Deploy Connector

Context: This plugin is for the Fivetran Connector SDK (CSDK). "CSDK" is shorthand for "Connector SDK".

Deploy Fivetran Connector

FIRST: Read sdk-reference.md from the plugin directory to load SDK rules and patterns.

Package and deploy the connector in the current directory.

Step 1: Pre-Deployment Validation

Verify the connector is ready:

1. Files exist: connector.py, requirements.txt, README.md; configuration.json when supplying configuration.
2. Code quality: Read connector.py and check for:
   • Both schema() and update() functions present
   • connector = Connector(update=update, schema=schema) in global scope
   • if __name__ == "__main__": connector.debug() entry point
   • No forbidden patterns (Dict[str, Any], Generator[op.Operation, ...], op.Operation in type hints)
3. Configuration: configuration.json is JSON. Plaintext string values are supported; do not require custom encryption. Do not read, print, copy, or deploy plaintext configuration values in chat.

Step 2: Run Final Test

Use the secure runner:

python "<plugin>/tools/run_connector.py" "<connector_directory>" --timeout-seconds 600

The runner defaults to 120 seconds and accepts up to 600. Use 600 for debug runs because the first run downloads and starts the Java tester. Set the harness command timeout to 600 seconds as well.

If the test fails, classify the error (INFRA / FIRST_RUN / CODE) and — for CODE errors — apply the fixer workflow (see workflows/fixer.md in the plugin, or — in plugins that support subagents — invoke the connector-fixer subagent).

Step 3: Deploy

For an existing connection, use its ID so the tool reuses its current name and destination without listing destinations or prompting:

python "<plugin>/tools/deploy_connector.py" "<connector_directory>" --connection-id "<id>"

For a new connection, supply the destination (group) name and optionally a connection name; otherwise the connection name is derived from the directory:

python "<plugin>/tools/deploy_connector.py" "<connector_directory>" --destination "<name>" --connection "<name>"

The tool reads FIVETRAN_API_KEY, passes local configuration through a named pipe when present, and invokes fivetran deploy --destination <name> --connection <name> --force. For an existing connection it reads connection details and then that connection's group details. Do not combine --connection-id with name or destination overrides.

If no destination is supplied for a new connection, a single available destination is selected automatically. Multiple destinations require a selection on stdin or an explicit argument. Harnesses without an input channel should pass the target explicitly. Closed input ends the command; do not retry without providing the target.

A missing local configuration file is allowed; the SDK may still use environment configuration. Preserve production settings during code repairs and verify the installed SDK's configuration behavior before deploying. Do not confuse local test inputs with the production configuration.

For required configuration or unusable encrypted values, follow Configuration entry in sdk-reference.md. Plaintext values are supported without a key; do not require re-entry or encryption of user-supplied values.

Prerequisite: FIVETRAN_API_KEY

If the user hasn't set the env var, the tool exits with a clear message. Direct the user to:

1. Create a Fivetran API key at https://fivetran.com/dashboard/user/api-config. It must be the base64-encoded {key}:{secret} string, with permission to manage connections and read destinations (so destination lookup, deploy, and unpause all work).

2. Add it to their shell config.

   macOS/Linux:

   export FIVETRAN_API_KEY=...
   

   Windows PowerShell:

   setx FIVETRAN_API_KEY "..."
   

3. Reload their shell and re-run the deploy command.

If no destinations exist

If the user has zero destinations, the tool exits with a link to the destinations page. Direct the user to create one in the dashboard (requires warehouse credentials) and re-run deploy.

Reference: https://fivetran.com/docs/connector-sdk/working-with-connector-sdk#deploytheconnector

Step 4: Offer to Start the Initial Sync

A newly deployed connection is created paused. Deploying does not start a sync.

After a successful deploy, surface the Connection ID and dashboard link the tool printed, then ask the user whether to start the initial sync now. State plainly that starting the sync begins consuming MAR. Do not start it automatically.

Only if the user explicitly confirms, unpause the connection:

python "<plugin>/tools/deploy_connector.py" "<connector_directory>" --start-sync --connection-id "<id>"

This calls PATCH /v1/connections/{id} with {"paused": false}; Fivetran then begins the initial sync. If the user declines, tell them they can start it anytime from the dashboard link or by re-running the command above.

Redeploying (updating an existing connection)

To update a deployed connection, use --connection-id <id>. This preserves its name and destination even when the recovered project directory has a different name. Redeployment replaces code and supplied configuration; it does not itself unpause the connection. Verify connection health after deployment and use the explicit start-sync path only when authorized.

Alternative: Manual Packaging

If the user prefers manual deployment (e.g., wants to inspect the package before upload):

1. Build the deployable archive:

   fivetran package
   

   This produces a ZIP containing connector.py, configuration.json, requirements.txt (or pyproject.toml), README.md, and any additional source files, respecting .gitignore.
2. Upload via the Fivetran dashboard.