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 to perform various operations on internal metrics and other resources within a Dataiku DSS instance. Specifically, for the "Internal Metric" resource with the "List Internal Metrics" operation, it retrieves internal metrics from the DSS instance as a dictionary.
Common scenarios where this node is beneficial include:
- Monitoring and analyzing internal performance or usage metrics of a Dataiku DSS instance.
- Automating the retrieval of internal metrics for reporting or alerting purposes.
- Integrating DSS internal metrics into broader workflows or dashboards.
Example use case:
- A data engineer wants to periodically fetch internal metrics from their DSS instance to monitor system health and trigger alerts if certain thresholds are exceeded.
Properties
| Name | Meaning |
|---|---|
| Query Parameters | Collection of optional parameters to filter or modify the request when listing metrics. Options include: Active (boolean), Activity (string), All Users (boolean), Archive Path (string), Catalog Name (string), Code Env Name (string), Column Name (string), Columns (string), Connected (boolean), Connection Name (string), Container Execution Configuration Name (string), Deletion Mode (string), Destination ID (string), Drop Data (boolean), Export Analysis Models (boolean), Export Managed (boolean), Export Saved Models (boolean), Export Uploads (boolean), File Part (string), Filter (string), Folder ID (string), Folder Reference (string), Force Rebuild Env (boolean), Foreign (boolean), Format (string), Format Params (string), Full Class Name (string), Full Reguess (boolean), Include All Partitions (boolean), Include Libs (boolean), Limit (number, min 1, default 50), Max Dataset Count (number), Metric Lookup (string), Min Timestamp (number), Name (string), Only Monitored (boolean), Page (number), Partition (string), Partitions (string), Path (string), Peek (boolean), Prediction Type (string), Project Folder ID (string), Project Key (string), Published Project Key (string), Published Service ID (string), Purpose (string), Remote (string), Remove Intermediate (boolean), Reassign To (string), Results per Page (number), Rule ID (string), Schema Name (string), Step ID (string), Sub-Folder Name (string), Tags (string), Target Variable (string), Time Series Identifiers (string), Time Variable (string), Trigger ID (string), Trigger Run ID (string), Trust For Everybody (boolean), Type (string), Versions (string), Wait (boolean), With Scenarios (boolean). |
Note: The full list of query parameter options is extensive; users can specify any combination relevant to filtering or modifying the internal metrics request.
Output
The node outputs the response from the Dataiku DSS API call in the json field of the output items.
- For the "List Internal Metrics" operation, the output JSON contains a dictionary of internal metrics retrieved from the DSS instance.
- The structure of the returned JSON depends on the DSS API but generally includes metric names and their corresponding values or details.
- No binary data output is expected for this operation.
Dependencies
- Requires an active connection to a Dataiku DSS instance.
- Requires valid API credentials (an API key credential) for authentication with the DSS API.
- The node uses HTTP requests to communicate with the DSS REST API endpoints.
- No additional external services or environment variables are required beyond the configured 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 and provided.
- Required Parameter Errors: The node validates required parameters based on the selected resource and operation. For example, the project key might be required for some operations. Ensure all mandatory fields are filled.
- API Request Failures: Network issues, incorrect server URLs, or invalid API keys can cause request failures. Verify the DSS server URL and API key correctness.
- Unexpected Response Format: If the API returns unexpected data or errors, check the DSS API documentation for changes or restrictions on the requested operation.
- Large Result Sets: When retrieving many metrics, consider using pagination parameters like
limitandpageto manage response size.
Links and References
- Dataiku DSS API Documentation
- Dataiku DSS Internal Metrics API
- n8n Documentation - Creating Custom Nodes
This summary focuses on the "Internal Metric" resource and the "List Internal Metrics" operation as requested.