Actions364
- API Service Actions
- Bundles Automation-Side Actions
- Bundles Design-Side Actions
- Connection Actions
- Continuous Activity 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
- Dataset Actions
- 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
- Get Last Metric Values
- Get Metadata
- Get Schema
- Get Single Metric History
- List Datasets
- List Partitions
- List Tables
- List Tables Schemas
- Prepare Tables Import
- Run Checks
- Set Metadata
- Set Schema
- Synchronize Hive Metastore
- Update Dataset Settings
- Update From Hive Metastore
- Dataset Statistic Actions
- Discussion Actions
- DSS Administration Actions
- Flow Documentation Actions
- Insight Actions
- Internal Metric Actions
- Job Actions
- Library Actions
- LLM Mesh Actions
- Long Task Actions
- Machine Learning - Experiment Tracking Actions
- Machine Learning - Lab Actions
- 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
- Delete Visual Analysis
- Deploy Trained Model to Flow
- Download Model Documentation of Trained Model
- Generate Model Documentation From Custom Template
- 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
- Start Training ML Task
- Update User Metadata for Trained Model
- Update Visual Analysis
- Machine Learning - Saved Model Actions
- Compute Partial Dependencies of Version
- 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
- Get Version Scoring PMML
- Get Version Snippet
- Import MLflow Version From File or Path
- List Saved Models
- List Versions
- Set Version Active
- Set Version User Meta
- Update Saved Model
- Macro Actions
- Managed Folder Actions
- Meaning Actions
- Model Comparison Actions
- Notebook Actions
- Plugin Actions
- 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
- 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
- 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 Actions
- Project Deployer Actions
- Create Deployment
- Create Infra
- Create Project
- Delete Bundle
- Delete Deployment
- Delete Infra
- Delete Project
- Get Deployment
- Get Deployment Governance Status
- Get Deployment Settings
- Get Deployment Status
- Get Infra
- Get Infra Settings
- Get Project
- Get Project Settings
- Save Deployment Settings
- Save Infra Settings
- Save Project Settings
- Update Deployment
- Upload Bundle
- Project Folder Actions
- Recipe Actions
- Scenario Actions
- Security Actions
- SQL Query Actions
- Streaming Endpoint Actions
- Webapp Actions
- Wiki Actions
- Workspace Actions
DSS Administration → Save General Settings
AI-generatedOverview
This node integrates with the Dataiku DSS API, allowing users to perform a wide range of administrative and operational tasks on a Dataiku DSS instance. Specifically, for the DSS Administration resource and the Save General Settings operation, the node enables saving or updating the general settings of the DSS instance.
Common scenarios where this node is beneficial include automating configuration changes in DSS environments, managing global settings programmatically as part of CI/CD pipelines, or integrating DSS administration into broader workflows.
For example, you might use this node to update global DSS settings such as system-wide parameters or configurations without manually accessing the DSS UI, enabling automated environment management.
Properties
| Name | Meaning |
|---|---|
| Request Body | JSON object containing the general settings data to save/update in the DSS instance. |
The Request Body property expects a JSON object representing the new or updated general settings for the DSS instance. The exact structure depends on the DSS API specification for general settings.
Output
The node outputs the response from the DSS API call in the json field of the output data. This typically contains the updated general settings object or confirmation of the successful update.
If the API returns binary data (not typical for this operation), it would be provided in the binary field, but for saving general settings, the output is JSON.
Dependencies
- Requires an active connection to a Dataiku DSS instance.
- Requires valid API credentials: specifically, a DSS server URL and a user API key for authentication.
- The node uses HTTP requests to communicate with the DSS REST API.
- No additional external services are required beyond the DSS API.
Troubleshooting
- Missing Credentials Error: If the node throws "Missing Dataiku DSS API Credentials," ensure that the API credentials (server URL and API key) are correctly configured in n8n.
- Required Parameter Errors: The node validates required parameters before making the API call. For this operation, ensure the
requestBodyJSON is properly formed and not empty. - API Errors: Errors returned by the DSS API will be surfaced as node errors with messages like "Error calling Dataiku DSS API: ...". Check the message and stack trace for details.
- Invalid JSON in Request Body: Ensure the JSON provided in the
Request Bodyproperty is valid and matches the expected schema for DSS general settings. - Network Issues: Verify network connectivity to the DSS server and that the API endpoint is accessible.
Links and References
- Dataiku DSS API Documentation - General Settings (official API docs for general settings)
- Dataiku DSS REST API Overview
- n8n Documentation - Creating Custom Nodes
Note: This summary focuses on the DSS Administration resource and the Save General Settings operation only, based on the provided input properties and source code analysis.