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. It supports managing projects, datasets, plugins, dashboards, scenarios, machine learning models, and many other Dataiku DSS entities.
Specifically, for the Plugin resource with the Install Plugin From Git operation, the node allows you to install a plugin by checking it out from a Git repository and installing it into the Dataiku DSS instance. This is useful for automating plugin deployment workflows, integrating custom functionality, or managing plugin lifecycle programmatically.
Common Scenarios
- Automate installation of custom plugins hosted in Git repositories as part of CI/CD pipelines.
- Deploy new or updated plugins to multiple Dataiku DSS instances without manual intervention.
- Integrate plugin management into broader data workflows orchestrated in n8n.
Practical Example
You have developed a custom Dataiku DSS plugin stored in a Git repository. Using this node, you can configure it to automatically pull the latest version of the plugin from Git and install it on your DSS server whenever triggered, ensuring your environment always runs the latest plugin code.
Properties
| Name | Meaning |
|---|---|
| Request Body | JSON object containing additional parameters required by the API endpoint for the operation. For "Install Plugin From Git", this typically includes details like the Git repository URL, branch, credentials, or other installation options. |
Note: The node supports many other properties depending on the resource and operation selected, but for the Plugin - Install Plugin From Git operation, the main input is the Request Body JSON.
Output
The node outputs the response from the Dataiku DSS API call:
- If the response is JSON, it returns it as structured JSON data in the
jsonoutput field. - If the response is a file download (binary data), it returns the binary data prepared for further use in the workflow.
- For the plugin installation operation, the output will typically be a JSON object indicating success or failure of the installation process, including any relevant metadata or status messages.
Dependencies
- Requires an active connection to a Dataiku DSS instance.
- Requires valid API credentials (an API key) for authentication with the Dataiku DSS API.
- The node uses HTTP requests to communicate with the DSS REST API endpoints.
- No additional external dependencies beyond the configured Dataiku DSS API credentials.
Troubleshooting
- Missing Credentials Error: If the node throws an error about missing credentials, ensure that the Dataiku DSS API credentials are properly configured in n8n.
- Required Parameter Errors: Many operations require specific parameters such as project keys, plugin IDs, or other identifiers. Missing these will cause errors. Verify all required fields are filled.
- API Endpoint Errors: If the API returns errors, check the request body JSON for correctness and ensure the Git repository URL and access permissions are valid.
- Binary Data Handling: For operations returning files, ensure subsequent nodes handle binary data correctly.
- Network Issues: Ensure the n8n instance can reach the Dataiku DSS server URL and that firewall or network policies allow communication.
Links and References
This summary focuses on the Plugin resource and the Install Plugin From Git operation, describing how the node constructs the API request, handles authentication, sends the request, and processes the response accordingly.