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. Specifically for the Plugin resource and the Delete Plugin operation, the node allows you to delete a plugin from the Dataiku DSS instance by specifying its Plugin ID.
Common scenarios where this node is beneficial include automating plugin management tasks such as installing, updating, or removing plugins programmatically within workflows. For example, you might want to automatically clean up unused plugins or manage plugin lifecycle as part of a CI/CD pipeline.
Practical example:
- You have a workflow that manages your Dataiku DSS environment and want to remove a specific plugin by its ID without manual intervention. This node can be configured to delete that plugin safely.
Properties
| Name | Meaning |
|---|---|
| Plugin ID | The unique identifier of the plugin to delete. Required to specify which plugin to remove. |
| Request Body | A JSON object for additional request data if needed (not typically required for delete). |
Output
The output of the node is a JSON array containing the response from the Dataiku DSS API after attempting to delete the plugin. Typically, for a delete operation, the response may be empty or contain status information confirming the deletion.
If the operation involves downloading files or binary content (not applicable for delete), the node would output binary data accordingly. For the delete plugin operation, no binary output is expected.
Example output JSON structure on success might be:
{
"Status Code": "204 No Content"
}
or an empty JSON object indicating successful deletion.
Dependencies
- Requires an active connection to a Dataiku DSS instance.
- Requires valid API credentials: an API key credential with access rights to manage plugins.
- The node expects the Dataiku DSS server URL and user API key to be configured in the credentials.
Troubleshooting
- Missing Credentials Error: If the node throws an error about missing credentials, ensure that the API key credential is properly set up and linked.
- Plugin ID Required: The node will throw an error if the Plugin ID is not provided. Make sure to specify the correct Plugin ID.
- API Errors: Errors returned from the Dataiku DSS API (e.g., permission denied, plugin not found) will be surfaced as node errors. Verify that the API key has sufficient permissions and that the Plugin ID exists.
- Network Issues: Connection failures or timeouts indicate network problems or incorrect server URLs.
- Unexpected Response Format: If the API returns unexpected data, check the API version compatibility and the correctness of input parameters.
Links and References
- Dataiku DSS API Documentation
- Dataiku DSS Plugins Management Guide
- n8n documentation on creating custom nodes
This summary focuses on the Plugin resource's Delete Plugin operation as requested, based on static analysis of the provided source code and property definitions.