## Summary
Adds read methods to `RunStore` (`findRun`, `findRunOrThrow`,
`findRuns`) and routes every Postgres read of `TaskRun` through them,
mirroring how writes already go through the store. Behavior-preserving:
each relocated read keeps its exact query, field selection, and database
client (writer, replica, or transaction). This lets `TaskRun` reads be
retargeted to a different backing store later without touching call
sites.
Stacked on #3981 (the write adapter); that PR is the base of this one.
## Scope
In scope: the run engine, webapp services, presenters, and route
loaders. Three reads that pulled `TaskRun` in through a parent model's
relation `include` (alert delivery, batch results, attempt-dependency
cancellation) are decomposed to fetch the run(s) through the store and
stitch them back, since a relation include would not follow `TaskRun` to
a new table.
Left reading the existing table (out of scope): the legacy MarQS paths,
the legacy trigger idempotency read, and one raw-SQL recovery script
(commented for revisiting at cutover).
## Notes
Reads default to the read replica; callers pass the writer or a
transaction client wherever the original read did, so writer-vs-replica
behavior is unchanged.
Follow-up to #3992, which gated the send runner-side - but only for new
runner images. Existing runners still POST a debug log per line.
When `SEND_RUN_DEBUG_LOGS` is off (default), the route now drops the
request immediately: `skipBodyParsing` skips the body read/parse, a bare
handler returns 204, no wide event. The route stays registered so it
avoids the `No route match` error log; the only per-request log left is
the framework's `logger.debug` trace, suppressed at the default `info`
level. Still counted by request metrics, and 204 is non-retryable so no
retry storm.
Adds a `skipBodyParsing` flag to the internal HTTP server.
Runners were POSTing a debug log to the supervisor for every log line -
one request per line, unbatched and unconditional. The supervisor
already has a `SEND_RUN_DEBUG_LOGS` toggle (off by default) that
discards them on receipt, but the runner fired the request regardless,
so the traffic hit the supervisor either way.
This gates the send at the source. The runner now reads
`TRIGGER_SEND_RUN_DEBUG_LOGS` (off by default, injected by the
supervisor from its existing `SEND_RUN_DEBUG_LOGS` setting) and skips
the POST entirely when disabled. Local log output is unchanged. Dev runs
use a separate path and are unaffected.
## Summary
Adds an environment-scoped HTTP API over the Errors feature, mirroring
the runs API. Task-run failures are grouped by a fingerprint into "error
groups," and this exposes everything you can do with them in the
dashboard:
- `GET /api/v1/errors` lists error groups, with
`filter[taskIdentifier]`, `filter[version]`, `filter[status]`
(`unresolved`/`resolved`/`ignored`), `filter[search]`, a time range, and
cursor pagination.
- `GET /api/v1/errors/{errorId}` retrieves a single group (summary,
lifecycle state, affected versions).
- `POST /api/v1/errors/{errorId}/{resolve,ignore,unresolve}` changes its
state.
- `GET /api/v1/runs?filter[error]={errorId}` lists the runs behind a
group.
Request and response schemas are exported from `@trigger.dev/core/v3` so
the SDK can reuse them, and all endpoints are documented in the API
reference (OpenAPI). `errorId` is the `error_<fingerprint>` friendly id.
## Attribution
State changes record who made them. A plain environment API key has no
user, so `resolvedBy`/`ignoredByUserId` stay null. When the caller uses
an environment JWT obtained by exchanging a personal access token or a
delegated user token at `POST /api/v1/projects/:ref/:env/jwt`, that
exchange now stamps an `act` delegation claim, and the write endpoints
read `act.sub` to attribute the change to the acting user. This is the
first endpoint to consume the `act` claim, so two small pieces of
plumbing ride along: the exchange stamps `act` for personal-access-token
subjects too (it was delegated-token-only), and the public-JWT
bearer-auth path surfaces `act.sub` to the handler.
Built on the delegated-token work in #3997.
## Summary
Adds a short-lived, delegated token (`tr_uat_...`) that authenticates
against the API as a user without handing out a long-lived personal
access token. You mint one from a PAT, optionally narrow it to a set of
scopes, and give it a lifetime; the API then treats requests as that
user, subject to their role.
`trigger.dev mint-token` is the entry point (it uses your stored PAT):
```bash
UAT=$(trigger.dev mint-token --ttl 3600 --cap read:runs)
```
The token works anywhere a PAT does for user-level endpoints, and can be
exchanged for an environment JWT at `POST
/api/v1/projects/:ref/:env/jwt` to reach environment-scoped data (the
same exchange a PAT supports).
## How it works
A user-actor token is a short-lived JWT verified by a new first-class
`authenticateUserActor` method on the RBAC plugin. Self-hosters get a
built-in fallback; role-aware enforcement comes from the plugin.
Effective permissions are the intersection of the user's role and the
token's optional scope cap, so a token is only ever narrower than the
user, never broader.
Minting is restricted to personal access tokens (a token can't mint
another one, and an environment key can't mint one). Tokens default to a
1 hour lifetime (max 365 days). When exchanged for an environment JWT,
the user is stamped on it for attribution and the scope cap is carried
through.
## Summary
Replaces the multi-select popover task type filter on the Tasks page
with a single-select segmented control: **All** plus icon-only
**Agent**, **Standard**, and **Scheduled** segments. Each segment has a
tooltip showing its label and a number-key shortcut (0-3), and the
search field no longer autofocuses so the shortcuts work on page load.
## ✅ Checklist
- [x] I have followed every step in the [contributing
guide](https://github.com/triggerdotdev/trigger.dev/blob/main/CONTRIBUTING.md)
- [x] The PR title follows the convention.
- [x] I ran and tested the code works
## Summary
The Personal Access Tokens page now shows each token's maximum role in a
new column, so you can see at a glance what a token is capped to. The
column only appears when an RBAC plugin is installed, and shows "-" for
tokens with no cap. Its header tooltip reuses the same explanation shown
in the create-token panel.
Pushes new organizations and users into the Attio CRM at signup time,
for Customer Success (TRI-10431).
- Orgs → Attio `workspaces`, users → Attio `users`, keyed on Attio's
built-in unique `workspace_id` / `user_id` so writes are idempotent
upserts.
- Runs on the common Redis worker (not inline), so a slow or unavailable
Attio never blocks the signup path; failures retry (3 attempts).
- Hooks: user-created (alongside the existing Loops call) and
org-created (`createOrganization`).
- Gated behind `ATTIO_API_KEY`, no key means the sync is skipped
entirely, so OSS / self-hosted installs are unaffected.
Only creation is covered here (the record "shell"); spend, runs, plan
changes, churn, and role/relationship linking are populated by the
scheduled full sync, tracked separately.
**Deploy note:** requires an Attio API key set as `ATTIO_API_KEY` in the
webapp env, with scopes **Records (read-write)** + **Object
Configuration (read)**, the assert/upsert endpoint reads object config
to resolve the matching attribute. Without the key the sync no-ops.
---------
Co-authored-by: Matt Aitken <matt@mattaitken.com>
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
## ✅ Checklist
- [x] I have followed every step in the [contributing
guide](https://github.com/triggerdotdev/trigger.dev/blob/main/CONTRIBUTING.md)
- [x] The PR title follows the convention.
- [x] I ran and tested the code works
---
## Testing
Ran the webapp locally with the change applied; it compiles and serves.
The edit only swaps the chart card title string from "LLM spend" to "LLM
spend ($)" on the agent landing page.
---
## Changelog
The agent dashboard "LLM spend" chart label now includes the currency
unit, reading "LLM spend ($)".
---
## Screenshots
_[Screenshots]_
💯
## Summary
Several dashboard routes performed actions a restricted role should not
be able to do (cancel or replay runs, manage prompt versions, invite and
manage members, manage billing) without any permission check. This adds
role-based permission enforcement to those routes, and disables the
matching UI controls (with a tooltip) when the current role lacks
permission.
Covered actions:
- Runs: cancel and replay (single, bulk create, bulk abort)
- Prompts: create or edit override versions, and promote a version to
current
- Members: invite, resend invite, revoke invite
- Billing: change plan, billing alerts, and the customer portal
## How
Each affected route now goes through the `dashboardLoader` /
`dashboardAction` route builders with an `authorization` block declaring
the required permission (or a per-intent check where one route handles
several intents). Existing tenancy and data-scoping queries are
untouched; this only layers permission checks on top. The UI follows
disable-don't-hide: controls stay visible but disabled with a "You don't
have permission to ..." tooltip.
Two reusable pieces support this: `checkPermissions(ability, checks)`
turns a set of checks into a boolean map a loader returns to the client,
and `PermissionButton` / `PermissionLink` disable the underlying control
and show a tooltip when a permission flag is false.
## Behaviour
No change in the default configuration: permissions are permissive, so
every control stays enabled and every route behaves as before. The
checks only take effect when an RBAC plugin is installed. This also
makes role assignment on invite-accept non-fatal, so a failure there
cannot block joining an org.
Verified with `pnpm run typecheck --filter webapp`; `checkPermissions`
has unit tests.
The global feature flags admin page had a few rough edges.
The percentage flags are numeric (`z.coerce.number()`) but rendered as
free-text inputs, so you could type non-numeric values that only failed
validation after submitting - and the error surfaced behind the confirm
dialog. The control-type detection now recognises numbers and renders a
proper number input, with the min/max range as the placeholder so the
type is clear even when the field is unset. The save error also shows
inside the confirm dialog now, not just behind it.
The action buttons were unreachable without zooming out. The admin
layout wrapped each page in a plain block, so `h-full` page content
overran the viewport by the height of the tab bar and got clipped by the
`overflow-hidden` body. Making the layout a flex column bounds each page
to the space below the tabs, so the existing per-page scroll works and
the feature flags page scrolls like the Users/Orgs tabs. Also capped the
confirm dialog's diff list so its footer stays on screen when there are
many changes.
## Summary
Prisma infrastructure failures (P1xxx-class: database unreachable, timed
out, connection dropped, engine init/panic) carry the database hostname
in their `.message`. This captures them centrally for observability and
ensures they never reach API clients verbatim.
## Design
A `$allOperations` client extension on the writer and replica clients
logs infrastructure errors with the originating model and operation,
then rethrows the **original** error unchanged — call sites that branch
on `error.code` (unique-violation idempotency, not-found handling) and
transaction retries keep working. Only infrastructure errors are logged;
routine query/validation errors (P2xxx) are left alone.
`$allOperations` can't see the transaction boundary (`$transaction` is a
client method, not an operation), so infrastructure errors surfacing
from `$transaction()` without a Prisma code — e.g.
`PrismaClientInitializationError` — are logged separately at the
transaction wrapper, where the existing coded-error path would otherwise
miss them.
`clientSafeErrorMessage()` swaps an infrastructure error's message for
`"Internal Server Error"` at the API routes that previously returned
`error.message` raw. Status codes, headers, and every non-infrastructure
message are unchanged.
## Test plan
- [x] P2002 / P2025 rethrow with code intact and are not logged
- [x] Statement errors inside `$transaction` keep their code (retry
logic intact)
- [x] Raw queries wrapped without crashing on the undefined model
- [x] A genuine connectivity failure is logged with model/operation/code
- [x] `clientSafeErrorMessage` obfuscates infra messages, preserves all
others
- [x] `pnpm run typecheck --filter webapp` (12/12)
## Note
Overlaps with #3391 (Prisma 7 migration) on
`apps/webapp/app/db.server.ts` — coordinate rebasing.
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.
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.
## Summary
Typing in the search bar on the task page could clear or reset the input
mid-keystroke. This fixes the re-render race so the field stays stable
while you type.
## Root cause
Two things compounded:
- `SearchInput`'s sync effect depended on `text`, so it re-ran on every
keystroke and could overwrite the input with the URL/controlled value
while focused.
- Each task row unmounted and remounted its activity chart during the
side-panel open/close animation (25 charts at once), forcing heavy
re-renders that the search effect raced against.
## Fix
- `SearchInput` now tracks the last synced value in a ref instead of
comparing against `text`, keeping the effect off the keystroke path. It
only writes to state when the incoming URL/controlled value actually
changes, and never while the input is focused.
- Activity charts are now hidden (`hidden` attribute) instead of
unmounted during the panel animation, so the rows don't churn the tree
and the resize stays smooth.
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
The Models page is now split into two tabs. **Your models** shows the
models your project has actually used in the selected time range, with
usage charts (cost over time, tokens over time, calls by model), a
per-model table of calls / cost / avg TTFC / avg tokens-per-sec, and
calls/tokens trend sparklines. **Model library** is the full catalog,
reordered from alphabetical to a relevance-based provider order
(Anthropic, OpenAI, Google, then the rest), newest models first within
each provider, with a "New" badge on models released in the last 7 days.
One time-range selector drives the whole Your models tab, so the charts,
the table, and the sparklines all share the same window. Opening a model
shows its own metrics with an independent range picker and a "View in AI
metrics" link that opens the AI metrics dashboard filtered to that
model. The active tab is kept in the URL so it survives a refresh and is
shareable.
## Prompt caching & cost accuracy
Both the Your models tab and the AI metrics dashboard now surface
prompt-cache usage: a cache-savings column plus per-model cached-tokens
and cache-hit-rate views, and a caching section on the dashboard (hit
rate, cached tokens, estimated savings, and hit rate by model).
Building this surfaced a cost bug. `input_tokens` is the total prompt
count and already includes cache-read and cache-creation tokens, but the
cost pipeline charged the full input at the input price and then added a
separate cache line, so cached tokens were billed twice (and on
Anthropic, cache reads were never discounted because their price is
keyed differently). The input price now applies only to the non-cached
remainder, with cache prices resolved across the provider-specific keys,
so LLM cost and the cache hit-rate metric are accurate. Hit rate is
computed as cached reads over total input.
## Notes
Also fixes React "invalid DOM property" console warnings from the
provider icons (the Llama and DeepSeek SVGs used raw `fill-rule` /
`clip-rule` / `clip-path` attributes), which this page surfaces by
rendering more provider icons.
## Screenshots
**Your models tab:** usage charts and a per-model table with
calls/tokens trend sparklines.
<img width="2560" height="1267" alt="1-your-models-tab"
src="https://github.com/user-attachments/assets/859bd24f-9047-4828-8bbb-83e5882846d6"
/>
**Model library:** provider-relevance ordering with a "New" badge on
models released in the last 7 days.
<img width="2560" height="1267" alt="2-model-library-tab"
src="https://github.com/user-attachments/assets/46dd54b9-80f9-4922-ade9-5935b08dfebc"
/>
**Model detail, Metrics tab:** per-model range picker and a "View in AI
metrics" link.
<img width="2560" height="1267" alt="3-model-detail-metrics"
src="https://github.com/user-attachments/assets/0f65d9d0-6142-4918-93f0-110bb277101a"
/>
**View in AI metrics:** the dashboard deep-linked and filtered to the
selected model.
<img width="2560" height="1267" alt="4-ai-metrics-filtered"
src="https://github.com/user-attachments/assets/821f256c-e305-493c-98c7-eafaf2f57f83"
/>
## Summary
Reworks the scheduled task page right-hand sidebar.
- Adds **Overview** / **Schedules** tabs. The Schedules tab is a
paginated table of all schedules attached to the task, declarative
first.
- Surfaces schedule fields (ID, CRON + human-readable description,
next/last run, status) directly in the Overview property table.
- Sidebar can be dragged much wider (up to 80% of the viewport).
- "No schedules attached" panel explains declarative vs imperative and
links to docs.
- Schedule **create / edit / enable / disable / delete** all happen
inside the existing Sheet — no more navigating to the standalone
schedule page. Toasts confirm each action.
## Test plan
- Open a scheduled task page and verify the new tabs
- Create, edit, enable/disable, and delete a schedule — confirm you stay
on the page and see a toast each time
- Visit a task with no schedules attached and confirm the info panel
renders
- Drag the sidebar wider; confirm pagination shows when there are >25
schedules
### Problem
Firestarter's `didWarmStart: true` means the response was written to a
long-poll socket — not that the runner received it. A silently dead
poller (no FIN, e.g. a VM torn down mid-poll) leaves the dispatched run
stuck in `PENDING_EXECUTING` until the run engine's heartbeat redrive,
and each redrive burns a queue redelivery toward
`TASK_RUN_DEQUEUED_MAX_RETRIES`.
### Change
After a warm-start hit, the supervisor retains the `DequeuedMessage`
(TimerWheel, default 10s), then probes the existing `getLatestSnapshot`
API. If the run is still on the exact dequeued snapshot, no runner ever
acted — it falls through to the regular cold-create path. Recovery: ~10s
+ cold start, no new APIs, no CLI changes.
- **Double-start safe**: `startRunAttempt` runs under a per-run lock and
409s stale snapshot ids, so a reviving runner and the fallback workload
can't both execute; the loser exits before running anything.
- **Probe errors → do nothing**: healthy runners legitimately act late
during platform brownouts (nested attempt-start retries), so falling
back on uncertainty would stampede duplicates. The heartbeat redrive
stays as the backstop (also covers supervisor restarts dropping timers).
- **Off by default**: `TRIGGER_WARM_START_VERIFY_ENABLED` (+
`TRIGGER_WARM_START_VERIFY_DELAY_MS`, 1–60s, default 10s). Disabled =
complete no-op. Works for all workload managers (compute/k8s/docker)
since it hooks the shared dequeue path.
- Emits `warmstart.verify` wide events (`outcome: delivered | fallback |
probe_error`), making the silent-loss rate directly measurable.
Currently the `db:seed` script just hangs on success.
This PR adds `process.exit(0)` to the finally block after db disconnect
so the script exits properly.
---------
Co-authored-by: Chris Arderne <chris@trigger.dev>
### Summary
Self-serve billing UI is now hidden for managed-billing organizations.
Plan pickers, upgrade actions, billing alerts, and related upgrade
prompts are replaced with a "Contact us" option where appropriate.
Uses the new showSelfServe subscription flag, defaulting to true for
existing self-serve organizations.
### Testing
- [x] billing pages render correctly for self-serve organizations.
- [x] managed-billing organizations no longer see self-serve upgrade
flows.
- [x] "Contact us" actions are shown instead of upgrade actions where
applicable.
### Changelog
Hide self-serve billing flows for managed-billing organizations behind
the new showSelfServe subscription flag.
Major dashboard restructure plus the new task landing pages and
self-serve schedules add-on integration.
## Side menu
- Full restructure: standalone Tasks / Runs / Sessions block at the top;
new collapsible sections for AI, Observability, Deployments, Manage
- Persisted collapse state per section in `dashboardPreferences`
- New / updated icons across the menu
- Dashboards section: built-in Run metrics + AI metrics + custom
dashboards, with drag-to-reorder via ReactGridLayout
(`DashboardList.tsx`)
- DevPresence connection indicator in the env selector (DEV + V2)
## Tasks (`_index` — unified Tasks page)
- Replaces the separated Agents / Standard / Schedules listing pages
with one table
- New `UnifiedTaskListPresenter` composes `TaskListPresenter` +
`AgentListPresenter` (shared `currentWorker` lookup)
- Columns: Type (with kind badge), ID, File, Running (numeric for tasks;
running + suspended pills for agents), Activity (24h stacked-by-status),
sticky menu
- Search + "Task type" multi-select filter (URL-synced)
- Client-side pagination at 25/page
- Right-hand "useful links" panel (cookie-persisted state)
- Live-reload SSE: page revalidates on `WORKER_CREATED` so onboarding
`trigger dev` flips the blank state automatically
## Agent landing page (`/agents/$agentParam`)
- New per-agent detail page
- Top tabs (Sessions / Runs) toggle both the chart panel and the table
- Three dashboard-style chart cards: Sessions/Runs activity, LLM spend,
Tokens
- `AgentDetailPresenter` queries ClickHouse for run activity, session
activity (with FINAL on `sessions_v1`), and LLM cost/token activity from
`llm_metrics_v1`
- TimeFilter at the top drives all three charts
- Sticky table header, resizable horizontal handle, sidebar with Test
agent button + properties
- Docs link → `ai-chat/overview`
## Standard Task landing page (`/tasks/standard/$taskParam`)
- New per-task detail page mirroring the Agent layout
- `TaskDetailPresenter` for activity + properties
- Chart panel wrapped in a Card with "Runs by status" header
- Top bar with title, TimeFilter, pagination
- Right sidebar: Test task + identifier, queue, machine, retry, TTL,
payload schema, etc.
## Scheduled Task landing page (`/tasks/scheduled/$taskParam`)
- New per-task detail page mirroring the Agent / Standard layout
- Top-bar actions (right → left): pagination, Bulk replay…, View all
runs, TimeFilter, Create schedule
- Connected schedules mini-table in the sidebar
- **Self-serve schedules add-on integration** (reincarnated from the
now-removed `/schedules` listing page during the `origin/main` merge):
- Bottom usage bar pinned via `grid-rows-[auto_1fr_auto]` — progress
ring + "X/Y of your schedules" + Purchase / Upgrade / Request CTA
- At-limit "Create schedule" intercept dialog
- `PurchaseSchedulesModal` extracted as a shared component
(`apps/webapp/app/components/schedules/PurchaseSchedulesModal.tsx`)
handling increase / decrease / above-quota / need-to-delete states
- New resource action route at
`/resources/orgs/$organizationSlug/schedules-addon`
## Sessions
- Index page: list, filters, blank state, help tooltip rework
- Detail page: combined input/output chronological view (replaces split
tabs)
- Improved raw-message view layout (full-height)
- AI payload UI: `data-*` parts grouped under "AI SDK data parts:" label
- `toSafeUrl` helper guards rendered URLs from streamed content
- Fix: duplicate assistant content on inspector tab switch
## Playground (Test agent)
- Restructured top menu; back button + agent-selector popover
- Improved blank state
- Recent agent chat history moved into the tabbed menu
- Better message-scroll container (full height)
## Dashboards
- New Dashboards landing page (`/dashboards`) — Run metrics, AI metrics,
Create your own CTAs
- `BuiltInDashboards` updated; new `TasksDashboardPresenter` for the
tasks overview
- Custom dashboards section gains drag-to-reorder; cosmetic fix for
active-row drag-handle blending
## PageHeader / shared primitives
- `PageTitle` gains an `accessory` prop supporting string (auto-wrapped
in tooltip) and ReactNode
- Help tooltips on Tasks, Runs, Sessions PageTitles explaining the
concept and sub-categories
- `Card` primitive used for dashboard-style chart panels throughout
## Code review fixes (last batch on this branch)
- ClickHouse activity queries hardened: `FINAL` + `_is_deleted = 0` on
`task_runs_v2` (ReplacingMergeTree); `organization_id` + `project_id`
filters for sort-key prefix; `inserted_at` partition filter on
`llm_metrics_v1`
- `UnifiedTaskListPresenter`: shared `currentWorker` lookup;
slug-collision guard in `mergeRunningStates`; off-by-one fixed in 24h
bucket alignment
- `ScheduleListPresenter`: halved platform RPCs by deriving limit from
`currentPlan` instead of calling `getLimit`
- Sessions detail: stopped IntersectionObserver / scroll listener
re-attach on every chunk; `requestAnimationFrame` deferral on
auto-scroll to avoid virtualizer race
- URL hardening: `?types=` validated against known kinds; new
`parseFiniteInt` helper applied to `from`/`to`/`page` params
- AgentView: HITL resolution buffer now cleared once parts reach a
terminal state (was an unbounded Map on long sessions); subscription
effect deps documented with eslint suppression
- `PurchaseSchedulesModal`: bundle state resets on each open instead of
persisting stale drafts
## Manual testing
Manual smoke-test plan is tracked under
[TRI-10883](https://linear.app/triggerdotdev/issue/TRI-10883), broken
into 20 sub-issues covering onboarding, self-serve schedules, side menu,
the four landing pages, sessions, runs, dashboards, regressions and
performance.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Two defensive fixes to the native realtime backend's run-change
publishing (behind a feature flag, off by default), so turning it on can
never destabilize the run lifecycle.
**Never throws at the caller.** Publish sites run synchronously on the
run-engine event bus and the metadata flush loop. The internal publish
was already wrapped in try/catch, but lazy construction (singleton +
metrics) and record encoding ran before that guard, so a throw could
propagate into a run lifecycle operation. The public
`publishChangeRecord` / `publishManyChangeRecords` helpers now wrap the
whole call and log-and-drop on failure.
**Bounds outage buffering.** The publisher connection caps
`maxRetriesPerRequest` at 1 (vs ioredis's default of 20), so during a
pub/sub Redis outage a publish rejects after ~1 reconnect cycle instead
of holding commands in memory for ~20s. A dropped publish is
latency-only, since the consumer has a periodic backstop full-resolve.
The offline queue stays on, so the first publish after a process boots
still flushes once the connection is ready.
Two expected, non-failure conditions were being logged at `error` level,
which surfaces them as exceptions in error tracking and adds noise
without signal. This downgrades both to `warn`. The first is the
checkpoint-restore path when a `RESTORE` event already exists for a
checkpoint — a benign idempotency skip on a duplicate or retried event.
The second is the `/api/v1/token` endpoint when the authorization code
is invalid or expired, which is the expected steady state while the CLI
polls the endpoint during login; genuinely unexpected failures there
still log at `error`. No behavior or response changes — the token
endpoint still returns 400 in the same cases.
### Summary
Queue searches previously executed both a count query and a page query
with identical filters. This PR switches filtered searches to `hasMore`
pagination, removing the extra count query while preserving existing
search behavior.
### Testing
cd apps/webapp && pnpm run test ./test/queueListSearch.test.ts --run
passes
### Changelog
Improve filtered queue search performance.
## Summary
Adds observability to the task metadata cache that backs the trigger hot
path. Follow-up to #3930, which made locked-version triggers fall back
to the primary when the read replica returns no row; this makes the
cache's effectiveness (and that fallback) measurable instead of
inferred.
## What it emits
A single bounded counter `task_meta_cache.resolve`, labeled by lookup
path (`locked` / `current`) and the source that satisfied it (`cache` /
`replica` / `writer` / `miss`):
- `cache / total` is the cache hit rate (its inverse is how cold the
cache runs).
- `writer / total` is how often the read replica returned empty for a
row the primary had (the condition #3930 recovers from).
Labels are bounded, with no per-env / worker / slug cardinality.
TRI-10873
Adds a `workload_create_duration_seconds` Prometheus histogram to the
supervisor, observed around the workload manager `create()` call:
- `backend` label: `kubernetes` | `compute` | `docker` — set once from
the configured workload manager
- `outcome` label: `success` | `error` — the per-outcome counts double
as a create error rate
Registered on the supervisor's existing metrics registry, so it's
exposed on the existing `/metrics` endpoint with no config changes.
Notes:
- Covers cold creates only; warm starts and restores return before
reaching `create()`.
- A create may include backend-internal retries, so one observation can
span multiple attempts.
- Fixed low cardinality: 2 active label sets per deployment × 10
buckets.
## Summary
`triggerAndWait` (and other locked-version triggers) could
intermittently fail with `Task '<id>' not found on locked version
'<version>'` for a task that was registered on that version. The
failures came in bursts and recovered on their own, so a retry minutes
later would succeed.
## Root cause
For a locked-version trigger, the queue resolver looks up the task's
`BackgroundWorkerTask` metadata from the read replica (behind a Redis
cache). On a cache miss it queried the replica, and a `null` result was
treated as "task not registered" and turned into a non-retryable 422. A
read replica can return an empty result for a row that already exists on
the primary, so a momentarily-behind replica produced a false negative
even though the locked worker (resolved on the primary in the same
request) clearly had the task.
## Fix
On a cache miss, when the replica returns no row the resolver now
re-checks the primary before concluding the task is missing. If the
primary has the row it is used (and the cache is back-filled); the error
fires only when the primary genuinely lacks it, which is the only case
where the 422 is correct. The extra read happens on the
cache-miss-and-replica-empty path only, so the hot path is unchanged.
Verified with a unit test (replica stub vs. real primary) and end-to-end
against a local streaming replica with replication paused to reproduce
the stale read.
TRI-10868
## Summary
Two read-replica races on the session APIs could break chats whose first
activity lands inside the replication window (or any time the replica
lags):
1. A session's first `.in` append or `.out` subscribe could fail with a
404 for a session that exists on the writer, because the route resolved
the Session row on the replica only.
2. `ensureRunForSession` probed run liveness on the replica, so a probe
miss on a run triggered moments earlier was judged "run is dead" and a
second live run was spawned for the same session. Both runs then
consumed the same input stream, producing duplicated turns and doubled
responses (and doubled LLM cost).
## Fix
Liveness now re-probes the writer before declaring the current run dead
(the old code already fell back to the writer, but only to recover the
friendlyId, after the wrong verdict was made). Session resolution on the
append and subscribe/init routes goes through a new
`resolveSessionWithWriterFallback`, which stays replica-first on the hot
path and only touches the writer on a miss.
Reproduced and verified against a local streaming replica with an
artificial apply delay: pre-fix, a send immediately after session
creation reliably produced either the 404 or two executing runs with a
doubled response; post-fix, the same flow produces exactly one run and
one response.
Also rides along: the local docker replica's default apply delay drops
from 150ms to a realistic 20ms (override via `REPLICA_APPLY_DELAY` when
you want to deliberately widen the race window).
## Problem
The item-streaming endpoint of the two-phase batch API (`POST
/api/v3/batches/:batchId/items`) processed streamed items strictly
sequentially. For a batch of many large payloads, each offloaded to
object storage inline, this serialized N object-store round-trips inside
a single request and could exceed Node's default `server.requestTimeout`
(300s). The webapp then returned `408`, which the SDK reads as `408
terminated` and retries up to 5 times, turning a slow ingest into a
failure that takes tens of minutes to surface.
## Fix
Ingest now runs through `p-map` over the NDJSON async iterable with
bounded concurrency (`STREAMING_BATCH_INGEST_CONCURRENCY`, default 10):
- `p-map` pulls lazily from the stream, so at most `concurrency` items
are read and in-flight at once. Peak memory stays bounded to roughly
`concurrency × STREAMING_BATCH_ITEM_MAXIMUM_SIZE` and request-body
backpressure is preserved.
- Set the env to `1` for fully sequential ingestion (escape hatch).
## Why this is safe (ordering and idempotency unchanged)
- Ordering derives from each item's index (enqueue `timestamp =
batch.createdAt + index`), not enqueue order.
- Dedup is atomic per index in `enqueueBatchItem`.
- The NDJSON parser now stamps oversized-item markers with their emit
position, removing the consumer's sequential `lastIndex` assumption (the
only order-dependent bit).
- The count-check and conditional-seal path is untouched.
## Scope
This speeds up every batch ingested through the streaming endpoint, not
just large-payload batches. Each item does a per-item Redis enqueue
regardless of size, and those now overlap. Large payloads benefit most
because they add an object-store offload round-trip on top of the
enqueue.
## Verification
Added an integration test (`streamBatchItems.test.ts`) that drives the
real service against Postgres + Redis + RunEngine and times a 150-item
batch at increasing concurrency. Object-store offload is modelled as a
fixed per-item latency (local round-trips are too small to compare
meaningfully):
```
runCount=150
large payloads (10ms/item offload):
concurrency=1 1739ms
concurrency=10 192ms (9.1x faster)
concurrency=50 57ms (30.7x faster)
small payloads (Redis enqueue only, no offload):
concurrency=1 90ms
concurrency=10 24ms (3.7x faster)
```
The test asserts correctness at every concurrency (all items accepted,
sealed, enqueued exactly once), that parallel ingest beats the
sequential floor, and that the small-payload case is strictly faster
than sequential, so the win is not specific to large payloads.
Also exercised end-to-end over real HTTP against a local server: a
20-item batch (12MB body) ingests and seals, a re-stream of the sealed
batch returns `sealed: true` with zero re-accepted items (idempotent
retry), and an oversized item still seals at its correct index.
Existing coverage stays green: concurrent ingest of a 100-item batch,
in-flight processing never exceeding the configured concurrency,
concurrent dedup on streaming retry, and emit-position marker indexing.
## Follow-ups (not in this PR)
- SDK pre-offload of large item payloads (send `application/store` refs
instead of raw blobs) to remove object-store work from the request hot
path and shrink the request body.
- Optional `server.requestTimeout` bump as a safety net.
## CI fix
Added `.github/workflows/codeql.yml` to replace GitHub's automatic
("dynamic") CodeQL scanning. The dynamic setup was failing to upload
SARIF results because the auto-generated `GITHUB_TOKEN` lacked the
`security-events: write` permission. The explicit workflow grants that
permission at the job level and pins all actions to commit SHAs,
consistent with the repo's security conventions.
## ✅ Checklist
- [ ] I have followed every step in the [contributing
guide](https://github.com/triggerdotdev/trigger.dev/blob/main/CONTRIBUTING.md)
- [ ] The PR title follows the convention.
- [ ] I ran and tested the code works
---
## Testing
- Integration test (`streamBatchItems.test.ts`) validates correctness
and performance at concurrency 1, 10, and 50 for both large and small
payloads.
- End-to-end verified over real HTTP: 20-item/12MB batch ingests and
seals, idempotent retry returns `sealed: true`, oversized item seals at
correct index.
---
## Changelog
Streaming batch ingest now processes items with bounded concurrency
instead of one at a time, so batches of many large payloads ingest far
faster and no longer time out. Concurrency is configurable via
`STREAMING_BATCH_INGEST_CONCURRENCY` (default 10); set it to 1 for fully
sequential ingestion.
---
## Screenshots
_[Screenshots]_
💯
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
## Summary
When the realtime runs feed (the backend behind the `realtimeBackend`
feature flag) hydrates a change from a Postgres read replica, the read
can race the replica's apply of the very write that triggered it. The
delivered row then carries the previous change's content, and an
isolated final change (for example a last `metadata.set` before a run
goes quiet) is not corrected until the roughly 20 second backstop poll.
Measured against a replica with deliberate apply delay, every delivery
trailed exactly one change behind and a final change stranded for the
full backstop interval.
## Fix
Publishers stamp each change record with the committed row's
`updatedAt`, taken from writes they already perform, so the stamp costs
no extra queries. The router delays its wake hydrate until the replica's
measured lag has passed, anchored to that timestamp: a record that has
already spent longer than the lag in transit is hydrated immediately, so
only the racing leading edge ever waits. After hydrating, a tripwire
compares each row against its record's watermark. Still-stale rows are
withheld and retried briefly, and each detection feeds the lag estimate.
If retries run out, the rows are delivered anyway (liveness over
freshness) and follow-up re-hydrates emit the fresh version through the
normal working-set diff once the replica catches up, with the backstop
as the terminal net.
Replica lag is sampled reader-side only, and only while feeds are
active. Aurora reports live lag via `aurora_replica_status()`; vanilla
Postgres can only report "caught up or not" (mid-apply lag is not
honestly measurable from a replica), so tripwire observations floor the
estimate there. Deployments without a replica resolve to zero lag and
skip the gate entirely. Tunables live under
`REALTIME_BACKEND_NATIVE_REPLICA_LAG_*`, and
`realtime_native.stale_hydrates` plus
`realtime_native.replica_lag_estimate_ms` make replica health
observable.
Two adjacent fixes: a metadata update that writes nothing no longer
publishes a change record, and buffered parent and root metadata
operations now publish when the flusher writes them, so those changes
wake live feeds instead of waiting for the backstop.
For local testing, `docker-compose` gains an opt-in `database-replica`
service (compose profile `replica`) with a configurable
`recovery_min_apply_delay`, which reproduces replica-lag behavior
deterministically. With the gate disabled this rig reproduces the
one-change-behind delivery exactly; with it enabled, deliveries arrive
with current content at roughly the true replica lag, across write rates
faster and slower than the lag itself.
## Summary
The environment variables page loaded every variable value in the
project, unfiltered by environment. Archiving a preview branch does not
delete its environment variable value rows, so projects that churn
preview branches accumulate values forever, and every page view loaded
all of them. On large projects this made the page loader take many
seconds and stalled the server while deserializing the oversized result.
## Fix
The presenter now loads the displayed environments first and filters the
`values` relation to those environment IDs. That matches the display
semantics exactly (per-user dev environments and active branch
environments included), and the lookup is covered by the existing unique
index on `(variableId, environmentId)`. Values in archived branch
environments are no longer fetched at all.
Covered by a new testcontainers test asserting that values from active
environments (including branch environments) are returned while archived
branch environments are excluded.
## Summary
`test/runsRepositoryCursor.test.ts` pinned its fixture runs to
`createdAt = 2026-06-04T16:55:07Z`. `listRuns` applies the default 7 day
window when no time filter is given, so the fixtures aged out of the
window at 16:55 UTC on 2026-06-11 and all five tests started failing for
every branch, regardless of what the branch changed. The tests were
green on their own CI two days earlier because the fixtures were only
five days old at the time.
This switches the fixture base to a relative timestamp (one hour ago),
so the fixtures stay inside the default window permanently. Verified the
suite goes 5/5 green with this change on the same environment where the
pinned dates fail 5/5.
## Summary
The run trace page loader serialized every span's raw OTel events (with
full properties) into the response, even though the tree UI only renders
the derived `timelineEvents` and the span detail panel refetches what it
needs. On event-heavy traces that inflated both the loader payload and
the server-side heap copies built per request. This PR keeps raw span
events server-side and pairs that with a few related trace-view
improvements:
- A new optional `TRACE_VIEW_EMERGENCY_SPAN_CAP` env var (unset by
default) clamps the trace summary and detailed trace summary span limits
on both event store paths, including the public run trace endpoint, so
operators can bound trace query sizes in one place without retuning the
per-store limits.
- The TreeView virtualizer resolved every rendered row with a linear
scan over the whole tree (and `getNodeProps` did the same via
`findIndex`); rows now resolve through memoized id lookup maps, which
matters once traces reach tens of thousands of spans.
- The run stream SSE lookup now applies the same organization membership
scoping as the rest of the run page presenters, for consistency.
Behavior is unchanged by default: the trace tree renders from the same
`timelineEvents` it always has, and the new cap only takes effect when
set.
## Summary
HIPAA BAA is offered as a paid add-on on every paid plan. Each paid tier
on the in-app pricing card now has a "HIPAA BAA add-on" row with a
"Request a BAA" link that opens the existing contact dialog pre-filled
with a new `hipaa` inquiry type, prompting the user for their company
name and a brief description of the PHI workload.
The contact form's `feedbackTypes` are restructured to match the
marketing /contact form: every inquiry type carries a Plain label ID and
a "Contact form: ..." thread title, so threads land in Plain identically
whether they come from the dashboard or the marketing site. The
included-compute line on each tier also picks up the credits wording
from the marketing pricing page, and the Enterprise tier lifts its title
above the features row.
The compute suspend flow delays snapshots by `snapshotDelayMs` (~30s) so
short-lived waitpoints skip the snapshot entirely, with the intent that
a run continuing before the delay expires cancels the pending snapshot.
But the only `cancel()` call site was the `/continue` action, which
runners only invoke when restoring from an already-taken snapshot — so
pending snapshots were never cancelled (zero `snapshot.canceled` events
ever emitted in prod). When a run resumed and completed inside the
window, the stale snapshot fired ~30s later anyway, pausing the VM 6–13s
mid warm-start long-poll; the frozen guest couldn't fire its abort timer
or send a FIN, causing stalls and run-engine driven retries.
### Change
- Cancel the pending snapshot on `attempt.complete` — after the platform
accepts the completion, before the HTTP reply (so it can't reorder with
the runner's next `/suspend`).
- Cancel on `runDisconnected` (crash, exit, or run replaced on the
socket).
- Both cancels are guarded by a runnerId match (new
`TimerWheel.peek()`): a stale duplicate runner for a reassigned run must
not cancel the fresh runner's pending snapshot. A missing runnerId falls
through to an unconditional cancel (the pre-existing `/continue`
behavior is unchanged).
Waitpoint suspensions keep the runner socket connected and the attempt
incomplete, so neither hook touches a snapshot that is still wanted.
Known limitation (fail-safe direction): `socket.data.runnerId` is frozen
at the websocket handshake, so after a same-supervisor restore the
disconnect-path guard refuses the cancel. The `attempt.complete` path
uses the runner's current header id and is unaffected.
`ComputeWorkloadManager.create` swallows gateway errors currently, so a
cold start that fails placement (e.g. a netns slot with a busy tap, a
full node disk) silently abandons the dequeued run until the run
engine's `PENDING_EXECUTING` heartbeat timeout redrives it via stall
detection.
### Changes
- Retry `instances.create` with short backoff (default 3 attempts, 250ms
backoff), recording `createAttempts` in the wide event.
- **Only statuses where the create definitely did not commit are
retried**: 500 (agent/fcrun create failed) and 503 (no placement).
502/504 are excluded — the gateway emits those when it fails to reach
the node or read its response, which can happen *after* the agent
committed the create; the gateway only records the instance name on a
clean 201, so a same-name retry would miss the collision check and could
double-create the VM on another node. Network-level fetch failures are
retried (if the gateway processed the create, its name index is
populated and the retry 409s harmlessly). Timeouts are not retried.
- **Retry attempts after a 5xx use a deterministic `-rN` name suffix**:
a failed create can leave its name registered until async cleanup runs.
Attempt 1 keeps the unsuffixed name.
Fixes an intermittent `Test timed out in 30000ms` in the
`streamBatchItems` suite. Not a logic hang — the 30s budget covers
container setup, and each case boots its own per-test Redis container +
a full `RunEngine`, so under CI Docker contention a cold boot can cross
30s (which is why the failure moved between tests).
- New `containerTestWithIsolatedRedisNoClickhouse` fixture (Postgres
clone + per-test Redis, no ClickHouse) — this suite never uses
ClickHouse, but the old fixture's auto `resetClickhouse` forced a
ClickHouse boot + migration onto the cold-start test.
- Raised `testTimeout` 30s → 120s, matching the run-engine convention
for this footprint.
## Summary
Reliability and authorization fixes for realtime chat sessions:
- Session-stream waitpoint delivery is scoped to the environment, so two
environments using the same session `externalId` can no longer complete
each other's waitpoints.
- The session snapshot-url routes now enforce per-session authorization,
and appending to a session's `out` channel requires secret-key auth, so
a session-scoped token can't read another session's snapshot or forge
assistant output.
- Appends that carry an `X-Part-Id` header are deduplicated on retry, so
a retried send can't duplicate a message.
- Session creation rejects expired sessions (instead of triggering a run
that can never receive input), `externalId` is immutable after creation,
and the sessions list endpoint returns friendly `run_*` ids to match the
single-session routes.
## Rollout
The waitpoint cache key gains an environment prefix. To keep waitpoints
registered by the previous deploy working across the boundary, the drain
reads both the new and the previous key for this release; the legacy
read can be removed a release later once no pre-deploy waitpoints
remain.
## Summary
Adds a second backend for the realtime runs feed (`useRealtimeRun`,
`subscribeToRunsWithTag`, `subscribeToBatch`), built to stay healthy
when a single busy environment has many subscribers watching many runs
at once. It is gated behind a feature flag with the existing backend as
the default, so nothing changes for users until it is enabled per
environment.
## Design
A run change is published once, as a small self-describing record, to a
single per-environment channel. Every feed is then a predicate over that
one stream rather than owning a channel:
- A per-instance router indexes the currently-held feeds by run, tag,
and batch. When a run changes it hydrates the affected rows once and
serializes them once, then fans the result to every matching feed. One
hot shared tag watched by many subscribers costs a single database query
and serialize, not one per subscriber.
- Feeds that don't match a change are never woken, wake delivery per
environment is coalesced on a leading edge (250ms default) so a burst of
changes costs one wake, and cold reads coalesce onto a single
short-TTL-cached resolve.
- An admission gate bounds how many cold ClickHouse resolves run
concurrently, so a mass reconnect across many distinct filters queues
instead of stampeding the database.
- Changes that land while a client is between long-polls are delivered
on its next poll instead of waiting for the periodic backstop: each
environment buffers its recent change records, subscriptions linger
briefly after the last feed closes, and a newly-armed poll replays
exactly the connection's gap.
- The per-connection replay cursors behind that are shared across
instances via Redis (a single timestamp each), so a poll landing on a
different instance behind the load balancer still reads the connection's
true gap instead of falling back to a cold resolve. Cursor reads have a
bounded deadline and degrade to the cold-read path on any Redis trouble.
- Tag subscriptions with multiple tags match runs carrying all of the
tags, mirroring the existing backend's filter semantics, and live
long-polls hold for about 20 seconds to match its cadence.
- The per-environment channel supports Redis Cluster sharded pub/sub, so
the wake path scales horizontally across shards by environment.
- The backend reports its health through OpenTelemetry metrics (delivery
lag, poll resolution paths, backstop outcomes, replay and cursor-store
activity), with a provisioned Grafana dashboard for local development.
Everything is behind the feature flag and tunable via env vars; the
existing backend remains the default.
## Summary
When `RUN_ENGINE_READ_REPLICA_SNAPSHOTS_SINCE_ENABLED` is on,
`RunEngine.getSnapshotsSince` reads from the read replica. During write
spikes the replica can briefly lag, so the snapshot id a runner just
learned from the writer isn't visible there yet: the lookup threw, the
worker route returned a 500, and the runner waited for its next poll —
turning sub-second snapshot notifications into poll-interval latency
exactly when things are busiest. This PR makes the flag safe to enable:
a replica miss of the since snapshot gets one jittered retry on the
replica (most lag windows are shorter than the ~50–200ms wait, so the
writer is never touched), then falls back to the primary, observed via a
new `run_engine.snapshots_since.replica_miss` counter with an `outcome`
attribute (`replica_retry` vs `primary`). Only genuine misses — absent
on the primary too — remain errors.
## Design
- `getExecutionSnapshotsSince` now throws a typed
`ExecutionSnapshotNotFoundError` so the engine can distinguish the
expected lag miss from real failures. The message string is unchanged
and the error never leaves the engine.
- The recovery path only engages when the flag is on, a distinct replica
client is configured, and no transaction client was passed. With the
flag off, the path is behaviorally identical to before.
- Retry delay bounds are configurable
(`RUN_ENGINE_SNAPSHOTS_SINCE_REPLICA_RETRY_MIN_MS`/`MAX_MS`, default
50/200; `MAX_MS=0` skips the replica retry and goes straight to the
primary).
- The warn log fires only when the primary serves the read (the writer
spill is the operationally interesting event); replica-retry recoveries
are counted but quiet. A permanently-missing snapshot id stays an
error-level failure with a `failedDuring` field, so lag metrics aren't
polluted by bogus ids.
- Stale-tail lag (replica has the since snapshot but not newer rows)
deliberately still returns the replica's view; the next poll catches up.
- The since-snapshot anchor lookup is now scoped to the polled run
(`where: { id, runId }`), so a snapshot id from a different run raises
not-found instead of silently anchoring a too-wide window of the run's
snapshots.
## Test plan
All vitest + testcontainers, no mocks. A new `schemaOnlyPrisma` fixture
(migrated-but-empty clone database) simulates a replica that hasn't
caught up, and a real in-memory OTel meter pins the counter semantics
per outcome.
- [x] Replica catches up during the jittered retry window → served by
the replica, `outcome=replica_retry` = 1, primary never consulted
- [x] Replica permanently missing the since snapshot → served by the
primary, `outcome=primary` = 1
- [x] Snapshot missing on both replica and primary → null, counter = 0
- [x] Replica has the since snapshot but lags by one → the replica's
view is served, no fallback (verified discriminating power: the test
fails if reads secretly hit the primary)
- [x] Flag off with a replica configured → primary serves the read
- [x] Transaction client provided → bypasses the replica entirely
- [x] Since snapshot belonging to a different run → null
- [x] Existing getSnapshotsSince + waitpoints suites green; run-engine,
testcontainers, and webapp typechecks pass
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
## Summary
Adds `GET /api/v1/projects/{projectRef}/environments` (personal access
token auth), which lists the base environments a user can access for a
project — their own dev environment plus the project's staging, preview,
and production environments.
## Details
- Built on the PAT route builder, so it inherits org-membership auth and
the per-resource ability check.
- `dev` is scoped to the token owner; archived environments are
excluded.
- Returns the branchable **parent** preview environment — preview branch
children are not included. A consumer targets the parent; branch-level
overrides are handled separately.
- Sorted to match the dashboard's environment switcher (dev → staging →
preview → prod), and never returns API keys.
Example response:
```json
[
{ "id": "...", "slug": "dev", "type": "DEVELOPMENT", "isBranchableEnvironment": false, "branchName": null, "paused": false },
{ "id": "...", "slug": "stg", "type": "STAGING", "isBranchableEnvironment": false, "branchName": null, "paused": false },
{ "id": "...", "slug": "preview", "type": "PREVIEW", "isBranchableEnvironment": true, "branchName": null, "paused": false },
{ "id": "...", "slug": "prod", "type": "PRODUCTION", "isBranchableEnvironment": false, "branchName": null, "paused": false }
]
```
## Summary
The dashboard's Agent view rendered `source-url` and `file` message
parts by putting their `url` straight into an `href`/`src`. Those URLs
come from streamed agent and tool data, so a tool that emitted something
like `javascript:alert(1)` produced a clickable XSS payload in the
dashboard.
## Fix
A `toSafeUrl` helper now gates every URL before it reaches an
`href`/`src`: it allows only `http:`/`https:`/`blob:` (and
`data:image/...` for inline images) and returns `null` for anything
else. Unsafe values render as plain text instead of a link or image, so
a hostile or malformed URL degrades gracefully rather than becoming
clickable. Safe URLs render exactly as before. Covered by a unit test
over the allow/deny list.
Daniel Sutton