## Summary
The webapp Docker image build runs `pnpm run build --filter=webapp...`,
which builds `@trigger.dev/sdk` as a dependency. The SDK's `build`
script recently gained a `bundle-docs` step (`tsx
../../scripts/bundleSdkDocs.ts`), but the build couldn't run it in the
pruned image, breaking the image build.
Two things were missing:
- `docker/Dockerfile` copied `scripts/updateVersion.ts` into the builder
stage but not `scripts/bundleSdkDocs.ts`, so the step failed with
`ERR_MODULE_NOT_FOUND`.
- Even with the script present, the repo-level `docs/` tree it reads is
a separate workspace package that isn't in webapp's dependency graph, so
`turbo prune --scope=webapp` excludes it — the script's missing-docs
guard would then fail the build.
## Design
The Dockerfile now copies `bundleSdkDocs.ts` alongside
`updateVersion.ts`. `bundleSdkDocs.ts` skips gracefully when the repo
`docs/` tree is absent, which is exactly the pruned-dependency-build
case (the SDK is compiled there but never published). Publishing always
runs from the full monorepo where `docs/` exists, so the missing-docs
guard still protects releases — it only fires when `docs/` is present
but a cited doc is genuinely missing, rather than when the whole tree
was pruned away. This avoids dragging 27M of docs into a throwaway
builder stage.
## Test plan
- [x] `bundle-docs` from the full monorepo still bundles all cited docs
(exit 0)
- [x] Simulated pruned tree without `docs/` skips cleanly instead of
failing
- [ ] Webapp Docker image build succeeds in CI
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
Two read-replica races on the session APIs could break chats whose first
activity lands inside the replication window (or any time the replica
lags):
1. A session's first `.in` append or `.out` subscribe could fail with a
404 for a session that exists on the writer, because the route resolved
the Session row on the replica only.
2. `ensureRunForSession` probed run liveness on the replica, so a probe
miss on a run triggered moments earlier was judged "run is dead" and a
second live run was spawned for the same session. Both runs then
consumed the same input stream, producing duplicated turns and doubled
responses (and doubled LLM cost).
## Fix
Liveness now re-probes the writer before declaring the current run dead
(the old code already fell back to the writer, but only to recover the
friendlyId, after the wrong verdict was made). Session resolution on the
append and subscribe/init routes goes through a new
`resolveSessionWithWriterFallback`, which stays replica-first on the hot
path and only touches the writer on a miss.
Reproduced and verified against a local streaming replica with an
artificial apply delay: pre-fix, a send immediately after session
creation reliably produced either the 404 or two executing runs with a
doubled response; post-fix, the same flow produces exactly one run and
one response.
Also rides along: the local docker replica's default apply delay drops
from 150ms to a realistic 20ms (override via `REPLICA_APPLY_DELAY` when
you want to deliberately widen the race window).
## Summary
When the realtime runs feed (the backend behind the `realtimeBackend`
feature flag) hydrates a change from a Postgres read replica, the read
can race the replica's apply of the very write that triggered it. The
delivered row then carries the previous change's content, and an
isolated final change (for example a last `metadata.set` before a run
goes quiet) is not corrected until the roughly 20 second backstop poll.
Measured against a replica with deliberate apply delay, every delivery
trailed exactly one change behind and a final change stranded for the
full backstop interval.
## Fix
Publishers stamp each change record with the committed row's
`updatedAt`, taken from writes they already perform, so the stamp costs
no extra queries. The router delays its wake hydrate until the replica's
measured lag has passed, anchored to that timestamp: a record that has
already spent longer than the lag in transit is hydrated immediately, so
only the racing leading edge ever waits. After hydrating, a tripwire
compares each row against its record's watermark. Still-stale rows are
withheld and retried briefly, and each detection feeds the lag estimate.
If retries run out, the rows are delivered anyway (liveness over
freshness) and follow-up re-hydrates emit the fresh version through the
normal working-set diff once the replica catches up, with the backstop
as the terminal net.
Replica lag is sampled reader-side only, and only while feeds are
active. Aurora reports live lag via `aurora_replica_status()`; vanilla
Postgres can only report "caught up or not" (mid-apply lag is not
honestly measurable from a replica), so tripwire observations floor the
estimate there. Deployments without a replica resolve to zero lag and
skip the gate entirely. Tunables live under
`REALTIME_BACKEND_NATIVE_REPLICA_LAG_*`, and
`realtime_native.stale_hydrates` plus
`realtime_native.replica_lag_estimate_ms` make replica health
observable.
Two adjacent fixes: a metadata update that writes nothing no longer
publishes a change record, and buffered parent and root metadata
operations now publish when the flusher writes them, so those changes
wake live feeds instead of waiting for the backstop.
For local testing, `docker-compose` gains an opt-in `database-replica`
service (compose profile `replica`) with a configurable
`recovery_min_apply_delay`, which reproduces replica-lag behavior
deterministically. With the gate disabled this rig reproduces the
one-change-behind delivery exactly; with it enabled, deliveries arrive
with current content at roughly the true replica lag, across write rates
faster and slower than the lag itself.
## Summary
Adds a second backend for the realtime runs feed (`useRealtimeRun`,
`subscribeToRunsWithTag`, `subscribeToBatch`), built to stay healthy
when a single busy environment has many subscribers watching many runs
at once. It is gated behind a feature flag with the existing backend as
the default, so nothing changes for users until it is enabled per
environment.
## Design
A run change is published once, as a small self-describing record, to a
single per-environment channel. Every feed is then a predicate over that
one stream rather than owning a channel:
- A per-instance router indexes the currently-held feeds by run, tag,
and batch. When a run changes it hydrates the affected rows once and
serializes them once, then fans the result to every matching feed. One
hot shared tag watched by many subscribers costs a single database query
and serialize, not one per subscriber.
- Feeds that don't match a change are never woken, wake delivery per
environment is coalesced on a leading edge (250ms default) so a burst of
changes costs one wake, and cold reads coalesce onto a single
short-TTL-cached resolve.
- An admission gate bounds how many cold ClickHouse resolves run
concurrently, so a mass reconnect across many distinct filters queues
instead of stampeding the database.
- Changes that land while a client is between long-polls are delivered
on its next poll instead of waiting for the periodic backstop: each
environment buffers its recent change records, subscriptions linger
briefly after the last feed closes, and a newly-armed poll replays
exactly the connection's gap.
- The per-connection replay cursors behind that are shared across
instances via Redis (a single timestamp each), so a poll landing on a
different instance behind the load balancer still reads the connection's
true gap instead of falling back to a cold resolve. Cursor reads have a
bounded deadline and degrade to the cold-read path on any Redis trouble.
- Tag subscriptions with multiple tags match runs carrying all of the
tags, mirroring the existing backend's filter semantics, and live
long-polls hold for about 20 seconds to match its cadence.
- The per-environment channel supports Redis Cluster sharded pub/sub, so
the wake path scales horizontally across shards by environment.
- The backend reports its health through OpenTelemetry metrics (delivery
lag, poll resolution paths, backstop outcomes, replay and cursor-store
activity), with a provisioned Grafana dashboard for local development.
Everything is behind the feature flag and tunable via env vars; the
existing backend remains the default.
Two small hygiene tweaks to **dev-only** images:
- `docker/Dockerfile.postgres`: add `--no-install-recommends` to the
partman install (leaner image, skips unneeded recommended packages).
- `internal-packages/clickhouse/Dockerfile`: run the migration helper as
a non-root user.
Both are local-dev images (the `pnpm run docker` stack) - no impact on
the published webapp image, prod, or self-hosting.
Hardens the webapp Docker image and adds a CVE scan of each published
image.
- Base image `bullseye-slim` → `bookworm-slim` (Debian 12), pinned by
digest. Adds `apt-get upgrade` + `--no-install-recommends` + apt-cache
cleanup across the build stages so OS packages are patched at build
time.
- Moves the `react-email` CLI to `devDependencies` in
`internal-packages/emails` — only the `email dev` preview script uses
it; the runtime render path is `@react-email/render` +
`@react-email/components`. This also drops the bundled `esbuild` binary
from the production image.
- Bumps `goose` v3.26.0 → v3.27.1 and its Go builder image 1.23 → 1.26.
- Adds a reusable Trivy image-scan workflow wired into `publish.yml`, so
every published image (main builds and releases) is scanned for
OS-package CVEs right after it's pushed to GHCR. Report-only (writes to
the run summary), runs alongside the worker publishes so it never blocks
a deploy.
Verified locally: the image builds clean on the new base, and
`@react-email/render` carries no `esbuild` dependency so email rendering
is unaffected.
## Summary
Two papercuts new contributors hit running this repo locally:
1. Fresh clones default to v1 (Redis-only) realtime streams, so Sessions
and `chat.agent` error with `"S2 configuration is missing"`, even though
the `s2` service is already in `docker/docker-compose.yml` and pre-seeds
a `trigger-local` basin. Wire `REALTIME_STREAMS_S2_*` to it in
`.env.example` so the new-contributor flow just works. (Also drop the s2
healthcheck: the image is distroless, so the `wget` check always reports
unhealthy.)
2. Two clones can't both run `pnpm run docker` because ports, project
name, and container names are all hardcoded. Parameterize every host
port as `${VAR:-default}`, drive the project name via
`COMPOSE_PROJECT_NAME` (with a top-level `name:` field as the default),
prefix container names with `${CONTAINER_PREFIX:-}`, and pass
`--env-file .env` so compose reads the same root `.env` the webapp does.
The "Running multiple instances side by side" block in `.env.example`
lists every overridable knob.
Also split the optional services (`electric-shard-1`, `ch-ui`,
`toxiproxy`, `nginx-h2`, `otel-collector`, `prometheus`, `grafana`) into
`docker-compose.extras.yml` behind a new `pnpm run docker:full` script.
The core stack keeps everything the webapp actually needs to boot:
postgres, redis, electric, minio, clickhouse + migrator, s2-lite.
Defaults match every previous hardcoded value, so existing setups keep
working without touching `.env`.
## Test plan
- [x] `pnpm run docker` on a clean clone brings up the core services on
the standard ports under the `triggerdotdev-docker` project name.
- [x] Setting `COMPOSE_PROJECT_NAME=triggerdotdev-docker-alt` + the
`*_HOST_PORT` overrides in `.env` brings up a second stack alongside the
default one with no port or container-name clashes.
- [x] Webapp boots cleanly against the default `.env.example` values;
`/healthcheck` returns 200, no S2 errors.
- [x] s2-lite basin `trigger-local` accepts an append + read via the
same REST endpoints the webapp uses.
- [x] `pnpm run docker:full` brings up the optional services alongside
the core ones in the same project.
## Summary
Local ClickHouse was burning ~325% CPU endlessly merging its own
telemetry tables (`metric_log`, `asynchronous_metric_log`, `part_log`,
`trace_log`) after the container had been running long enough to
accumulate hundreds of GB of system-log data. OrbStack Helper reflected
this on the host (~400% CPU).
These tables are not used by anything in the dev stack. They only exist
for ClickHouse to log itself, so disabling them eliminates the merge
churn entirely.
## Changes
- Adds `docker/config/clickhouse-disable-system-logs.xml`, mounted into
`/etc/clickhouse-server/config.d/`, that removes the noisy system log
tables via `<table remove="1"/>`.
- Mounts the override file in `docker/docker-compose.yml`.
After applying, idle CPU dropped from 325% to ~12% on my machine.
## Test plan
- [ ] `pnpm run docker` brings up the stack cleanly
- [ ] `docker stats clickhouse` shows low idle CPU
- [ ] App functionality unaffected (system log tables are not queried by
the webapp)
- Tags webapp images by full commit SHA on `main` pushes
(`ghcr.io/triggerdotdev/trigger.dev:<sha>`) so any commit can be
resolved to a digest easily.
- Adds OCI labels (`source`, `revision`, `version`, `created`) so
`docker inspect`, vulnerability scanners, and
registry browsers see source/commit/version directly.
- Signs each pushed digest with SLSA build provenance via
`actions/attest-build-provenance@v4.1.0` (pinned by SHA), enabling `gh
attestation verify oci://...` against the source commit and workflow.
This allows seamless migration to different object storage.
Existing runs that have offloaded payloads/outputs will continue to use
the default object store (configured using `OBJECT_STORE_*` env vars).
You can add additional stores by setting new env vars:
- `OBJECT_STORE_DEFAULT_PROTOCOL` this determines where new run large
payloads will get stored.
- If you set that you need to set new env vars for that protocol.
Example:
```
OBJECT_STORE_DEFAULT_PROTOCOL=“s3"
OBJECT_STORE_S3_BASE_URL=https://s3.us-east-1.amazonaws.com
OBJECT_STORE_S3_ACCESS_KEY_ID=<val>
OBJECT_STORE_S3_SECRET_ACCESS_KEY=<val>
OBJECT_STORE_S3_REGION=us-east-1
OBJECT_STORE_S3_SERVICE=s3
```
---------
Co-authored-by: nicktrn <55853254+nicktrn@users.noreply.github.com>
Input streams enable sending typed data to executing tasks from external
callers — backends, frontends, or other tasks. This unlocks interactive
use cases like approval UIs, cancel buttons, chat interfaces, and
human-in-the-loop AI workflows where the task needs to receive data
while running.
Three consumption patterns inside a task:
* `.wait()` — Suspend the task until data arrives (process freed, most
efficient)
* `.once()` — Wait for the next message (process stays alive)
* `.on()` — Subscribe to a continuous stream of messages
One send pattern from outside:
* `.send(runId, data)` — Send typed data to a specific run's input
stream
## User-facing API
### Define a typed input stream
```ts
import { streams, task } from "@trigger.dev/sdk";
const approval = streams.input<{ approved: boolean; reviewer: string }>({ id: "approval" });
```
### Consume inside a task
```ts
export const myTask = task({
id: "my-task",
run: async () => {
// Pattern 1: Suspend until data arrives (most efficient — frees the process)
const result = await approval.wait({ timeout: "5m" });
// Pattern 2: Wait for next message (process stays alive)
const data = await approval.once().unwrap();
// Pattern 3: Subscribe to multiple messages
approval.on((data) => { /* handle each message */ });
},
});
```
### Send from outside
```ts
// From a backend (using secret API key)
await approval.send(runId, { approved: true, reviewer: "alice" });
// From a frontend (using public JWT token from trigger response)
const { send } = useInputStreamSend("approval", runId, { accessToken });
send({ approved: true, reviewer: "alice" });
```
---------
Co-authored-by: Claude <noreply@anthropic.com>
Adds support for skipping Postgres migrations on container startup via
the new `SKIP_POSTGRES_MIGRATIONS` environment variable.
Set `SKIP_POSTGRES_MIGRATIONS=1` to skip migrations, matching the
existing behavior of `SKIP_CLICKHOUSE_MIGRATIONS`.
## Summary
- Upgrades Node.js from 20.19.0 to 20.20.0 (and 22.12.0 to 22.22.0 for
supervisor) to address the async_hooks stack overflow DoS vulnerability
- Adds `maxDepth` parameter (default 128) to `flattenAttributes` and
`unflattenAttributes` to prevent stack overflow on maliciously deep
nested structures
## Details
The vulnerability (patched in Node.js 20.20.0, 22.22.0, 24.13.0, 25.3.0)
causes unrecoverable crashes (exit code 7) when stack overflow occurs
during async_hooks callbacks. Since the webapp uses `AsyncLocalStorage`,
it was theoretically vulnerable.
### Changes
**Node.js version updates:**
- `docker/Dockerfile`: 20.11.1 → 20.20.0
- `apps/supervisor/Containerfile`: 22-alpine → 22.22.0-alpine
- `.nvmrc`: 20.19.0 → 20.20.0
- `apps/supervisor/.nvmrc`: 22.12.0 → 22.22.0
- `references/prisma-7/.nvmrc`: 20.19.0 → 20.20.0
- All GitHub workflows: 20.19.0 → 20.20.0
**Defense in depth:**
- Added `maxDepth` parameter to `flattenAttributes()` and
`unflattenAttributes()` in `packages/core` to prevent stack overflow on
deeply nested user input
## Test plan
- [x] All existing `flattenAttributes` tests pass (50 tests)
- [x] New tests for depth limiting added
- [x] Verify Docker builds work with new base images
New batch trigger system with larger payloads, streaming ingestion,
larger batch sizes, and a fair processing system.
This PR introduces a new `FairQueue` abstraction inspired by our own
`RunQueue` that enables multi-tenant fair queueing with concurrency
limits. The new `BatchQueue` is built on top of the `FairQueue`, and
handles processing Batch triggers in a fair manner with per-environment
concurrency limits defined per-org. Additionally, there is a global
concurrency limit to prevent the BatchQueue system from creating too
many runs too quickly, which can cause downstream issues.
For this new BatchQueue system we have a completely new batch trigger
creation and ingestion system. Previously this was a single endpoint
with a single JSON body that defined details about the batch as well as
all the items in the batch.
We're introducing a two-phase batch trigger ingestion system. In the
first phase, the BatchTaskRun record is created (and possibly rate
limited). The second phase is another endpoint that accepts an NDJSON
body with each line being a single item/run with payload and options.
At ingestion time all items are added to a queue, in order, and then
processed by the BatchQueue system.
## New batch trigger rate limits
This PR implements a new batch trigger specific rate limit, configured
on the `Organization.batchRateLimitConfig` column, and defaults using
these environment variables:
- `BATCH_RATE_LIMIT_REFILL_RATE` defaults to 10
- `BATCH_RATE_LIMIT_REFILL_INTERVAL` the duration interval, defaults to
`"10s"`
- `BATCH_RATE_LIMIT_MAX` defaults to 1200
This rate limiter is scoped to the environment ID and controls how many
runs can be submitted via batch triggers per interval. The SDK handles
the retrying side.
## Batch queue concurrency limits
The new column `Organization.batchQueueConcurrencyConfig` now defines an
org specific `processingConcurrency` value, with a backup of the env var
`BATCH_CONCURRENCY_LIMIT_DEFAULT` which defaults to 10. This controls
how many batch queue items are processed concurrently per environment.
There is also a global rate limit for the batch queue set via the
`BATCH_QUEUE_GLOBAL_RATE_LIMIT` which defaults to being disabled. If
set, the entire batch queue system won't process more than
`BATCH_QUEUE_GLOBAL_RATE_LIMIT` items per second. This allows
controlling the maximum number of runs created per second via batch
triggers.
## Batch trigger settings
- `STREAMING_BATCH_MAX_ITEMS` controls the maximum number of items in a
single batch
- `STREAMING_BATCH_ITEM_MAXIMUM_SIZE` controls the maximum size of each
item in a batch
- `BATCH_CONCURRENCY_DEFAULT_CONCURRENCY` controls the default
environment concurrency
- `BATCH_QUEUE_DRR_QUANTUM` how many credits each environment gets each
round for the DRR scheduler
- `BATCH_QUEUE_MAX_DEFICIT` the maximum deficit for the DRR scheduler
- `BATCH_QUEUE_CONSUMER_COUNT` how many queue consumers to run
- `BATCH_QUEUE_CONSUMER_INTERVAL_MS` how frequently they poll for items
in the queue
### Configuration Recommendations by Use Case
**High-throughput priority (fairness acceptable at 0.98+):**
```env
BATCH_QUEUE_DRR_QUANTUM=25
BATCH_QUEUE_MAX_DEFICIT=100
BATCH_QUEUE_CONSUMER_COUNT=10
BATCH_QUEUE_CONSUMER_INTERVAL_MS=50
BATCH_CONCURRENCY_DEFAULT_CONCURRENCY=25
```
**Strict fairness priority (throughput can be lower):**
```env
BATCH_QUEUE_DRR_QUANTUM=5
BATCH_QUEUE_MAX_DEFICIT=25
BATCH_QUEUE_CONSUMER_COUNT=3
BATCH_QUEUE_CONSUMER_INTERVAL_MS=100
BATCH_CONCURRENCY_DEFAULT_CONCURRENCY=5
```
* chore(docker): use bitnami legacy repo
* chore(helm): use bitnami legacy repo
* Make Helm webapp chart images configurable
Adds configurability for init and token syncer container images through
new values in the Helm chart configuration
* chore(helm): refactor utility image config
* chore(helm): bump chart version to 4.0.3
---------
Co-authored-by: LeoKaynan <leokaynan@hotmail.com>
* Initial work on upgrading to 6.14.0
Set the output to node_modules still to make it easier
* Use ./generated Prisma folder, update types to fix issues
* Docker compose restart Clickhouse
* Prisma instrumentation update
* Docker
* Removed database dockerignore file, add generated prisma client to the top-level one
* Delete v3-catalog package.json
* Resolved pnpm lock file
* Log errors for very slow queries
* Create schema and migration for organization access tokens
* Add helpers for creating and authenticating OATs
* Adapt the auth service to also accept OATs
* Accept OATs in the whoami v2 endpoint
* Enable deployments with the CLI using OATs
* Avoid reading env variables directly in the token utils
* Remove duplicate cli token utils
* Validate ENCRYPTION_KEY length when parsing env vars
* Make token utils a server-only module
* Disallow revoking already revoked OATs
* Simplify generics in authenticateRequest
* Use 32 bytes mock encryption key in the test setup
* Update dummy encryption key values in tests and templates
* Add a column in the OATs table to differentiate between user and system generated
* Simplify args for v3ProjectPath
Co-authored-by: Matt Aitken <matt@mattaitken.com>
* Add index on org id and createdAt
* Avoid storing the encrypted oat token and its obfuscated version in the DB at all
It is a safer approach. Also we do not need to ever read the decrypted token value after creation.
* Fix prisma update condition
* Add token type to the OAT table index
* Accept OATs in the mcp auth flow
* Simplify env auth flow around the /projects endpoints
---------
Co-authored-by: Matt Aitken <matt@mattaitken.com>
* Sentry WIP
* Configure sentry for uploading and releasing during the publish webapp step
* Delete source maps after uploading
* Forward logger.error calls to sentry through Logger.onError
* Couple tweaks to the dockerfile
* Add retry logic for insert operations
Add a generic retry mechanism for task run and payload inserts to handle
transient connection errors. The new #insertWithRetry method retries up to
three times with exponential backoff and jitter on retryable connection
errors such as connection resets or timeouts. Errors are logged and
recorded in tracing spans to improve observability and robustness of the
replication service.
* Replication settings are configurable
* Log out the runIds for failed batches
* Detecting bad JSON in run replication and ignoring it
* Reproduced split unicode error
* Move output file
* Massively improved the performance
* Minor performance improvements
* Unskip tests
* Remove unused test in CH package
* Fix for the ClickHouse UI explorer
* RunReplication keepAlive defaults to false
* Add concurrency_key and bulk_action_group_ids to ClickHouse task runs
* ClickHouse package doesn't need to be built anymore for the webapp
* Set the concurrency_key from the run replication service
* remove unused env vars
* actually use ALERT_REPLY_TO_EMAIL for alerts (non-breaking)
* increase fallback branch limit to 100M
* more unused env vars and example
* hide usage page when self-hosted
* fix for init flow
* set default or concurrency to 300 to match 100 on env
* fail fast when registry env vars are empty strings
* runs replication leader lock expiration fix
* Allow configuring the container image --max-old-space-size using NODE_MAX_OLD_SPACE_SIZE
* Ability to configure the clickhouse keep alive settings
* Add some logging because we might not be able to do telemetry
* WIP clickhouse package with test containers setup
* More clickhouse client setup now with otel and real tests, and the v1 of raw run events
* Add some additional columns to raw_run_events_v1
* WIP runs dashboard service
* Create a new run engine event bus event for the runs dashboard to hook into
* Track run events in the run engine
* make sure engine v1 runs get synced to CH
* Update the attemptNumber of v3 task runs
* Restructure the run events to be more sparse
* emit more stuff
* Setup replication package
* scaffold the replication package
* replication wip
* resolve conflicts
* more replication stuff
* Add ability to drop the replication slot completely on teardown
* Use the new single replacingmergetree task events table for replication
* get it working
* insert payloads into their own table only on insert and then join
* prepare for using clickhouse cloud and now running ch migrations during boot in the entrypoint.sh
* Handover WIP and tests
* Testing the replication service
* Remove the runs dashboard stuff that we aren't using anymore
* Added a test for large payloads
* hacky typecheck fix
* Fix new internal package typecheck issues and start adding telemetry to the replication service
* tracing over spans, some other improvements
* Improvements to the runs replication service, now ready for testing
* Some fixes and cleanups
* Don't need this code anymore
* move transaction types into the runs replication service
* only send spans where there are transaction events
* A couple of suggested tweaks
* refactor: docker compose migration
* fix compose download link
* set static name for electric container
---------
Co-authored-by: nicktrn <55853254+nicktrn@users.noreply.github.com>
* fix and restructure dockerignore
* switch to using pnpm deploy
* pass webapp node image as build arg
* ensure pnpm is downloaded at build, not runtime
* Fix streaming splits in realtime streams v2
* Add changeset
* Skip all flaky tests 😡
* Improve the way we stream from tasks to the server
* Improve the v1 realtime streams (Redis)
* Turn on the relay realtime stream service
* Improved the relay realtime cleanup
* Fixed consuming realtime runs w/streams after the run is already finished
* Remove some logs
* Update changeset
* Fixed runStream tests
* Realtime streams now powered by electric, and fix the streaming update duplicate issues by converting the electric Shape materialized view into a ReadableStream of changes
* Ensure realtime subscription stops when runs are finished, and add an onComplete handle to use realtime hooks
* Fix tests
Daniel Sutton