Linking Gerrit 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 Gerrit connector syncs changes, accounts, projects, 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 your Gerrit instance URL and credentials to pull your code review data.
Generate an HTTP password in your Gerrit account under Settings > HTTP Credentials (or HTTP Password on older versions) and enter it together with your Gerrit username. On public instances you can leave both blank to sync with anonymous read access - you'll only see the changes, accounts, and projects that are publicly visible, and group listing requires an authenticated account.
You'll be asked for:
- Instance URL: for example
https://gerrit.example.com.
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.
Some Gerrit tables sync incrementally, so later runs only fetch new or updated rows. The rest are full refresh.
Configuration
| Option | Type | Required |
|---|---|---|
Instance URL | text | Yes |
Username | text | No |
HTTP password | password | No |
Supported tables
| Table | Description | Sync method | Incremental field | Primary key |
|---|---|---|---|---|
changes | A change under review: one unit of work (a commit and its patch sets) proposed for a project branch, with its labels, review messages, and current revision. | Incremental, Full refresh | updated | — |
accounts | A user account on the Gerrit instance. Only active accounts are synced. | Full refresh | — | — |
projects | A project (Git repository) hosted on the Gerrit instance. | Full refresh | — | — |
groups | An account group on the Gerrit instance. Listing groups requires an authenticated account. | Full refresh | — | — |
group_members | The direct members of each internal account group, one row per group and account. External groups (such as LDAP or system groups) have no member list. | Full refresh | — | — |
project_branches | The branches of each project, including HEAD and refs/meta/config. | Full refresh | — | — |
change_comments | Published inline and file-level review comments on each change, across all patch sets. | Incremental, Full refresh | change_updated | — |
change_files | The files modified by the current patch set of each change, with per-file line counts. | Incremental, Full refresh | change_updated | — |
Troubleshooting
- If the connection fails with an authorization error, the HTTP password 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.