
across a
custom `prepareMessages` hook so prompt caching and Head Start compose.
## Summary
The logs search page (behind a feature flag) ran ClickHouse out of
memory when browsing back over long time ranges. This keeps it within
bounded memory and fixes a pagination bug that could skip or duplicate
rows at a page boundary.
## Fix
Memory: the list query reads in sort-key order, which opens one read
stream per part in the window, and on object storage those per-part read
buffers dominate peak memory, so it scaled with the number of parts
scanned. Two changes bound it:
- The logs ClickHouse client caps the per-part read buffers via new
env-tunable settings. The object-storage-only setting is opt-in, so it
is never sent to a ClickHouse version that lacks it.
- Recent-first window narrowing: rows come back newest first, so the
presenter probes the most recent window and only widens toward the full
requested range when a page is short. A busy environment fills a page
from a few recent parts instead of scanning the whole range; a quiet one
still returns every row in a couple of cheap reads.
Correctness: the keyset cursor ordered on (triggered_timestamp,
trace_id), which is not unique because the spans of a trace share both,
so rows at a tie could be skipped or duplicated across pages. The cursor
and ORDER BY now include span_id, and the cursor is versioned so stale
cursors reset to the first page.
Guards: the effective page size is capped, and the existing per-query
memory limit lets a pathological wide browse fail with an error instead
of taking the node down.
## ClickHouse 26.2
The memory fix relies on lazy materialization deferring the wide
attributes column to the output rows, which only holds on 26.x. Cloud
already runs 26.2, so this moves the dev stack, testcontainers, and CI
to match. The ClickHouse test suite passes on 26.2.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
## Summary
The webapp Docker image build runs `pnpm run build --filter=webapp...`,
which builds `@trigger.dev/sdk` as a dependency. The SDK's `build`
script recently gained a `bundle-docs` step (`tsx
../../scripts/bundleSdkDocs.ts`), but the build couldn't run it in the
pruned image, breaking the image build.
Two things were missing:
- `docker/Dockerfile` copied `scripts/updateVersion.ts` into the builder
stage but not `scripts/bundleSdkDocs.ts`, so the step failed with
`ERR_MODULE_NOT_FOUND`.
- Even with the script present, the repo-level `docs/` tree it reads is
a separate workspace package that isn't in webapp's dependency graph, so
`turbo prune --scope=webapp` excludes it — the script's missing-docs
guard would then fail the build.
## Design
The Dockerfile now copies `bundleSdkDocs.ts` alongside
`updateVersion.ts`. `bundleSdkDocs.ts` skips gracefully when the repo
`docs/` tree is absent, which is exactly the pruned-dependency-build
case (the SDK is compiled there but never published). Publishing always
runs from the full monorepo where `docs/` exists, so the missing-docs
guard still protects releases — it only fires when `docs/` is present
but a cited doc is genuinely missing, rather than when the whole tree
was pruned away. This avoids dragging 27M of docs into a throwaway
builder stage.
## Test plan
- [x] `bundle-docs` from the full monorepo still bundles all cited docs
(exit 0)
- [x] Simulated pruned tree without `docs/` skips cleanly instead of
failing
- [ ] Webapp Docker image build succeeds in CI
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
Two read-replica races on the session APIs could break chats whose first
activity lands inside the replication window (or any time the replica
lags):
1. A session's first `.in` append or `.out` subscribe could fail with a
404 for a session that exists on the writer, because the route resolved
the Session row on the replica only.
2. `ensureRunForSession` probed run liveness on the replica, so a probe
miss on a run triggered moments earlier was judged "run is dead" and a
second live run was spawned for the same session. Both runs then
consumed the same input stream, producing duplicated turns and doubled
responses (and doubled LLM cost).
## Fix
Liveness now re-probes the writer before declaring the current run dead
(the old code already fell back to the writer, but only to recover the
friendlyId, after the wrong verdict was made). Session resolution on the
append and subscribe/init routes goes through a new
`resolveSessionWithWriterFallback`, which stays replica-first on the hot
path and only touches the writer on a miss.
Reproduced and verified against a local streaming replica with an
artificial apply delay: pre-fix, a send immediately after session
creation reliably produced either the 404 or two executing runs with a
doubled response; post-fix, the same flow produces exactly one run and
one response.
Also rides along: the local docker replica's default apply delay drops
from 150ms to a realistic 20ms (override via `REPLICA_APPLY_DELAY` when
you want to deliberately widen the race window).
## Summary
When the realtime runs feed (the backend behind the `realtimeBackend`
feature flag) hydrates a change from a Postgres read replica, the read
can race the replica's apply of the very write that triggered it. The
delivered row then carries the previous change's content, and an
isolated final change (for example a last `metadata.set` before a run
goes quiet) is not corrected until the roughly 20 second backstop poll.
Measured against a replica with deliberate apply delay, every delivery
trailed exactly one change behind and a final change stranded for the
full backstop interval.
## Fix
Publishers stamp each change record with the committed row's
`updatedAt`, taken from writes they already perform, so the stamp costs
no extra queries. The router delays its wake hydrate until the replica's
measured lag has passed, anchored to that timestamp: a record that has
already spent longer than the lag in transit is hydrated immediately, so
only the racing leading edge ever waits. After hydrating, a tripwire
compares each row against its record's watermark. Still-stale rows are
withheld and retried briefly, and each detection feeds the lag estimate.
If retries run out, the rows are delivered anyway (liveness over
freshness) and follow-up re-hydrates emit the fresh version through the
normal working-set diff once the replica catches up, with the backstop
as the terminal net.
Replica lag is sampled reader-side only, and only while feeds are
active. Aurora reports live lag via `aurora_replica_status()`; vanilla
Postgres can only report "caught up or not" (mid-apply lag is not
honestly measurable from a replica), so tripwire observations floor the
estimate there. Deployments without a replica resolve to zero lag and
skip the gate entirely. Tunables live under
`REALTIME_BACKEND_NATIVE_REPLICA_LAG_*`, and
`realtime_native.stale_hydrates` plus
`realtime_native.replica_lag_estimate_ms` make replica health
observable.
Two adjacent fixes: a metadata update that writes nothing no longer
publishes a change record, and buffered parent and root metadata
operations now publish when the flusher writes them, so those changes
wake live feeds instead of waiting for the backstop.
For local testing, `docker-compose` gains an opt-in `database-replica`
service (compose profile `replica`) with a configurable
`recovery_min_apply_delay`, which reproduces replica-lag behavior
deterministically. With the gate disabled this rig reproduces the
one-change-behind delivery exactly; with it enabled, deliveries arrive
with current content at roughly the true replica lag, across write rates
faster and slower than the lag itself.
## Summary
Adds a second backend for the realtime runs feed (`useRealtimeRun`,
`subscribeToRunsWithTag`, `subscribeToBatch`), built to stay healthy
when a single busy environment has many subscribers watching many runs
at once. It is gated behind a feature flag with the existing backend as
the default, so nothing changes for users until it is enabled per
environment.
## Design
A run change is published once, as a small self-describing record, to a
single per-environment channel. Every feed is then a predicate over that
one stream rather than owning a channel:
- A per-instance router indexes the currently-held feeds by run, tag,
and batch. When a run changes it hydrates the affected rows once and
serializes them once, then fans the result to every matching feed. One
hot shared tag watched by many subscribers costs a single database query
and serialize, not one per subscriber.
- Feeds that don't match a change are never woken, wake delivery per
environment is coalesced on a leading edge (250ms default) so a burst of
changes costs one wake, and cold reads coalesce onto a single
short-TTL-cached resolve.
- An admission gate bounds how many cold ClickHouse resolves run
concurrently, so a mass reconnect across many distinct filters queues
instead of stampeding the database.
- Changes that land while a client is between long-polls are delivered
on its next poll instead of waiting for the periodic backstop: each
environment buffers its recent change records, subscriptions linger
briefly after the last feed closes, and a newly-armed poll replays
exactly the connection's gap.
- The per-connection replay cursors behind that are shared across
instances via Redis (a single timestamp each), so a poll landing on a
different instance behind the load balancer still reads the connection's
true gap instead of falling back to a cold resolve. Cursor reads have a
bounded deadline and degrade to the cold-read path on any Redis trouble.
- Tag subscriptions with multiple tags match runs carrying all of the
tags, mirroring the existing backend's filter semantics, and live
long-polls hold for about 20 seconds to match its cadence.
- The per-environment channel supports Redis Cluster sharded pub/sub, so
the wake path scales horizontally across shards by environment.
- The backend reports its health through OpenTelemetry metrics (delivery
lag, poll resolution paths, backstop outcomes, replay and cursor-store
activity), with a provisioned Grafana dashboard for local development.
Everything is behind the feature flag and tunable via env vars; the
existing backend remains the default.
Two small hygiene tweaks to **dev-only** images:
- `docker/Dockerfile.postgres`: add `--no-install-recommends` to the
partman install (leaner image, skips unneeded recommended packages).
- `internal-packages/clickhouse/Dockerfile`: run the migration helper as
a non-root user.
Both are local-dev images (the `pnpm run docker` stack) - no impact on
the published webapp image, prod, or self-hosting.
Hardens the webapp Docker image and adds a CVE scan of each published
image.
- Base image `bullseye-slim` → `bookworm-slim` (Debian 12), pinned by
digest. Adds `apt-get upgrade` + `--no-install-recommends` + apt-cache
cleanup across the build stages so OS packages are patched at build
time.
- Moves the `react-email` CLI to `devDependencies` in
`internal-packages/emails` — only the `email dev` preview script uses
it; the runtime render path is `@react-email/render` +
`@react-email/components`. This also drops the bundled `esbuild` binary
from the production image.
- Bumps `goose` v3.26.0 → v3.27.1 and its Go builder image 1.23 → 1.26.
- Adds a reusable Trivy image-scan workflow wired into `publish.yml`, so
every published image (main builds and releases) is scanned for
OS-package CVEs right after it's pushed to GHCR. Report-only (writes to
the run summary), runs alongside the worker publishes so it never blocks
a deploy.
Verified locally: the image builds clean on the new base, and
`@react-email/render` carries no `esbuild` dependency so email rendering
is unaffected.
## Summary
Two papercuts new contributors hit running this repo locally:
1. Fresh clones default to v1 (Redis-only) realtime streams, so Sessions
and `chat.agent` error with `"S2 configuration is missing"`, even though
the `s2` service is already in `docker/docker-compose.yml` and pre-seeds
a `trigger-local` basin. Wire `REALTIME_STREAMS_S2_*` to it in
`.env.example` so the new-contributor flow just works. (Also drop the s2
healthcheck: the image is distroless, so the `wget` check always reports
unhealthy.)
2. Two clones can't both run `pnpm run docker` because ports, project
name, and container names are all hardcoded. Parameterize every host
port as `${VAR:-default}`, drive the project name via
`COMPOSE_PROJECT_NAME` (with a top-level `name:` field as the default),
prefix container names with `${CONTAINER_PREFIX:-}`, and pass
`--env-file .env` so compose reads the same root `.env` the webapp does.
The "Running multiple instances side by side" block in `.env.example`
lists every overridable knob.
Also split the optional services (`electric-shard-1`, `ch-ui`,
`toxiproxy`, `nginx-h2`, `otel-collector`, `prometheus`, `grafana`) into
`docker-compose.extras.yml` behind a new `pnpm run docker:full` script.
The core stack keeps everything the webapp actually needs to boot:
postgres, redis, electric, minio, clickhouse + migrator, s2-lite.
Defaults match every previous hardcoded value, so existing setups keep
working without touching `.env`.
## Test plan
- [x] `pnpm run docker` on a clean clone brings up the core services on
the standard ports under the `triggerdotdev-docker` project name.
- [x] Setting `COMPOSE_PROJECT_NAME=triggerdotdev-docker-alt` + the
`*_HOST_PORT` overrides in `.env` brings up a second stack alongside the
default one with no port or container-name clashes.
- [x] Webapp boots cleanly against the default `.env.example` values;
`/healthcheck` returns 200, no S2 errors.
- [x] s2-lite basin `trigger-local` accepts an append + read via the
same REST endpoints the webapp uses.
- [x] `pnpm run docker:full` brings up the optional services alongside
the core ones in the same project.
## Summary
Local ClickHouse was burning ~325% CPU endlessly merging its own
telemetry tables (`metric_log`, `asynchronous_metric_log`, `part_log`,
`trace_log`) after the container had been running long enough to
accumulate hundreds of GB of system-log data. OrbStack Helper reflected
this on the host (~400% CPU).
These tables are not used by anything in the dev stack. They only exist
for ClickHouse to log itself, so disabling them eliminates the merge
churn entirely.
## Changes
- Adds `docker/config/clickhouse-disable-system-logs.xml`, mounted into
`/etc/clickhouse-server/config.d/`, that removes the noisy system log
tables via `<table remove="1"/>`.
- Mounts the override file in `docker/docker-compose.yml`.
After applying, idle CPU dropped from 325% to ~12% on my machine.
## Test plan
- [ ] `pnpm run docker` brings up the stack cleanly
- [ ] `docker stats clickhouse` shows low idle CPU
- [ ] App functionality unaffected (system log tables are not queried by
the webapp)
- Tags webapp images by full commit SHA on `main` pushes
(`ghcr.io/triggerdotdev/trigger.dev:<sha>`) so any commit can be
resolved to a digest easily.
- Adds OCI labels (`source`, `revision`, `version`, `created`) so
`docker inspect`, vulnerability scanners, and
registry browsers see source/commit/version directly.
- Signs each pushed digest with SLSA build provenance via
`actions/attest-build-provenance@v4.1.0` (pinned by SHA), enabling `gh
attestation verify oci://...` against the source commit and workflow.
This allows seamless migration to different object storage.
Existing runs that have offloaded payloads/outputs will continue to use
the default object store (configured using `OBJECT_STORE_*` env vars).
You can add additional stores by setting new env vars:
- `OBJECT_STORE_DEFAULT_PROTOCOL` this determines where new run large
payloads will get stored.
- If you set that you need to set new env vars for that protocol.
Example:
```
OBJECT_STORE_DEFAULT_PROTOCOL=“s3"
OBJECT_STORE_S3_BASE_URL=https://s3.us-east-1.amazonaws.com
OBJECT_STORE_S3_ACCESS_KEY_ID=<val>
OBJECT_STORE_S3_SECRET_ACCESS_KEY=<val>
OBJECT_STORE_S3_REGION=us-east-1
OBJECT_STORE_S3_SERVICE=s3
```
---------
Co-authored-by: nicktrn <55853254+nicktrn@users.noreply.github.com>
Input streams enable sending typed data to executing tasks from external
callers — backends, frontends, or other tasks. This unlocks interactive
use cases like approval UIs, cancel buttons, chat interfaces, and
human-in-the-loop AI workflows where the task needs to receive data
while running.
Three consumption patterns inside a task:
* `.wait()` — Suspend the task until data arrives (process freed, most
efficient)
* `.once()` — Wait for the next message (process stays alive)
* `.on()` — Subscribe to a continuous stream of messages
One send pattern from outside:
* `.send(runId, data)` — Send typed data to a specific run's input
stream
## User-facing API
### Define a typed input stream
```ts
import { streams, task } from "@trigger.dev/sdk";
const approval = streams.input<{ approved: boolean; reviewer: string }>({ id: "approval" });
```
### Consume inside a task
```ts
export const myTask = task({
id: "my-task",
run: async () => {
// Pattern 1: Suspend until data arrives (most efficient — frees the process)
const result = await approval.wait({ timeout: "5m" });
// Pattern 2: Wait for next message (process stays alive)
const data = await approval.once().unwrap();
// Pattern 3: Subscribe to multiple messages
approval.on((data) => { /* handle each message */ });
},
});
```
### Send from outside
```ts
// From a backend (using secret API key)
await approval.send(runId, { approved: true, reviewer: "alice" });
// From a frontend (using public JWT token from trigger response)
const { send } = useInputStreamSend("approval", runId, { accessToken });
send({ approved: true, reviewer: "alice" });
```
---------
Co-authored-by: Claude <noreply@anthropic.com>
Adds support for skipping Postgres migrations on container startup via
the new `SKIP_POSTGRES_MIGRATIONS` environment variable.
Set `SKIP_POSTGRES_MIGRATIONS=1` to skip migrations, matching the
existing behavior of `SKIP_CLICKHOUSE_MIGRATIONS`.
## Summary
- Upgrades Node.js from 20.19.0 to 20.20.0 (and 22.12.0 to 22.22.0 for
supervisor) to address the async_hooks stack overflow DoS vulnerability
- Adds `maxDepth` parameter (default 128) to `flattenAttributes` and
`unflattenAttributes` to prevent stack overflow on maliciously deep
nested structures
## Details
The vulnerability (patched in Node.js 20.20.0, 22.22.0, 24.13.0, 25.3.0)
causes unrecoverable crashes (exit code 7) when stack overflow occurs
during async_hooks callbacks. Since the webapp uses `AsyncLocalStorage`,
it was theoretically vulnerable.
### Changes
**Node.js version updates:**
- `docker/Dockerfile`: 20.11.1 → 20.20.0
- `apps/supervisor/Containerfile`: 22-alpine → 22.22.0-alpine
- `.nvmrc`: 20.19.0 → 20.20.0
- `apps/supervisor/.nvmrc`: 22.12.0 → 22.22.0
- `references/prisma-7/.nvmrc`: 20.19.0 → 20.20.0
- All GitHub workflows: 20.19.0 → 20.20.0
**Defense in depth:**
- Added `maxDepth` parameter to `flattenAttributes()` and
`unflattenAttributes()` in `packages/core` to prevent stack overflow on
deeply nested user input
## Test plan
- [x] All existing `flattenAttributes` tests pass (50 tests)
- [x] New tests for depth limiting added
- [x] Verify Docker builds work with new base images
New batch trigger system with larger payloads, streaming ingestion,
larger batch sizes, and a fair processing system.
This PR introduces a new `FairQueue` abstraction inspired by our own
`RunQueue` that enables multi-tenant fair queueing with concurrency
limits. The new `BatchQueue` is built on top of the `FairQueue`, and
handles processing Batch triggers in a fair manner with per-environment
concurrency limits defined per-org. Additionally, there is a global
concurrency limit to prevent the BatchQueue system from creating too
many runs too quickly, which can cause downstream issues.
For this new BatchQueue system we have a completely new batch trigger
creation and ingestion system. Previously this was a single endpoint
with a single JSON body that defined details about the batch as well as
all the items in the batch.
We're introducing a two-phase batch trigger ingestion system. In the
first phase, the BatchTaskRun record is created (and possibly rate
limited). The second phase is another endpoint that accepts an NDJSON
body with each line being a single item/run with payload and options.
At ingestion time all items are added to a queue, in order, and then
processed by the BatchQueue system.
## New batch trigger rate limits
This PR implements a new batch trigger specific rate limit, configured
on the `Organization.batchRateLimitConfig` column, and defaults using
these environment variables:
- `BATCH_RATE_LIMIT_REFILL_RATE` defaults to 10
- `BATCH_RATE_LIMIT_REFILL_INTERVAL` the duration interval, defaults to
`"10s"`
- `BATCH_RATE_LIMIT_MAX` defaults to 1200
This rate limiter is scoped to the environment ID and controls how many
runs can be submitted via batch triggers per interval. The SDK handles
the retrying side.
## Batch queue concurrency limits
The new column `Organization.batchQueueConcurrencyConfig` now defines an
org specific `processingConcurrency` value, with a backup of the env var
`BATCH_CONCURRENCY_LIMIT_DEFAULT` which defaults to 10. This controls
how many batch queue items are processed concurrently per environment.
There is also a global rate limit for the batch queue set via the
`BATCH_QUEUE_GLOBAL_RATE_LIMIT` which defaults to being disabled. If
set, the entire batch queue system won't process more than
`BATCH_QUEUE_GLOBAL_RATE_LIMIT` items per second. This allows
controlling the maximum number of runs created per second via batch
triggers.
## Batch trigger settings
- `STREAMING_BATCH_MAX_ITEMS` controls the maximum number of items in a
single batch
- `STREAMING_BATCH_ITEM_MAXIMUM_SIZE` controls the maximum size of each
item in a batch
- `BATCH_CONCURRENCY_DEFAULT_CONCURRENCY` controls the default
environment concurrency
- `BATCH_QUEUE_DRR_QUANTUM` how many credits each environment gets each
round for the DRR scheduler
- `BATCH_QUEUE_MAX_DEFICIT` the maximum deficit for the DRR scheduler
- `BATCH_QUEUE_CONSUMER_COUNT` how many queue consumers to run
- `BATCH_QUEUE_CONSUMER_INTERVAL_MS` how frequently they poll for items
in the queue
### Configuration Recommendations by Use Case
**High-throughput priority (fairness acceptable at 0.98+):**
```env
BATCH_QUEUE_DRR_QUANTUM=25
BATCH_QUEUE_MAX_DEFICIT=100
BATCH_QUEUE_CONSUMER_COUNT=10
BATCH_QUEUE_CONSUMER_INTERVAL_MS=50
BATCH_CONCURRENCY_DEFAULT_CONCURRENCY=25
```
**Strict fairness priority (throughput can be lower):**
```env
BATCH_QUEUE_DRR_QUANTUM=5
BATCH_QUEUE_MAX_DEFICIT=25
BATCH_QUEUE_CONSUMER_COUNT=3
BATCH_QUEUE_CONSUMER_INTERVAL_MS=100
BATCH_CONCURRENCY_DEFAULT_CONCURRENCY=5
```
* chore(docker): use bitnami legacy repo
* chore(helm): use bitnami legacy repo
* Make Helm webapp chart images configurable
Adds configurability for init and token syncer container images through
new values in the Helm chart configuration
* chore(helm): refactor utility image config
* chore(helm): bump chart version to 4.0.3
---------
Co-authored-by: LeoKaynan <leokaynan@hotmail.com>
* Initial work on upgrading to 6.14.0
Set the output to node_modules still to make it easier
* Use ./generated Prisma folder, update types to fix issues
* Docker compose restart Clickhouse
* Prisma instrumentation update
* Docker
* Removed database dockerignore file, add generated prisma client to the top-level one
* Delete v3-catalog package.json
* Resolved pnpm lock file
* Log errors for very slow queries
* Create schema and migration for organization access tokens
* Add helpers for creating and authenticating OATs
* Adapt the auth service to also accept OATs
* Accept OATs in the whoami v2 endpoint
* Enable deployments with the CLI using OATs
* Avoid reading env variables directly in the token utils
* Remove duplicate cli token utils
* Validate ENCRYPTION_KEY length when parsing env vars
* Make token utils a server-only module
* Disallow revoking already revoked OATs
* Simplify generics in authenticateRequest
* Use 32 bytes mock encryption key in the test setup
* Update dummy encryption key values in tests and templates
* Add a column in the OATs table to differentiate between user and system generated
* Simplify args for v3ProjectPath
Co-authored-by: Matt Aitken <matt@mattaitken.com>
* Add index on org id and createdAt
* Avoid storing the encrypted oat token and its obfuscated version in the DB at all
It is a safer approach. Also we do not need to ever read the decrypted token value after creation.
* Fix prisma update condition
* Add token type to the OAT table index
* Accept OATs in the mcp auth flow
* Simplify env auth flow around the /projects endpoints
---------
Co-authored-by: Matt Aitken <matt@mattaitken.com>
* Sentry WIP
* Configure sentry for uploading and releasing during the publish webapp step
* Delete source maps after uploading
* Forward logger.error calls to sentry through Logger.onError
* Couple tweaks to the dockerfile
* Add retry logic for insert operations
Add a generic retry mechanism for task run and payload inserts to handle
transient connection errors. The new #insertWithRetry method retries up to
three times with exponential backoff and jitter on retryable connection
errors such as connection resets or timeouts. Errors are logged and
recorded in tracing spans to improve observability and robustness of the
replication service.
* Replication settings are configurable
* Log out the runIds for failed batches
* Detecting bad JSON in run replication and ignoring it
* Reproduced split unicode error
* Move output file
* Massively improved the performance
* Minor performance improvements
* Unskip tests
* Remove unused test in CH package
* Fix for the ClickHouse UI explorer
* RunReplication keepAlive defaults to false
* Add concurrency_key and bulk_action_group_ids to ClickHouse task runs
* ClickHouse package doesn't need to be built anymore for the webapp
* Set the concurrency_key from the run replication service
Eric Allam