main
86 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Oskar Otwinowski
|
adaa8e9e30 |
fix(clickhouse): renumber the external deployment id migration to 041 (#4734)
## Summary `goose up` against `internal-packages/clickhouse/schema` panics on `main` today, so ClickHouse migrations cannot be applied from a fresh checkout. Renumbering the external deployment id migration from 040 to 041 clears it. ## Root cause Two migrations claim version 40. [#4615](https://github.com/triggerdotdev/trigger.dev/pull/4615) added `040_create_task_events_search_v2.sql`, and [#4661](https://github.com/triggerdotdev/trigger.dev/pull/4661) added `040_add_task_runs_v2_external_deployment_id.sql` a day later. #4661 was opened before #4615 merged, so 040 was genuinely free at branch time, and because the two files have different names there is no textual conflict for git or a rebase to surface. Both merged green, and no workflow in this repo runs `goose`, so the collision only shows up the first time someone actually migrates. goose parses the numeric filename prefix as the version and refuses duplicates: ``` panic: goose: duplicate version 40 detected: .../040_create_task_events_search_v2.sql .../040_add_task_runs_v2_external_deployment_id.sql ``` It aborts while collecting the directory, before executing any SQL, so nothing was half applied and there is no migration state to repair. This migration gets renumbered rather than the `task_events_search_v2` one because goose keys on the version number and not the filename: version 40 is already recorded wherever 040 has been applied, so renaming that file would re-run an applied migration. Verified with a full `goose up` against ClickHouse 26.2.19.43 (the image pinned in `internal-packages/testcontainers`): migrations apply cleanly through version 41, and `task_runs_v2.external_deployment_id` lands as `String DEFAULT ''`. |
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Oskar Otwinowski
|
8b0385c429 |
feat(run-engine): trigger tasks pinned to an external deployment id (#4664)
The SDK discovers an external deployment id at runtime (explicit TRIGGER_EXTERNAL_DEPLOYMENT_ID always; platform commit-SHA variables and generic fallbacks when TRIGGER_AUTOMATIC_SKEW_VERSION_PROTECTION=1) and sends it alongside lockToVersion; the server resolves precedence (version > external id > current). An id held by a deployed deployment pins the run to that worker; an in-flight or unknown id parks the run in PENDING_VERSION with the id in TaskRun.annotations, wakes it pinned when a deployment carrying the id finalizes (ClickHouse candidates, Postgres authoritative), and expires it after a deadline that re-checks Postgres before acting. Parking outranks delaying and preserves delayUntil. The id is projected to ClickHouse task_runs_v2.external_deployment_id during replication. Redis cache for id-to-worker resolution, guarded version-aware writes. Ids are not unique. Several deployments can hold one id - a --force rebuild is the ordinary way to get there - so resolution always picks the highest version among the candidates, never the newest by timestamp. The rule is applied identically on both paths that can bind a run to a worker: resolveExternalDeployment at trigger time, and PendingVersionSystem when a landing deployment wakes a parked run. Version comparison is numeric on the counter half, so 20260807.10 outranks 20260807.9. A run whose id never lands expires at the deadline with EXTERNAL_DEPLOYMENT_NOT_FOUND and an error naming the id it waited for, which is what a failed build or a typo looks like from the caller. Default deadline is one hour (EXTERNAL_DEPLOYMENT_PARK_DEADLINE_MS). Debounce registration happens in both the parked and the delayed branch through one helper, so a debounced run that parks still binds its debounce key; without it every later trigger for the same key created another parked run, and all of them executed when the deployment landed. The two DELAYED-only status checks in DebounceSystem also accept PENDING_VERSION, without which the lock-contention fallback would rethrow a 5xx the SDK retries and amplifies, and the fast path would push every trigger on a parked key through the redlock. Resolution is skipped in development. A dev environment cannot hold a WorkerDeployment - trigger dev registers a BackgroundWorker with nothing behind it, and deploy --env refuses dev - so an external deployment id there could only ever park, and the parked run then expired against the dev TTL while a connected dev worker sat idle. The id is still annotated so the dashboard shows what the app sent (TRI-13000). |
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Oskar Otwinowski
|
8fded28fcd |
feat(schema): add WorkerDeployment.externalId and task_runs_v2.external_deployment_id (#4661)
Migrations only, no code reads them yet. Postgres: nullable non-unique externalId on WorkerDeployment plus a CONCURRENTLY-built (environmentId, externalId) index in its own migration file. ClickHouse: external_deployment_id String DEFAULT '' on task_runs_v2 (plain String, not LowCardinality - commit SHAs are high-cardinality). Part of task run version skew protection (TRI-12998). |
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Chris Arderne
|
338326c0d0 | fix(clickhouse): lowercase logs search index terms (#4705) | ||
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Chris Arderne
|
49aff3cb39 |
fix(clickhouse): use compatible logs text index syntax (#4704)
## Summary Allow the logs search schema migration to run on ClickHouse versions that require text index options to be literals. ## Root cause The text index declared `lowerUTF8(search_text)` as a preprocessor option. Some ClickHouse versions reject that column expression while parsing index settings. The projected `search_text` is already normalized to lowercase before insertion, so removing the redundant preprocessor preserves search behavior. Verified with the task events search integration tests. |
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Chris Arderne
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f4320937c5 |
chore: prefer direct iteration and function callback types (#4677)
## Summary Enable lint rules that prefer direct iteration and concise function callback types. The existing code now uses direct iteration where no index is needed, and callback contracts use function types consistently. Base: [#4675](https://github.com/triggerdotdev/trigger.dev/pull/4675) |
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Chris Arderne
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b4313c8199 | feat: logs search v2 (#4615) | ||
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Chris Arderne
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b33197691b | chore: enforce no unused deps or code in ci (#4654) | ||
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Eric Allam
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c0b84595a3 |
feat(webapp): hosted webhook ingress, delivery pipeline, and dashboard (#4344)
## Summary The server half of hosted webhooks: the public ingress endpoint, signature verification, the delivery pipeline (Postgres partitioned storage + ClickHouse for ordering), the in-app partition manager, the HTTP API, and the dashboard (Deliveries, Endpoints, and the in-app test console). The public SDK and docs half is #4537. That PR carries the user-facing API (`webhook()`, `chat.event` / `chat.channels`, the `@trigger.dev/slack` connector) and builds on the shared `@trigger.dev/core` schemas that ship here. ## Shipping behind a flag A `WEBHOOK_ENABLED` env var (default off) gates the public ingress route and the engine worker plus partition cron, so merging and deploying this changes nothing in production until it is flipped on per environment. The dashboard is separately gated per org by the `hasWebhooksAccess` feature flag. ## Note on packages This PR includes the `@trigger.dev/core` schema additions the server compiles against, but carries no changeset. Core is not consumed independently of the SDK, so it is released together with the SDK via #4537. Keeping its changeset off `main` means no release cut from `main` publishes it early. |
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Chris Arderne
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1240d91e43 | perf(clickhouse): add task_events_v2 inserted_at minmax index (#4620) | ||
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Chris Arderne
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ed1bb72fb8 |
feat: implement cron window spread backend (#4566)
- New DB fields on Schedule and ScheduleInstance - Use `queueTimestamp` for the "effectiveAt" delayed start time, propagate it to Clickhouse TaskRun table - Disable fastpath for delayed jobs - Add schedule timing logic, API endpoints with windows, persistence - Calculate phase for every schedule, only persist when window is non-null - Additional o11y for phased rollout |
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Eric Allam
|
9d57aff542 |
fix(webapp): make the Queues hero charts environment-wide (#4486)
## Summary The four charts above the queues table aggregated over **at most the 25 queues on the current page**. They reused the loader's already-paginated queue array as a ClickHouse `queue IN (...)` filter, so paging or re-sorting changed the values, and a name search matching nothing blanked the whole chart row. The stat tiles above them were already environment-wide, so the two rows disagreed. They now read `env_metrics`, the environment-level rollup that already exists for exactly this (the built-in Queues dashboard and the health report read it). That is both correct and queue-count-independent: no `GROUP BY queue` across an entire environment, and no client-side summing. Note this is not only a paging artifact: page 1 under-reported too. On the seeded environment below, page 1 read 82% saturation against a true 87%, because the environment's running total is not the sum of one page of per-queue gauges. Three related fixes ride along. **Scheduling delay and throttling sawed to zero.** Both are event-driven, so at the 10-second bucket a short range picks, most buckets hold no samples at all and were drawn as `0ms`. Measured over a 1-hour window: **232 of 349 buckets had no scheduling-delay samples**. A bucket where nothing started is not a bucket where nothing waited, so the line was both ugly and wrong. TRQL grows a `minBucketSeconds` floor, plumbed through the metric resource route, and the hero tiles set 60s. Buckets that still have no samples render as a gap instead of a dive to zero. **The floor must not feed a width-dependent headline.** Two of the four headlines are not peaks, so widening the plotted buckets moved them: - **Throttled** is a share of buckets that saw any throttling, so a single brief throttle came to mark a whole minute instead of ten seconds: the same seeded events read 17% at 10s and 85% at 60s. - **Scheduling delay p95** is a percentile, and merging quantile states over a wider bucket yields a p95 between the sub-buckets' own. Two 240s samples among twenty in one 10-second sub-bucket give a worst-of-six p95 of 240,000ms against a merged 60-second p95 of 5,000ms — a 48x understatement of a headline whose tooltip claims it is the worst in the window. Both charts keep the floor, since a readable line was the point of it. Their headlines now come from a second query at the range's natural bucket width, via an optional `readout` on the tile, so each means what its tooltip says regardless of how the plotted buckets are sized. Saturation and backlog are genuinely width-invariant (a max of maxes is the same at any width), so they are unchanged and issue no extra query. Both caught by Devin in review; I had wrongly lumped p95 in with the peaks. **Charts reported a hydration mismatch on every render.** Recharts resolved victory-vendor's CJS entry on the server and its ESM entry in the browser. Those bundle different d3-shape builds, and the CJS one predates d3-path's digit rounding, so every server-rendered curve carried full-precision coordinates while the client rounded to 3 decimals: ``` Server: M0,3C0.9305555555555555,3,1.8611111111111112,3,... Client: M0,3C0.931,3,1.861,3,... ``` Bundling recharts for SSR makes both sides resolve the same ESM build. Verified: 45 of 45 server-rendered chart curves now match the client, and the page loads with an empty console. ## Verification An isolated stack with 40 seeded queues (20 heavily loaded, 20 idle) and 90 minutes of 10-second buckets written into `queue_metrics_raw_v1`, so the real materialized views built `queue_metrics_v1`, `env_metrics_v1` and the 5m rollup. Ground truth for the environment: 260 running against a limit of 300 (**87% saturation**), 800 queued. | | before | after | | -- | -- | -- | | Saturation, page 1 | 82% peak | **87% peak** | | Saturation, page 2 | 5% peak | **87% peak** | | Backlog / delay, page 2 | "No activity" | **800 peak / 59.5s** | | Name search matching nothing | all four charts blank | charts stay environment-wide | | Metric refetches on a page change | 4, each painting a skeleton | **0, no skeleton** | | Buckets drawn as 0ms with no samples | 232 of 349 | **0** | | Throttled readout | 17% | **17%**, unchanged by the wider buckets | | Worst-p95 readout source | plotted buckets | **natural width**, so a sub-minute spike is not averaged away | | Crosshair reach, hovering one detail-page chart | 2 of 4 others | **4 of 4** | | SSR chart curves mismatching the client | 45 | **0** | The bucket floor was measured across ranges: it widens 10s to 60s at 30m and 1h, and is correctly a no-op at 12h (300s) and 7d (3600s). One extra request per page load, for the throttled readout. The built-in Queues dashboard, which reads `env_metrics` independently, agrees at 86.7% and 260 of 300. `internal-packages/tsql` suite green (612 tests), including 5 new ones for the floor that fail without it. Webapp typecheck, oxfmt and oxlint clean. Spot-checked the Run metrics dashboard and the per-queue detail page for SSR regressions from bundling recharts: both render, console clean. The queue detail page carries the same event-driven series, so its scheduling delay, throttling and per-key mean delay take the same treatment. ## Screenshots <img width="2540" height="580" alt="after-page1-charts" src="https://github.com/user-attachments/assets/6cd23f9c-e7fd-4918-bcfa-b1d3340b16d1" /> ## Rollout Already behind the per-organization `queueMetricsUiEnabled` flag, so only gated orgs see any of it. Blast radius is chart values on one page plus the SSR bundling of recharts; rollback is a revert with no data migration. ## Stated limitations - `wait_ms_count` and the quantile state both only count `wait_ms > 0`, so "nothing started in this bucket" and "everything started instantly" are indistinguishable in storage. Both render as a gap. Distinguishing them needs a schema change, which is not in this PR. - The queue name search deliberately no longer narrows the charts. It only did so incidentally and incorrectly before (first 25 matches, and blanked on zero matches). Search-scoped charts would need the full unpaginated matching set and a server-side aggregate; worth its own ticket if we want it. - Bundling recharts for SSR grows the server bundle slightly. That is the cost of both sides resolving one d3-shape build. - The plotted delay line is a smoothed 60-second view, so a sub-minute spike above the one-minute warning threshold can fail to colour the line even though the headline reports it and colours itself. - Every chart inside one synced group shares the floor, because the hover crosshair is a reference line on a category x-axis and only draws where the hovered bucket exists in the other chart's own data. That costs the queue detail page's gauges some resolution (1 minute instead of 10 seconds) in exchange for the crosshair working across the row. Separately, while taking the screenshots I found a pre-existing rendering bug unrelated to this change: a **perfectly flat** saturation series draws no line at all (the readout still shows the right percentage), which looks like the threshold gradient's offset degenerating when the series min equals its max. It reproduces on `main`, so it is not a regression here and I have left it alone; filed as its own issue. Refs TRI-12784 |
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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. |
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Chris Arderne
|
68ed809416 |
test(clickhouse): keep queue metrics fixtures within TTL (#4428)
## Summary Keeps the queue metrics ClickHouse tests stable as wall-clock time advances. ## Root cause The fixtures used fixed timestamps. Once those timestamps crossed the tables' 30-day retention boundary, ClickHouse immediately expired the inserted aggregate rows and all six tests read empty results. The fixtures now derive a recent minute-aligned timestamp once per test file. The second 10-second bucket and ranking window are derived from the same anchor, preserving deterministic bucket relationships while keeping rows inside both the raw and aggregate table TTLs. Verified with `pnpm --filter @internal/clickhouse exec vitest run src/queueMetrics.test.ts`. |
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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.
|
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|
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>
|
||
|
Chris Arderne
|
dc87b884e7 |
chore: upgrade to typescript 6 (#4310)
## Summary Upgrades the workspace to TypeScript 6.0.3 and applies the compiler, type, and build configuration changes required to preserve package layouts and existing runtime behavior, apart from correcting the HTTP status field used for deployment connection errors. ## Compatibility - Centralizes TypeScript 6.0.3 through the pnpm workspace catalog. - Replaces compiler options and module resolution modes that TypeScript 6 no longer accepts. - Restores explicit Node types where TypeScript 6 no longer includes them transitively. - Adds explicit declaration build roots that preserve each package's existing output layout. - Patches tsup to stop injecting the removed `baseUrl` option during declaration builds. - Uses type-only assertions for stricter typed-array and stream definitions without changing runtime behavior. - Reads the EventSource v3 HTTP status from `code`, so deployment connection errors include it correctly. - Keeps standalone CLI compatibility fixtures pinned to their existing TypeScript version and lockfiles. `turbo run typecheck` and the complete PR test suite are green. |
||
|
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. |
||
|
Eric Allam
|
02cf9c81ad |
fix(tsql): make JSON functions work on the output and error columns (#4221)
## Summary A Query page (TRQL) query that pulls fields out of a run's `output` with JSON functions (`JSONExtractString`, `JSONExtractInt`, `JSONHas`, and the rest of the family) failed with "The first argument of function ... should be a string containing JSON, illegal type: JSON". Those queries now work. ## Root cause and fix `output` is a native ClickHouse `JSON` column, but `JSONExtract*`, `JSONHas`, `JSONLength`, and `JSONType` all expect a String containing JSON text. The compiler already swaps in the column's String companion (`output_text`) when a JSON column is selected or compared, but not inside function-call arguments, so it emitted `JSONExtractInt(output, 'x')` against the native column. The fix prints the companion column for the first argument of these functions when it resolves to a bare JSON field, keeping the table alias when qualified (so it works in JOINs): JSONExtractInt(output, 'x') -> JSONExtractInt(output_text, 'x') JSONExtractArrayRaw(assumeNotNull(output), 'y') -> JSONExtractArrayRaw(assumeNotNull(output_text), 'y') It also reaches through value-preserving passthrough wrappers like `assumeNotNull(...)`, while leaving value-changing wrappers like `toJSONString(output)` on the native column (that argument is already a String). The swap is also semantically correct, not just a type fix: `output_text` is the unwrapped data JSON that the TRQL `output` model already represents, so field paths line up. Covered by printer unit tests and a ClickHouse integration test that runs the whole family (plus the wrapped and `toJSONString` cases) against a real native-JSON column. Both new cases fail with the exact "illegal type: JSON" error without the fix. |
||
|
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.
|
||
|
Daniel Sutton
|
a93b101d44 |
feat(run-ops): cross-producer ClickHouse version helper + cross-Postgres-version compat tests (#4114)
## What - Adds `composeTaskRunVersion` to `@internal/clickhouse` (exported from the package index). It packs a small `originGeneration` epoch into the top 8 bits of the ReplacingMergeTree version and keeps the producer's own LSN in the low 56 bits, so `task_runs_v2` rows replicated from more than one Postgres producer become globally comparable while preserving in-producer ordering. Single-producer setups never call it and keep using the raw LSN version. - Adds unit coverage for the helper in `taskRuns.test.ts` (bit layout, ordering, epoch precedence, range validation). - Adds two run-engine tests that exercise the cross-Postgres-version testcontainer fixture: - `heteroPostgresFixture.test.ts` — a smoke test asserting byte-identity and identical `ORDER BY` (under a pinned ICU collation) across two different Postgres major versions. - `crossVersionCompat.test.ts` — mirrors the run-engine's real raw-SQL surfaces and asserts byte-identical, ordering-identical results across the two versions. Ships with an env-gated block (skipped by default) that can be pointed at a real dedicated database in CI. ## Why Third PR in the run-ops split stack. It is purely additive: it introduces one new exported helper plus tests and changes no runtime call sites, so on its own it has no runtime behavior change. It lays down the version-composition primitive and the cross-version compatibility proof that later PRs in the stack rely on. ## Tests - New unit tests for `composeTaskRunVersion` in `internal-packages/clickhouse/src/taskRuns.test.ts` (run against a real ClickHouse testcontainer). - New cross-version tests in `internal-packages/run-engine/src/engine/tests/` running against real Postgres containers of two different major versions (no mocks). The env-gated dedicated-database block is skipped unless its URL is set. ## Notes Draft, **stacked on #4113** (`runops/pr02-db-foundation`). Review that 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> |
||
|
Chris Arderne
|
448443a024 |
chore: bump internal node to 22 and standardise (#4084)
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. |
||
|
Chris Arderne
|
c7861be520 |
chore: activate no-unused-vars and import linters (#4096)
Once this is merged, oxlint is at a pretty sensible baseline. **Enable `no-unused-vars`, `typescript/consistent-type-imports`, and `import/no-duplicates` lint rules** Turns on three previously-disabled oxlint rules across the monorepo and fixes all violations: - **`no-unused-vars`** – enabled as an error with standard ignore patterns: unused function arguments are ignored by default (`args: "none"`), variables/caught errors/destructured array elements prefixed with `_` are allowed, and rest siblings are permitted. - **`typescript/consistent-type-imports`** – enforced as an error; all type-only imports now use the `import type` syntax. - **`import/no-duplicates`** – enforced as an error; duplicate import statements from the same module have been merged. The remaining commits clean up the violations found across the codebase: removing unused variables/imports/type aliases, adding `_` prefixes to intentionally unused bindings, fixing duplicate imports, and converting value imports to `import type` where appropriate. |
||
|
Matt Aitken
|
536731a5d6 |
feat(clickhouse): infer mixed-type JSON arrays as Array(Dynamic) on insert (#4095)
## ✅ Checklist - [ ] 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. - [ ] I ran and tested the code works --- ## Testing `pnpm run typecheck --filter @internal/clickhouse` passes. This only adds a ClickHouse input-format setting to existing insert calls; the setting affects type inference for newly-inserted/merged data and is non-destructive to existing rows. --- ## Changelog Sets `input_format_json_infer_array_of_dynamic_from_array_of_different_types = 1` on every native-JSON insert path: - `task_runs_v2` (`output`, `error`) — `insertTaskRuns`, `insertTaskRunsCompactArrays`, and the async-insert variants - `task_events_v1` / `task_events_v2` (`attributes`) - `metrics_v1` - `sessions_v1` ### Why Our JSON columns contain arrays with mixed element types (e.g. `[{"key":"value"}, "string", "string"]`). With this setting off — which is the effective default under `24.12` compatibility — ClickHouse infers those as deeply nested unnamed `Tuple(JSON, Nullable(String), …)` types. ClickHouse 26.2 introduced `input_format_binary_max_type_complexity` (default 1000), and those tuple type trees exceeded the limit, causing background merges to fail with **Code 117**. With the setting on (the default since 25.8), mixed-type arrays are inferred as a single `Array(Dynamic)` — a simpler, flatter type representation that never approaches the complexity limit, even once the upstream default limit is restored. Setting this explicitly at insert time keeps behavior deterministic and version-controlled, so it does not depend on the server profile or a future compatibility bump. This is a forward-only change: it only affects newly inserted/merged data and does not rewrite existing parts. Our read path re-serializes these columns to strings (`toJSONString` via the materialized `*_text` columns), so the internal Tuple → Array(Dynamic) representation change is transparent to the application. ### Companion server-side setting To also apply this on the ClickHouse side (covers merges and any writes not going through these code paths), set it on the default user: ```sql ALTER USER default SETTINGS input_format_json_infer_array_of_dynamic_from_array_of_different_types = 1; ``` --- ## Screenshots _N/A_ 💯 🤖 Generated with [Claude Code](https://claude.com/claude-code) https://claude.ai/code/session_01AaChyhestFMBYBWh6bgcCF --- _Generated by [Claude Code](https://claude.ai/code/session_01AaChyhestFMBYBWh6bgcCF)_ --------- Co-authored-by: Claude <noreply@anthropic.com> |
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Chris Arderne
|
bfa902bd18 |
chore: enable more linters (#4080)
Re-enables ~15 oxlint rules that were blanket-disabled before. |
||
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Chris Arderne
|
b54201f986 | chore: switch to oxfmt, oxlint - add ci checks (#3977) | ||
|
James Ritchie
|
a90a495542 |
feat(webapp,database): show a Test column for agent sessions (#4011)
## Summary Sessions started from the agent Test playground were tagged with a `"playground"` tag that rendered in the Sessions table's Tags column. They are now flagged with a real `Session.isTest` boolean (mirroring `TaskRun.isTest`) and surfaced as a dedicated **Test** column with a check icon, to the left of Tags, on both the Sessions page and the Agent landing page, plus a matching **Test** property on the session detail page. This mirrors how Standard and Scheduled task runs already indicate test runs. ## Design `isTest` is a new `Session` column (Postgres) replicated into ClickHouse `sessions_v1` alongside the existing fields. The Sessions list reads `isTest` from Postgres for display (ClickHouse only supplies the ordered session IDs), so the column renders correctly without a ClickHouse backfill. The playground action now sets `isTest: true` on session create instead of writing the `"playground"` tag. The triggered run still carries `playground:true` in its own tags (unchanged). A migration backfills existing sessions, setting `isTest = true` and stripping the now-redundant `"playground"` tag where it is present, so the list and detail views render consistently without read-time tag filtering. |
||
|
nicktrn
|
6bdf800a11 |
feat(clickhouse): replicate run plan type to task_runs_v2 (#3978)
Replicates `TaskRun.planType` into the `task_runs_v2` ClickHouse table so run analytics can group by plan type. Adds a `plan_type` column (goose migration `033`, `LowCardinality(String)`), the replication insert mapping, and the matching schema/column/type entries - same shape as the recent `region` addition. Write-once at trigger, so it just rides along on existing replicated rows. Internal analytics only; not exposed in the Query API. |
||
|
nicktrn
|
7aa871f37b |
feat(webapp): plan-aware compute migration (#3957)
Adds an opt-in mechanism to route a configurable percentage of organizations onto the compute (MicroVM) backing of their region at trigger time, without changing their stored region settings. Routing is gated by three global feature flags - `computeMigrationEnabled`, `computeMigrationFreePercentage`, `computeMigrationPaidPercentage` - plus a per-org `computeMigrationEnabled` override that wins in both directions. A region's compute backing is resolved from a new `WorkerInstanceGroup.region` column: a container group and its MicroVM group share one geo `region`, so the migration swaps the resolved worker queue to the backing group's queue. Orgs are bucketed deterministically by id, so ramping a percentage down keeps a strict subset rather than reshuffling, and a region with no compute backing is never touched. Everything is off by default - behaviour is unchanged unless the flags are set. The flags and the worker-region groups are read on the trigger hot path from in-memory snapshots rather than the database: a small `createReloadingRegistry` helper loads each at startup and refreshes them on an interval, so no per-trigger query is added and a percentage or kill-switch change propagates within the reload interval. A cold replica whose snapshot hasn't loaded yet reads as not-migrated (the container path) and self-corrects on the next load - the same cold-start contract as the datastore / LLM-pricing registries, with a `reloading_registry_loaded` metric so a never-loaded registry is alertable. The same migration decision is consulted at deploy-time template creation so a migrated org gets a compute template built ahead of its first run. This runs in shadow mode (best-effort, never fails the deploy) by default, or - when the `computeMigrationRequireTemplate` flag is on - in required mode, built synchronously at deploy so the first run never builds on-demand and template errors surface at deploy time. So operators keep "which runs ran where" while customers only see geography: the run's actual worker queue is stored raw, and the geo region is stamped separately on `TaskRun.region` (and a new ClickHouse `region` column) at trigger time. Read surfaces - the dashboard, the API, and the Query/Logs page - show the geo region, falling back to the worker queue for runs written before the column existed. Minor follow-ups left out of scope: the percentage flags render as text inputs on the admin flags page (the catalog UI has no numeric control type yet), and `createReloadingRegistry` could later gain pub/sub for sub-second cross-replica propagation if the reload interval proves too slow. |
||
|
Matt Aitken
|
ef04cc39ef |
fix(webapp): use composite keyset cursor for run pagination (#3852)
## Problem
`ClickHouseRunsRepository.listRunIds` / `listRuns` order results by the
composite key `(created_at, run_id)`, but the cursor predicate cut on
`run_id` **alone**:
```ts
.where("run_id < {runId: String}", { runId: cursor })
.orderBy("created_at DESC, run_id DESC")
```
This is only sound when `run_id` lexicographic order matches
`created_at` order. `run_id`s are cuids — only coarsely time-sortable —
so when a burst of runs is created within a sub-second window, the two
orders can diverge. When they do, the next-page predicate (`run_id <
cursor`, where `cursor` is the *last* page element = the smallest
`created_at`, not necessarily the smallest `run_id`):
- **re-includes** rows already returned on a previous page (duplicates),
and
- **skips** rows it should have returned (silent data loss).
For bulk **replay** this caused runs to be replayed more than once
(replay has no idempotency guard). For the dashboard and the `runs.list`
API it could silently repeat or skip runs at page boundaries.
## Fix
Make the cursor predicate match the composite ordering:
- Cursors now encode the full `(created_at, run_id)` key as an **opaque
URL-safe base64 token**
(`base64url({"c":<createdAtMs>,"r":"<runId>"})`), and the query cuts on
the matching tuple — `(created_at, run_id) < (…)` forward / `> (…)`
backward.
- The `ORDER BY` is unchanged, so the query stays aligned with the
table's primary key — no performance regression (the tuple range
predicate is actually more index-friendly than `run_id <` alone).
- Cursors are **server-issued opaque tokens** (the SDK only echoes
`pagination.next` / `pagination.previous` back), so this needs **no
client/SDK update**. Legacy cursors were the bare internal `run_id`;
they're detected by decode failure (a cuid isn't a valid base64-wrapped
JSON payload) and fall back to the old `run_id`-only predicate, so
in-flight cursors keep working and drain naturally. New cursors also no
longer expose a bare internal run id.
- `listRunIds` is now the single cursor-aware list primitive: it returns
`{ runIds, pagination: { nextCursor, previousCursor } }`, and `listRuns`
builds on it (one place constructs cursors). Bulk actions consume the
same method and advance by `pagination.nextCursor`, finishing when it's
`null`.
- `getTaskRunsQueryBuilder` now also selects
`toUnixTimestamp64Milli(created_at) AS created_at_ms`, using a dedicated
`TaskRunListQueryResult` schema. The shared `TaskRunV2QueryResult` stays
`run_id`-only so the run-engine pending-version lookup
(`getPendingVersionIdsQueryBuilder`, which selects only `run_id`)
doesn't fail validation on a column it doesn't query.
## Tests
New `runsRepositoryCursor.test.ts` (testcontainer-backed, real
Postgres→ClickHouse replication):
- **forward** pagination returns every run exactly once when `run_id`
order is the reverse of `created_at` order (reproduces the
duplicate/skip bug — fails on `main`; this
walk-until-`nextCursor`-null-and-assert-complete is exactly the bulk
action's iteration),
- **backward** pagination round-trips to the previous page across a
boundary,
- **legacy** bare-`run_id` cursor still uses the old predicate
(backwards compatibility).
The existing `runsRepository` suites (part1–4) still pass; `part4`'s
`count new runs with listRunIds` test was updated for the new `{ runIds,
pagination }` return shape, and the `clickhouse` `taskRuns`
query-builder snapshots were regenerated for the added `created_at_ms`
column.
## Notes
- Separate, pre-existing issue (out of scope, not introduced here):
`listRuns`' backward display-slicing (`rows.slice(1, size+1)` when
`hasMore`) has an off-by-one that can return a straddled page. Tracked
separately.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
|
||
|
nicktrn
|
f261ff2b85 |
chore(docker): tidy dev postgres + clickhouse images (#3859)
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. |
||
|
nicktrn
|
fa15438e42 |
perf(ci): speed up unit tests with LPT sharding + container scoping (#3855)
Speeds up and de-flakes the unit-test suite: testcontainers booted once per vitest worker (per-test isolation kept only where a test runs background redis work that outlives it), a duration-weighted shard sequencer so each shard does roughly equal work, the slowest suites split, two genuine flakes fixed (`streamBatchItems` shared-redis leak; run-engine waits that relied on fixed sleeps), and transient DockerHub pulls retried. **Timings (CI, per-shard wall):** worst unit-test shard ~771s → ~294s; packages/webapp shards ~250-270s, most internal ~190-240s. All 25 shards green. A shard breaks down as ~70s fixed setup (install / image-pull / generate) + ~70s cold `^build` + the actual container tests. So the remaining cost is mostly the tests themselves plus that fixed setup. **Next (separate, timings):** - **typecheck (~6m24s)** — the slowest check overall; bound by full-graph `tsc`, not the TS version (a TS6 branch is still ~6m17s). The real lever is **tsgo** (the Go compiler). - Possible later: turbo CI caching could trim the ~70s cold build on *warm* runs, but it's conditional (cold runs rebuild anyway) and doesn't touch setup or test time — secondary. `cli-v3` e2e and `sdk-compat` are path-gated (don't run on test-infra changes) and already comfortably fast. |
||
|
Eric Allam
|
97036fb741 |
feat(webapp,clickhouse): export run traces as log, markdown, or jsonl (#3851)
## Summary Adds a trace export to the run page. From the new **Export trace** menu you can copy a run's full trace to the clipboard as Markdown (for pasting into an AI assistant) or download it as a flat Log, a Markdown table, or JSON Lines. Internal engine-debug events are filtered out by default, and errors are surfaced inline with their message. ## Design The export streams events from the store to the gzipped response one at a time and never materialises the span tree, so a trace of any size exports with bounded memory and without stalling the server. Output is flat and chronological: each line carries its own `spanId ← parentSpanId`, so the hierarchy is reconstructable without nesting. Formats share a single streaming pipeline and are pluggable via `?format=log|jsonl|markdown`, so adding a format is an isolated change. ## Screenshots **Export menu** <img width="370" height="252" alt="trace-export-menu" src="https://github.com/user-attachments/assets/3d10304a-8c49-4606-b15d-2859b137419f" /> **In context** <img width="2400" height="1802" alt="trace-export-run-page" src="https://github.com/user-attachments/assets/46c80b30-303b-47c6-9ace-a2fb06f6cb61" /> |
||
|
Katia Bulatova
|
4f8cf4cc63 |
feat(webapp): runs live updating
## Summary The Runs list now updates live without requiring a page refresh. Status changes and other run fields are updated in place while runs are executing. When new runs matching the current filters are created, a "New runs created" refresh button appears above the list. Root runs now show a live child-run status breakdown directly in the status tooltip. ### List live update - Visible runs update in place while they are still running. - A "New runs created" refresh button appears when new matching runs are detected. - Polling stops when all visible runs have finished and a refresh button is already shown. - Polling pauses when the browser tab is not visible. - Runs list status updates and new-run detection share a single runs/live polling path. ### Child-status tooltip - Root run tooltips now display a breakdown of child run statuses. - Child statuses are loaded when the tooltip opens (after a 400ms hover delay). - The tooltip stays up to date while child runs are still changing state. - Handles cases where child runs continue running after their parent run has completed, or have not yet been created. ### Supporting changes - Added hidden-tab awareness to polling. - Added safeguards around polling inputs (`runIds` deduping and limits). ## Test plan - [x] pnpm run typecheck --filter webapp passes - [x] cd apps/webapp && pnpm run test ./test/presenters/mapRunToLiveFields.test.ts --run passes - [x] cd apps/webapp && pnpm run test ./test/runsRepository.part2.test.ts --run -t "hasNewRuns" passes ### Manual smoke: - [x] Active runs update without a page refresh. - [x] A new matching run shows the refresh banner and the banner actions work as expected. - [x] Root run tooltips show live child-status updates and stop polling once child runs settle. --------- Co-authored-by: Ekaterina Bulatova <kathiekiwi@Ekaterinas-MacBook-Pro.local> |
||
|
Dan
|
cd252801eb |
feat: dashboard agent - package upgrades (#3793)
1. in webapp folder update ai-sdk to 6.x.x 2. update vitest to 4.xx |
||
|
Eric Allam
|
61ca40b4b1 |
perf(run-engine,webapp): look up PENDING_VERSION runs via ClickHouse (#3707)
## Summary When a background worker registers, the engine resolves runs that were queued before the worker was ready (status `PENDING_VERSION`). That lookup used to scan a Postgres status index on `TaskRun`. Move it to ClickHouse: query candidate run ids from `task_runs_v2`, then refetch the actual rows from Postgres by primary key with a `status = 'PENDING_VERSION'` guard for idempotency. ## Design The lookup is a pluggable interface on the run engine (`PendingVersionRunIdLookup`). The webapp wires a ClickHouse-backed implementation through the org-scoped `clickhouseFactory` using a new `"engine"` client type, configured by `RUN_ENGINE_CLICKHOUSE_*` env vars. The URL falls back to `CLICKHOUSE_URL` when unset, so self-hosted deployments don't need new config to keep working. When the lookup returns no candidates, one bounded retry is scheduled ~5s later to cover ClickHouse replication lag against `task_runs_v2`. The Postgres status guard on both the candidate refetch and the inner `updateMany` prevents double-promotion when a retry races with a concurrent deploy. Tests cover three existing PENDING_VERSION cases via a small Postgres-backed test adapter; new ClickHouse-backed integration tests will follow. |
||
|
Eric Allam
|
6c9f1f197e |
chore: parameterize docker host ports and wire s2-lite by default (#3642)
## 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.
|
||
|
Eric Allam
|
05d3ab1059 |
docs(clickhouse): require max+1 numbering and idempotent DDL (#3633)
## Summary Codify two rules for ClickHouse migration authors that came out of the 029/030 ordering incident on the TRI-9367 test cloud deploy: 1. **Number files to `max(existing) + 1`, never slot in below the latest.** Goose runs in strict mode in the cloud deploy pipeline and refuses to apply a missing version below the current version — slotting a file in below an already-applied number blocks the next deploy. 2. **DDL must be idempotent** (`ADD COLUMN IF NOT EXISTS`, `DROP COLUMN IF EXISTS`, `CREATE TABLE IF NOT EXISTS`, etc.) so a retry or out-of-order apply (`goose up --allow-missing` for local recovery, manual fixups) is a no-op rather than an error. ## Where the rules live - `internal-packages/clickhouse/CLAUDE.md` — full rules + example for migration authors (and AI agents writing migrations). - `.claude/REVIEW.md` — added a 🔴 finding under "What makes a 🔴 Important finding" so PR reviewers flag either fault as blocking. The existing migration files are left untouched; the idempotency requirement applies going forward. ## Test plan - [ ] Next ClickHouse migration PR uses `IF NOT EXISTS` / `IF EXISTS` forms - [ ] No new migration files numbered below an already-applied version on test/prod |
||
|
Eric Allam
|
032b5a117a |
fix(clickhouse): renumber task_kind migration 029 → 031 (#3631)
## Summary Renumber `029_add_task_kind_to_task_runs_v2.sql` → `031_add_task_kind_to_task_runs_v2.sql` to fix a deploy-blocking out-of-order migration, and make the DDL idempotent with `ADD COLUMN IF NOT EXISTS` / `DROP COLUMN IF EXISTS`. ## Root cause - Migration `030_create_sessions_v1.sql` landed on main on 2026-04-28 (PR #3417) and was applied to test cloud ClickHouse on a subsequent deploy. Current goose version on test ClickHouse: **30**. - Migration `029_add_task_kind_to_task_runs_v2.sql` was authored later on 2026-05-10 as part of the Sessions primitive PR series (`be1a6cf8`). - The next test cloud deploy failed because goose strict-mode refused to apply a missing version *before* the current version: ``` goose run: error: found 1 missing migrations before current version 30: version 29: 029_add_task_kind_to_task_runs_v2.sql ``` ## Fix 1. **Rename to `031_*`** (next available number after 030). Goose now treats it as a new migration after 030 and applies it cleanly on test/prod where the column does not yet exist. 2. **Make the DDL idempotent** (`ADD COLUMN IF NOT EXISTS`). The original 029 may have been applied in environments that ran goose with `--allow-missing` (e.g. some local dev databases) — those would have the column already, and the rename causes goose to see 031 as new and re-attempt the ADD. Idempotent DDL keeps that path safe. The `Down` mirrors with `DROP COLUMN IF EXISTS`. ## Test plan - [ ] Test cloud deploy (after this lands) successfully runs the ClickHouse migration step - [ ] `task_kind` column shows up on `trigger_dev.task_runs_v2` post-migration - [ ] Local environments that had previously applied 029 do not error on the next `goose up` |
||
|
Eric Allam
|
be1a6cf8de |
feat: Sessions primitive — durable run-aware streams + dashboard
Adds Sessions, a durable, run-aware stream primitive that scopes session.in / session.out records to a session (not a single run). Records survive run boundaries; reconnect-from-last-event-id is built in. Server foundation: - New /realtime/v1/sessions/:session/:io/append + /records routes - sessionRunManager + sessionsRepository + clickhouseSessionsRepository - mintRunToken for short-lived per-session tokens - s2Append retry-with-backoff + undici cause diagnostics - /api/v[12]/packets/* exempt from customer rate limits - BackgroundWorker schema gains taskKind enum (TASK, AGENT, SCHEDULED) - TaskRun.taskKind column + clickhouse 029_add_task_kind_to_task_runs_v2 Core types: - new sessionStreams, inputStreams, realtimeStreams packages in @trigger.dev/core - session-streams-api / realtime-streams-api surface Sessions dashboard UI (the primitive's own viewer): - /sessions index + detail routes - SessionsTable, SessionFilters, SessionStatus, CloseSessionDialog - AGENT/SCHEDULED filter in RunFilters + TaskTriggerSource Includes the sessions-primitive changeset. |
||
|
Eric Allam
|
c69e939c34 |
feat: Sessions - bidirectional durable agent streams (#3417)
> ⚠️ **Not released yet.** This PR is the server-side foundation only. The SDK changes that customers will actually use (`chat.agent` migration, `chat.createStartSessionAction`, `useTriggerChatTransport` updates) live on a separate branch and ship together in an upcoming `@trigger.dev/sdk` prerelease. Until that prerelease is published, this surface is reachable only via direct HTTP. ## What this gives Trigger.dev users A new first-class primitive, **Session**, for durable, task-bound, bidirectional I/O that outlives any single run. Sessions are the run manager for `chat.agent` going forward, and they unblock anything else that needs "one identifier, many runs over time" with a stable channel pair the client can write to and subscribe to. ### Use cases unblocked - **Chat agents that persist across many runs.** One session per chat (keyed on your own `chatId` via `externalId`), turns 1..N attach to the same Session, the UI subscribes once and keeps receiving output as new runs take over. - **Approval loops and long-running tasks with user feedback.** The task waits on `.in`, the client writes to `.in`, the server enforces no-writes-after-close. - **Workflow progress streams that live past the run.** Subscribe to `.out` after the task finishes to replay history. - **Resume-next-day flows.** A session is a durable row, not a transient stream. Send a message a day later and the server triggers a fresh run on the same session. ### How it works (Session-as-run-manager) A Session row is task-bound (`taskIdentifier` + `triggerConfig` are required) and owns its current run via `currentRunId` + `currentRunVersion` for optimistic claim. Three trigger paths: 1. **Session create** — `POST /api/v1/sessions` creates the row and triggers the first run synchronously. 2. **Append-time probe** — `POST /realtime/v1/sessions/:session/in/append` checks if the current run is alive; if it has terminated (idle exit, crash, etc.), the server triggers a new run before processing the append. 3. **End-and-continue handoff** — `POST /api/v1/sessions/:session/end-and-continue`, called by the running agent, triggers a fresh run and atomically swaps `currentRunId`. Used by `chat.requestUpgrade()` for version handoffs. Every triggered run is recorded in the `SessionRun` audit table with a reason (`initial`, `continuation`, `upgrade`, `manual`). ## Public API surface ### Control plane - `POST /api/v1/sessions` — create. Idempotent on `(env, externalId)`. Triggers the first run, returns the session and a session-scoped public access token. Returns 409 if the upserted row is already closed. - `GET /api/v1/sessions/:session` — retrieve by friendlyId (`session_abc...`) or by your own externalId (server disambiguates by prefix). - `GET /api/v1/sessions` — list with filters (`type`, `tag`, `taskIdentifier`, `externalId`, derived `status` ACTIVE/CLOSED/EXPIRED, created-at range) and cursor pagination. Backed by ClickHouse. - `PATCH /api/v1/sessions/:session` — update tags / metadata / externalId. - `POST /api/v1/sessions/:session/close` — terminate. Idempotent, hard-blocks new server-brokered writes. - `POST /api/v1/sessions/:session/end-and-continue` — agent-only handoff to a fresh run. ### Realtime - `PUT /realtime/v1/sessions/:session/:io` — initialize a channel. Returns S2 credentials in headers so high-throughput clients can write direct to S2. - `GET /realtime/v1/sessions/:session/:io` — SSE subscribe. Supports Last-Event-ID resume and an opt-in `X-Peek-Settled: 1` header that fast-closes the stream when the upstream is already settled (`trigger:turn-complete`), eliminating long-poll wait on reconnect-on-reload paths. - `POST /realtime/v1/sessions/:session/:io/append` — server-side appends. - `POST /api/v1/runs/:runFriendlyId/session-streams/wait` — runs wait on a session stream as a waitpoint, with a race-check to avoid suspending if data already landed. ### Auth scopes `sessions` is a new resource type. `read:sessions:{id}`, `write:sessions:{id}`, `admin:sessions:{id}` flow through the existing JWT validator. Session-scoped public access tokens minted by the server replace browser-held trigger-task tokens for chat-style flows — the browser never sees a run identifier or a run-scoped token in steady state. ## What's coming after this PR - **SDK + chat.agent migration**: separate branch, separate PR, ships in the next `@trigger.dev/sdk` prerelease alongside this server deploy. Customers using the prerelease `chat.agent` will follow the [upgrade guide](https://github.com/triggerdotdev/trigger.dev/blob/docs/tri-7532-ai-sdk-chat-transport-and-chat-task-system/docs/ai-chat/upgrade-guide.mdx). - **Dashboard surfaces**: dedicated agent list, agent playground, agent view on the run dashboard. Tracking separately. ## Implementation notes - **Postgres `Session` table**: scalar scoping columns (`projectId`, `runtimeEnvironmentId`, `environmentType`, `organizationId`) without FKs, matching the January TaskRun FK-removal decision. Point-lookup indexes only — list queries go to ClickHouse. Terminal markers (`closedAt`, `expiresAt`) are write-once. - **ClickHouse `sessions_v1`**: ReplacingMergeTree, partitioned by month, ordered by `(org_id, project_id, environment_id, created_at, session_id)`. Tags indexed via `tokenbf_v1` skip index. - **`SessionsReplicationService`**: mirrors `RunsReplicationService` exactly — leader-locked logical replication consumer, `ConcurrentFlushScheduler`, retry with exponential backoff + jitter, identical metric shape. Dedicated slot + publication so the two consume independently. - **S2 keys**: `sessions/{addressingKey}/{out|in}`. The existing `runs/{runId}/{streamId}` key format for run-scoped streams is untouched. - **Optimistic claim**: `ensureRunForSession` triggers a run upfront (cheap to cancel if it loses the race), then attempts an `updateMany` keyed on `currentRunVersion`. Loser cancels its triggered run and reuses the winner's. No DB lock held across the trigger. ### What did NOT change Run-scoped `streams.pipe` / `streams.input` and the existing `/realtime/v1/streams/{runId}/...` routes are unchanged. Sessions are net-new — not a reshaping of the current streams API. ## Deploy notes - Set `SESSION_REPLICATION_CLICKHOUSE_URL` and `SESSION_REPLICATION_ENABLED=1` to enable the replication consumer. - The `Session` table needs `REPLICA IDENTITY FULL` set on the prod source DB before the publication is created (same one-time DDL we did for `TaskRun`). Required for delete events to carry full column values. - Cross-form authorization on the `GET /api/v1/sessions/:session` loader (a JWT minted for either form authorizes both URL forms). Action routes are URL-form-specific, matching how the SDK mints PATs. ## Verification - Webapp typecheck clean (10/10). - `apps/webapp/test/sessionsReplicationService.test.ts` — round-trip tests for insert/update/delete through Postgres logical replication into ClickHouse via testcontainers. - Live end-to-end against local dev: create + retrieve (both forms) + update + close, `.out.initialize` + `.out.append` x2 + `.in.send` + `.out.subscribe` over SSE, list with all filter combinations + pagination, `end-and-continue` swap, `X-Peek-Settled` fast-close (verified in browser via reconnect-on-reload and via curl). Replicated row lands in ClickHouse within ~1s. - Multi-round Devin + CodeRabbit review feedback addressed (read-after-write paths use `prisma` writer, info-leak on auth-routes masked as 403, peek-settled discriminator parsing fix, etc.). ## Test plan - [ ] `pnpm run typecheck --filter webapp` - [ ] `pnpm run test --filter webapp ./test/sessionsReplicationService.test.ts --run` - [ ] Start the webapp with `SESSION_REPLICATION_CLICKHOUSE_URL` and `SESSION_REPLICATION_ENABLED=1`. Confirm the slot and publication auto-create on boot. - [ ] `POST /api/v1/sessions` and verify the row replicates to `trigger_dev.sessions_v1` within a couple of seconds. - [ ] `POST /api/v1/sessions/:id/close`, then confirm `POST /realtime/v1/sessions/:id/out/append` returns 400. - [ ] Reuse a closed session's `externalId` on `POST /api/v1/sessions` and confirm 409. - [ ] `GET /realtime/v1/sessions/:id/out` with `X-Peek-Settled: 1` after a turn completes and confirm `X-Session-Settled: true` response header + immediate close. |
||
|
Matt Aitken
|
0977c56efe |
Errors (versions) (#3187)
- Added versions filtering on the Errors list and page - Added errors stacked bars to the graph on the individual error page --------- Co-authored-by: James Ritchie <james@trigger.dev> |
||
|
Saadi Myftija
|
38559480c9 |
feat: replicate trigger_source, root_trigger_source, and is_warm_start to ClickHouse (#3274)
Adds three new top-level columns to the ClickHouse task_runs_v2 table primarily for analytics: - `trigger_source` / `root_trigger_source` - extracted from the existing TaskRun.annotations JSON during WAL replication - `is_warm_start` - new nullable boolean on TaskRun in Postgres, set in the existing taskRun.update() at attempt start (no additional write). null until the first attempt starts. Run region is already available via the existing `worker_queue` column in ClickHouse. |
||
|
Eric Allam
|
1a6481a579 |
feat: add Model Registry feature with catalog pipeline, dashboard pages, and TSQL schema (#3270)
- Add llm-model-catalog package (renamed from llm-pricing) with Claude CLI research pipeline - Add Prisma schema: catalog columns + baseModelName on LlmModel - Add ClickHouse: llm_model_aggregates MV + base_response_model column - Add TSQL llm_models schema for query page integration - Add ModelRegistryPresenter with catalog, metrics, and comparison queries - Add 3 dashboard pages: catalog (cards+table+filters), detail (overview+metrics+cost estimator), compare - Add sidebar navigation under AI section with hasAiAccess feature flag - Add admin dashboard sync/seed for catalog metadata - Add model variant grouping (dated snapshots under base models) - Add shared formatters and design system component usage refs TRI-7941 |
||
|
Eric Allam
|
54d95ee4b9 |
feat: AI prompt management dashboard and enhanced span inspectors (#3244)
- Full prompt management UI: list, detail, override, and version
management for AI prompts defined with `prompts.define()`
- Rich AI span inspectors for all AI SDK operations with token usage,
messages, and prompt context
- Real-time generation tracking with live polling and filtering
## Prompt management
Define prompts in your code with `prompts.define()`, then manage
versions and overrides from the dashboard without redeploying:
```typescript
import { task, prompts } from "@trigger.dev/sdk";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
import { z } from "zod";
const supportPrompt = prompts.define({
id: "customer-support",
model: "gpt-4o",
variables: z.object({
customerName: z.string(),
plan: z.string(),
issue: z.string(),
}),
content: `You are a support agent for Acme SaaS.
Customer: {{customerName}} ({{plan}} plan)
Issue: {{issue}}
Respond with empathy and precision.`,
});
export const supportTask = task({
id: "handle-support",
run: async (payload) => {
const resolved = await supportPrompt.resolve({
customerName: payload.name,
plan: payload.plan,
issue: payload.issue,
});
const result = await generateText({
model: openai(resolved.model ?? "gpt-4o"),
system: resolved.text,
prompt: payload.issue,
...resolved.toAISDKTelemetry(),
});
return { response: result.text };
},
});
```
The prompts list page shows each prompt with its current version, model,
override status, and a usage sparkline over the last 24 hours.
From the prompt detail page you can:
- **Create overrides** to change the prompt template or model without
redeploying. Overrides take priority over the deployed version when
`prompt.resolve()` is called.
- **Promote** any code-deployed version to be the current version
- **Browse generations** across all versions with infinite scroll and
live polling for new results
- **Filter** by version, model, operation type, and provider
- **View metrics** (total generations, avg tokens, avg cost, latency)
broken down by version
## AI span inspectors
Every AI SDK operation now gets a custom inspector in the run trace
view:
- **`ai.generateText` / `ai.streamText`** — Shows model, token usage,
cost, the full message thread (system prompt, user message, assistant
response), and linked prompt details
- **`ai.generateObject` / `ai.streamObject`** — Same as above plus the
JSON schema and structured output
- **`ai.toolCall`** — Shows tool name, call ID, and input arguments
- **`ai.embed`** — Shows model and the text being embedded
For generation spans linked to a prompt, a "Prompt" tab shows the prompt
metadata, the input variables passed to `resolve()`, and the template
content from the prompt version.
All AI span inspectors include a compact timestamp and duration header.
## Other improvements
- Resizable panel sizes now persist across page refreshes (patched
`@window-splitter/state` to fix snapshot restoration)
- Run page panels also persist their sizes
- Fixed `<div>` inside `<p>` DOM nesting warnings in span titles and
chat messages
- Added Operations and Providers filters to the AI metrics dashboard
## Screenshots
<img width="3680" height="2392" alt="CleanShot 2026-03-21 at 10 14
17@2x"
src="https://github.com/user-attachments/assets/f3e59989-a2fa-4990-a9d0-3cacda431868"
/>
<img width="3680" height="2392" alt="CleanShot 2026-03-21 at 10 15
37@2x"
src="https://github.com/user-attachments/assets/2f2d02df-2d2b-44fb-ac6f-9153f6a6c387"
/>
<img width="3680" height="2392" alt="CleanShot 2026-03-21 at 10 15
54@2x"
src="https://github.com/user-attachments/assets/baa161e0-ef91-4fa4-a55f-986b71cccdf0"
/>
|
||
|
Eric Allam
|
1cfc296c6b |
feat(ai): LLM metrics tracking and AI span inspector (#3213)
- Automatic LLM cost enrichment for AI SDK spans (streamText, generateText, generateObject) or any other spans that use semantic gen_ai attributes with support for 145+ models - New AI span inspector sidebar showing model, tokens, cost, messages, tool calls, and response text - LLM metrics dual-write to ClickHouse `llm_metrics_v1` table for analytics - LLM metrics built-in dashboard (unlinked at the moment) - Provider cost fallback — uses gateway/OpenRouter reported costs from `providerMetadata` when registry pricing is unavailable - Prefix-stripping for gateway/OpenRouter model names (e.g. `mistral/mistral-large-3` matches `mistral-large-3` pricing) - Admin dashboard for managing LLM model pricing (list, create, edit, delete, search, test pattern matching) - Missing models detection page — queries ClickHouse for unpriced models with sample spans and Claude Code-ready prompts for adding pricing - AI span seed script (`pnpm run db:seed:ai-spans`) with 51 spans across 12 provider systems for local dev testing - UI fixes: `completionTokens`/`promptTokens` aliases, `ai.response.object` display for generateObject, cache read/write token breakdown ## Screenshots: <img width="1030" height="104" alt="CleanShot 2026-03-17 at 16 48 54@2x" src="https://github.com/user-attachments/assets/bc8fccda-e48b-4d0c-bfb1-e620064e5979" /> <img width="1094" height="1512" alt="CleanShot 2026-03-17 at 16 49 23@2x" src="https://github.com/user-attachments/assets/c2424569-d07e-4d67-a436-e8250043a1ee" /> <img width="1074" height="1412" alt="CleanShot 2026-03-17 at 16 49 18@2x" src="https://github.com/user-attachments/assets/22342ac4-4769-45d1-a328-a24fb9a82a50" /> <img width="1012" height="2292" alt="CleanShot 2026-03-17 at 16 39 01@2x" src="https://github.com/user-attachments/assets/59e327d1-6652-4293-8be0-bb8326e5fbc5" /> <img width="3680" height="2392" alt="CleanShot 2026-03-15 at 08 29 38@2x" src="https://github.com/user-attachments/assets/1f77beb8-de67-495b-b890-bcdb8d7f1fe8" /> --------- Co-authored-by: James Ritchie <james@trigger.dev> |
||
|
Matt Aitken
|
d30ed3421e |
Logs query use_query_condition_cache=1 (#3186)
In theory this will make Log queries faster |
||
|
Matt Aitken
|
5f359be286 |
feature: Errors page (#3172)
A top-level Errors page that aggregates errors from failed runs with occurrences metrics. https://github.com/user-attachments/assets/8f0ef55e-90dd-4faa-9051-59f4665181e4 Errors are “fingerprinted” so similar errors are grouped together (e.g. has an ID in the error message). You can view an individual error to view a timeline of when it fired, the runs, and bulk replay them. |
||
|
Eric Allam
|
2135dc56d6 |
chore(claude): Improve claude code instructions (#3161)
Also includes a claude.md audit workflow for PRs |
||
|
Matt Aitken
|
9ba608d2cf |
TRQL function tests and fixes (#3076)
What changed - Fixed some functions like dateAdd, toString, ifNotFinite - Removed all functions that accept lambdas as they're not supported (yet) - Added tests for all TRQL functions that use ClickHouse |