Actions364
- Continuous Activity Actions
- Dataset Actions
- Get Last Metric Values
- Get Metadata
- Get Schema
- Get Single Metric History
- List Datasets
- List Partitions
- Compute Metrics
- Create Dataset
- Create Managed Dataset
- Delete Data
- Delete Dataset
- Execute Tables Import
- Get Column Lineage
- Get Data
- Get Data - Alternative Version
- Get Dataset Settings
- Get Full Info
- List Tables
- List Tables Schemas
- Prepare Tables Import
- Run Checks
- Set Metadata
- Set Schema
- Synchronize Hive Metastore
- Update Dataset Settings
- Update From Hive Metastore
- API Service Actions
- Bundles Automation-Side Actions
- Bundles Design-Side Actions
- Connection Actions
- Dashboard Actions
- Data Collection Actions
- Data Quality Actions
- Compute Rules on Specific Partition
- Create Data Quality Rules Configuration
- Delete Rule
- Get Data Quality Project Current Status
- Get Data Quality Project Timeline
- Get Data Quality Rules Configuration
- Get Dataset Current Status
- Get Dataset Current Status per Partition
- Get Last Outcome on Specific Partition
- Get Last Rule Results
- Get Rule History
- Update Rule Configuration
- DSS Administration Actions
- Job Actions
- Library Actions
- Dataset Statistic Actions
- Discussion Actions
- Flow Documentation Actions
- Insight Actions
- Internal Metric Actions
- LLM Mesh Actions
- Machine Learning - Lab Actions
- Delete Visual Analysis
- Deploy Trained Model to Flow
- Download Model Documentation of Trained Model
- Generate Model Documentation From Custom Template
- Start Training ML Task
- Update User Metadata for Trained Model
- Update Visual Analysis
- Adjust Forecasting Parameters and Algorithm
- Compute Partial Dependencies of Trained Model
- Compute Subpopulation Analysis of Trained Model
- Create ML Task
- Create Visual Analysis
- Create Visual Analysis and ML Task
- Generate Model Documentation From Default Template
- Generate Model Documentation From File Template
- Get ML Task Settings
- Get ML Task Status
- Get Model Snippet
- Get Partial Dependencies of Trained Model
- Get Scoring Jar of Trained Model
- Get Scoring PMML of Trained Model
- Get Subpopulation Analysis of Trained Model
- Get Trained Model Details
- Get Visual Analysis
- List ML Tasks of Project
- List ML Tasks of Visual Analyses
- List Visual Analyses
- Reguess ML Task
- Machine Learning - Saved Model Actions
- Compute Partial Dependencies of Version
- Get Version Scoring PMML
- Get Version Snippet
- Import MLflow Version From File or Path
- List Saved Models
- List Versions
- Set Version Active
- Compute Subpopulation Analysis of Version
- Create Saved Model
- Delete Version
- Download Model Documentation of Version
- Evaluate MLflow Model Version
- Generate Model Documentation From Custom Template
- Generate Model Documentation From Default Template
- Generate Model Documentation From File Template
- Get MLflow Model Version Metadata
- Get Partial Dependencies of Version
- Get Saved Model
- Get Subpopulation Analysis of Version
- Get Version Details
- Get Version Scoring Jar
- Set Version User Meta
- Update Saved Model
- Long Task Actions
- Machine Learning - Experiment Tracking Actions
- Macro Actions
- Plugin Actions
- Download Plugin
- Fetch From Git Remote
- Get File Detail From Plugin
- Get Git Remote Info
- Get Plugin Settings
- Install Plugin From Git
- Install Plugin From Store
- List Files in Plugin
- List Git Branches
- List Plugin Usages
- Move File or Folder in Plugin
- Add Folder to Plugin
- Create Development Plugin
- Create Plugin Code Env
- Delete File From Plugin
- Delete Git Remote Info
- Delete Plugin
- Download File From Plugin
- Move Plugin to Dev Environment
- Pull From Git Remote
- Push to Git Remote
- Rename File or Folder in Plugin
- Reset to Local Head State
- Reset to Remote Head State
- Set Git Remote Info
- Set Plugin Settings
- Update Plugin Code Env
- Update Plugin From Git
- Update Plugin From Store
- Update Plugin From Zip Archive
- Upload File to Plugin
- Upload Plugin
- Project Deployer Actions
- Get Deployment Settings
- Get Deployment Status
- Create Deployment
- Create Infra
- Create Project
- Delete Bundle
- Delete Deployment
- Delete Infra
- Delete Project
- Get Deployment
- Get Deployment Governance Status
- Get Infra
- Get Infra Settings
- Get Project
- Get Project Settings
- Save Deployment Settings
- Save Infra Settings
- Save Project Settings
- Update Deployment
- Upload Bundle
- SQL Query Actions
- Wiki Actions
- Managed Folder Actions
- Meaning Actions
- Model Comparison Actions
- Notebook Actions
- Project Actions
- Project Folder Actions
- Recipe Actions
- Scenario Actions
- Security Actions
- Streaming Endpoint Actions
- Webapp Actions
- Workspace Actions
Overview
This node integrates with the Dataiku DSS API, enabling users to manage various Dataiku DSS resources programmatically within n8n workflows. Specifically for the Connection resource and the Create Connection operation, it allows creating new connections on a Dataiku DSS instance by sending a JSON request body describing the connection details.
Common scenarios where this node is beneficial include automating the setup of data source connections in Dataiku DSS projects, integrating connection management into CI/CD pipelines, or dynamically creating connections based on external inputs or events.
For example, you might use this node to:
- Automatically create a new database connection in Dataiku DSS when a new environment is provisioned.
- Create connections to different data sources as part of a data pipeline orchestration.
- Manage connections centrally via n8n workflows triggered by external systems.
Properties
| Name | Meaning |
|---|---|
| Request Body | A JSON object defining the connection details to be created in Dataiku DSS. This should conform to the expected schema of the Dataiku DSS API for connection creation. |
The Request Body property is the main input for the "Create Connection" operation. It expects a JSON structure that specifies all necessary parameters for the connection, such as connection type, credentials, configuration settings, etc., as required by the Dataiku DSS API.
Output
The output of this node is a JSON array containing the response from the Dataiku DSS API after attempting to create the connection. The exact structure depends on the API's response but typically includes details about the newly created connection or error information if the creation failed.
If the API returns binary data (not typical for connection creation), it would be provided as binary output, but for this operation, the output is JSON.
Example output snippet (conceptual):
[
{
"json": {
"name": "my_new_connection",
"type": "jdbc",
"details": {
"host": "db.example.com",
"port": 5432,
"database": "mydb"
},
"status": "created"
}
}
]
Dependencies
- Requires an active connection to a Dataiku DSS instance.
- Requires valid API authentication credentials (an API key) configured in n8n for the Dataiku DSS API.
- The node uses HTTP requests to communicate with the Dataiku DSS REST API endpoints.
- No additional external services are needed beyond the Dataiku DSS server and its API.
Troubleshooting
- Missing Credentials Error: If the node throws an error about missing credentials, ensure that the Dataiku DSS API credentials (API key and server URL) are properly set up in n8n.
- Required Parameters Missing: The node validates required parameters like connection name. If these are missing, it will throw errors indicating which parameter is required.
- Invalid JSON in Request Body: Ensure the JSON provided in the
Request Bodyproperty is well-formed and matches the expected schema for a connection in Dataiku DSS. - API Errors: If the Dataiku DSS API returns an error (e.g., due to invalid connection details or permissions), the node will throw an error with the message returned by the API. Check the API documentation and your connection details.
- Network Issues: Connectivity problems between n8n and the Dataiku DSS server can cause failures. Verify network access and firewall rules.
Links and References
- Dataiku DSS API Documentation
- Dataiku DSS Connections API Reference
- n8n Documentation - Creating Custom Nodes
This summary focuses on the "Connection" resource and the "Create Connection" operation as requested, based on static analysis of the provided source code and properties.