Linking Hatchet as a source
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Skip the manual setup — run this in your project and the wizard auto-detects your databases and APIs and connects them to PostHog.
This source is currently in alpha. The interface and available tables may change.
The Hatchet connector syncs workflow runs, tasks, events, and more into the PostHog data warehouse, so you can analyze them alongside your product data.
Prerequisites
Credentials that can read the data you want to sync. PostHog only reads data, so read access is enough.
Adding a data source
- In PostHog, go to the Sources tab of the data pipeline section.
- Click + New source and click Link next to this source.
- Enter your credentials (see Configuration below) and click Next.
- Select the tables you want to sync, choose a sync method and frequency, then click Import.
Once the syncs are complete, you can start querying this data in PostHog.
Enter a Hatchet API token to sync your workflow runs, tasks, and events.
Create a tenant-scoped API token in your Hatchet dashboard under Settings > API Tokens. The token encodes your tenant and server URL, so that's usually all you need.
If you self-host Hatchet, or the token can't be decoded, set the Host and Tenant id fields to point the connection at your instance.
You'll be asked for:
- API token: for example
Bearer token from Settings > API Tokens.
Sync modes
Each table can be synced in one of several modes, depending on what the source supports:
- Webhook (when available) – the source pushes changes to PostHog in real time. Fastest freshness, lowest ongoing cost, and the only mode that reliably captures updates and deletes.
- Incremental – only new or updated rows are synced on each run, using a cursor field (such as an
updated_attimestamp). Cheaper than a full refresh, but deletes aren't captured. - Append only – new rows are appended using a cursor field; existing rows are never updated. Ideal for immutable, append-only tables like event logs.
- Full refresh – the whole table is reloaded on every sync. Use it when a table has no reliable cursor or when you need deletions reflected.
See sync methods for a full explanation of how each mode works and how to choose between them.
All Hatchet tables are full refresh. Each sync replaces the contents of the table.
Configuration
| Option | Type | Required |
|---|---|---|
API token | password | Yes |
Host | text | No |
Tenant id | text | No |
Supported tables
| Table | Description | Sync method | Incremental field | Primary key |
|---|---|---|---|---|
workflow_runs | A workflow (DAG) run or standalone task run in Hatchet, capturing its status, timings, and input/output payloads. | Incremental, Full refresh | created_at | id |
tasks | An individual task run in Hatchet, including the tasks that make up a DAG workflow run. | Incremental, Full refresh | created_at | id |
events | An event ingested into the Hatchet tenant. Events can trigger workflow runs. | Incremental, Full refresh | created_at | id |
event_keys | The distinct event keys seen in the tenant, used to match workflows that run on events. | Full refresh | — | key |
workflows | A workflow defined in the Hatchet tenant. Workflow runs and tasks reference it by id. | Full refresh | — | id |
workers | A worker registered with the Hatchet tenant. Only workers that sent a heartbeat in the last 24 hours are listed. | Full refresh | — | id |
task_events | A state transition of a Hatchet task (for example assigned, started, retried, failed), with one row per event in each workflow run. | Incremental, Full refresh | workflow_run_created_at | taskId, id |
task_timings | Queued, started, and finished times of each task in a Hatchet workflow run, for latency attribution. | Incremental, Full refresh | workflow_run_created_at | workflow_run_id, taskExternalId |
Troubleshooting
- If the connection fails with an authorization error, the API token is wrong, expired, or has been revoked. Create a new one, then reconnect the source.
- If a table syncs no rows, the credential may not have access to that data. Check its permissions, then reconnect the source.
If your sync is failing or data looks wrong, see the Data warehouse troubleshooting guide. If that doesn't help, contact support – we're happy to help.