Matt Aitken
c2c6e5c705
## Summary Runs created for a Session were triggered without a realtime streams version, so they fell through to the `realtimeStreamsVersion` column default of `v1`. A Session's own `.in` / `.out` channels are always `v2`, so any run-scoped `streams.append()` or `streams.pipe()` call made inside a session run wrote to a different backend than the session it belongs to, and stayed there for the life of the run. The API trigger routes were never affected. They call `determineRealtimeStreamsVersion` with the client's `x-trigger-realtime-streams-version` header and always pass an explicit value, so a current SDK asking for v2 gets it. Only the internal callers that build trigger options by hand were leaning on the column default, which no env var can influence because that path never calls the resolver at all. ## The version resolver Fixing the call site exposed a second problem in `determineRealtimeStreamsVersion`. Its two paths disagreed: an explicit `v2` was checked against the S2 configuration first, but when the caller expressed no preference it returned `REALTIME_STREAMS_DEFAULT_VERSION` verbatim with no check. A deployment that set the default to `v2` without configuring S2 therefore stamped runs `v2`, nothing failed at trigger time, and every later read or write against those runs' streams threw `Realtime streams v2 is required for this run but S2 configuration is missing` for the life of the run. Both paths now resolve through one pure function that takes its configuration rather than reading `env`: ```ts const requested = streamVersion ?? config.defaultVersion; if (requested !== "v2") return "v1"; const hasCredentials = Boolean(config.accessToken) || config.skipAccessTokens; return hasCredentials && Boolean(config.basin) ? "v2" : "v1"; ``` ## The basin requirement `resolveStreamBasin` resolves run, session and organization basins ahead of the global setting, so a deployment that provisions a basin per organization can serve v2 with no global basin at all. Gating purely on the global setting would degrade every run there to `v1`. `determineRealtimeStreamsVersion` therefore takes an optional organization basin, and every caller that holds one passes it, including the session path: ```ts basin: organizationBasinName ?? env.REALTIME_STREAMS_S2_BASIN, ``` This is deliberately the resolved basin and not the `REALTIME_STREAMS_PER_ORG_BASINS_ENABLED` flag. The flag says the feature is on, not that a given organization has been provisioned, and provisioning happens out of band. Keying off the flag would stamp `v2` on runs for unprovisioned organizations, recreating the failure this removes. **This widens behaviour for explicit `v2` requests**, which previously required the global basin: a provisioned organization on a per-org deployment now resolves `v2` where it used to get `v1`. That is intentional, and it makes every path agree. ## Scope Only newly created runs change. A run already stamped `v1` keeps that version for its lifetime by design, since readers resolve the backend from the same column and its existing streams have to stay readable. Scheduled runs reach the same column default through `scheduleEngine.server.ts` and are deliberately left alone: that one is a policy question about `REALTIME_STREAMS_DEFAULT_VERSION` rather than an inconsistency inside a single feature. ## Verification A full-stack e2e boots the real webapp plus Postgres, Redis and s2-lite, creates a Session through the public API so the run comes from the real trigger path, appends records the way `streams.append()` does, and asserts three things at once: the version stamped on the run, that the payload is readable from S2, and that no key exists in Redis. It appends at a realistic record size so the route's body cap and S2's per-record cap are both exercised. Reverting the session-path change flips all three observations, so it fails against the old behaviour rather than passing vacuously. Unit tests cover the resolver matrix, including organization-basin-only and credential-only configurations; two of them fail against the previous resolver. Also verified by hand against a local stack: a real `chat.agent` session run writing 8 records of 250KB through `streams.append()` put 2,049,072 bytes into S2 with no Redis key, while the same agent with the session-path change removed put 2,102,360 bytes into Redis and nothing into S2.
Build and deploy fully‑managed AI agents and workflows
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About Trigger.dev
Trigger.dev is the open-source platform for building AI workflows in TypeScript. Long-running tasks with retries, queues, observability, and elastic scaling.
The platform designed for building AI agents
Build AI agents using all the frameworks, services and LLMs you're used to, deploy them to Trigger.dev and get durable, long-running tasks with retries, queues, observability, and elastic scaling out of the box.
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Long-running without timeouts: Execute your tasks with absolutely no timeouts, unlike AWS Lambda, Vercel, and other serverless platforms.
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Durability, retries & queues: Build rock solid agents and AI applications using our durable tasks, retries, queues and idempotency.
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True runtime freedom: Customize your deployed tasks with system packages – run browsers, Python scripts, FFmpeg and more.
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Human-in-the-loop: Programmatically pause your tasks until a human can approve, reject or give feedback.
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Realtime apps & streaming: Move your background jobs to the foreground by subscribing to runs or streaming AI responses to your app.
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Observability & monitoring: Each run has full tracing and logs. Configure error alerts to catch bugs fast.
Key features:
- JavaScript and TypeScript SDK - Build background tasks using familiar programming models
- Long-running tasks - Handle resource-heavy tasks without timeouts
- Durable cron schedules - Create and attach recurring schedules of up to a year
- Trigger.dev Realtime - Trigger, subscribe to, and get real-time updates for runs, with LLM streaming support
- Build extensions - Hook directly into the build system and customize the build process. Run Python scripts, FFmpeg, browsers, and more.
- React hooks - Interact with the Trigger.dev API on your frontend using our React hooks package
- Batch triggering - Use batchTrigger() to initiate multiple runs of a task with custom payloads and options
- Structured inputs / outputs - Define precise data schemas for your tasks with runtime payload validation
- Waits - Add waits to your tasks to pause execution for a specified duration
- Preview branches - Create isolated environments for testing and development. Integrates with Vercel and git workflows
- Waitpoints - Add human-in-the-loop judgment at critical decision points without disrupting workflow
- Concurrency & queues - Set concurrency rules to manage how multiple tasks execute
- Multiple environments - Support for DEV, PREVIEW, STAGING, and PROD environments
- No infrastructure to manage - Auto-scaling infrastructure that eliminates timeouts and server management
- Automatic retries - If your task encounters an uncaught error, we automatically attempt to run it again
- Checkpointing - Tasks are inherently durable, thanks to our checkpointing feature
- Versioning - Atomic versioning allows you to deploy new versions without affecting running tasks
- Machines - Configure the number of vCPUs and GBs of RAM you want the task to use
- Observability & monitoring - Monitor every aspect of your tasks' performance with comprehensive logging and visualization tools
- Logging & tracing - Comprehensive logging and tracing for all your tasks
- Tags - Attach up to ten tags to each run, allowing you to filter via the dashboard, realtime, and the SDK
- Run metadata - Attach metadata to runs which updates as the run progresses and is available to use in your frontend for live updates
- Bulk actions - Perform actions on multiple runs simultaneously, including replaying and cancelling
- Real-time alerts - Choose your preferred notification method for run failures and deployments
Write tasks in your codebase
Create tasks where they belong: in your codebase. Version control, localhost, test and review like you're already used to.
import { task } from "@trigger.dev/sdk";
//1. You need to export each task
export const helloWorld = task({
//2. Use a unique id for each task
id: "hello-world",
//3. The run function is the main function of the task
run: async (payload: { message: string }) => {
//4. You can write code that runs for a long time here, there are no timeouts
console.log(payload.message);
},
});
Deployment
Use our SDK to write tasks in your codebase. There's no infrastructure to manage, your tasks automatically scale and connect to our cloud. Or you can always self-host.
Environments
We support Development, Staging, Preview, and Production environments, allowing you to test your tasks before deploying them to production.
Full visibility of every job run
View every task in every run so you can tell exactly what happened. We provide a full trace view of every task run so you can see what happened at every step.
Getting started
The quickest way to get started is to create an account and project in our web app, and follow the instructions in the onboarding. Build and deploy your first task in minutes.
Useful links:
- Quick start - get up and running in minutes
- How it works - understand how Trigger.dev works under the hood
- Guides and examples - walk-through guides and code examples for popular frameworks and use cases
Self-hosting
If you prefer to self-host Trigger.dev, you can follow our self-hosting guides:
- Docker self-hosting guide - use Docker Compose to spin up a Trigger.dev instance
- Kubernetes self-hosting guide - use our official Helm chart to deploy Trigger.dev to your Kubernetes cluster
Support and community
We have a large active community in our official Discord server for support, including a dedicated channel for self-hosting.
Development
To setup and develop locally or contribute to the open source project, follow our development guide.