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 perform a wide range of operations on Dataiku DSS resources directly from n8n workflows. Specifically, for the API Service resource and the Delete Package operation, the node allows deleting a specific package of an API service within a given project.
Typical use cases include automating the management of API services in Dataiku DSS projects, such as cleaning up outdated or unused API packages programmatically. For example, after deploying a new version of an API service package, you might want to delete older packages automatically to maintain a clean environment.
Properties
| Name | Meaning |
|---|---|
| Project Key | The unique key identifying the Dataiku DSS project where the API service resides. |
| Service ID | The identifier of the API service containing the package to be deleted. |
| Package ID | The identifier of the specific package to delete from the API service. |
These properties are required to specify which package to delete within which API service and project.
Output
The node outputs a JSON array where each item corresponds to the response from the Dataiku DSS API for the executed operation.
- For the Delete Package operation, the output JSON typically contains the API response confirming the deletion or relevant status information.
- If the API returns binary data (not typical for delete operations), it would be provided in the
binaryfield, but this operation does not produce binary output.
Example output JSON snippet after successful deletion might look like:
{
"status": "success",
"message": "Package deleted successfully"
}
(Note: Actual response structure depends on the Dataiku DSS API.)
Dependencies
- Requires valid Dataiku DSS API credentials, including:
- The DSS server URL.
- A user API key for authentication.
- The node uses HTTP requests to communicate with the Dataiku DSS REST API.
- No additional external dependencies beyond standard n8n credential configuration.
Troubleshooting
Common Issues
- Missing Credentials: The node will throw an error if the Dataiku DSS API credentials are not set or invalid.
- Missing Required Parameters: Errors occur if any of the required parameters (
Project Key,Service ID, orPackage ID) are not provided. - HTTP Errors: Network issues or incorrect API endpoint usage can cause request failures.
Error Messages
"Missing Dataiku DSS API Credentials": Ensure that the API credentials are configured correctly in n8n."Project Key is required","Service ID is required","Package ID is required": Provide these mandatory inputs."Error calling Dataiku DSS API: <error message>": Indicates an issue during the API call; check network connectivity, API permissions, and parameter correctness.
Resolution Tips
- Verify all required input fields are filled.
- Confirm the API key has sufficient permissions to delete packages.
- Check the DSS server URL is reachable from the n8n instance.
- Review API documentation for any changes in endpoints or required parameters.
Links and References
- Dataiku DSS API Documentation — Official reference for available API endpoints and their usage.
- Dataiku DSS API Services Guide — Details on managing API services and packages.
- n8n Documentation — General guidance on using credentials and HTTP request nodes.
This summary focuses on the API Service resource and the Delete Package operation, describing how to configure and use the node to delete an API service package in Dataiku DSS.