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 administrative and operational tasks on a Dataiku DSS instance. Specifically, for the DSS Administration resource and the Get Log operation, it retrieves the content of a specified log file from the DSS server.
Common scenarios where this node is beneficial include:
- Monitoring and troubleshooting DSS system behavior by fetching logs such as web server logs, notebook logs, or core backend platform logs.
- Automating log retrieval for audit or compliance purposes.
- Integrating DSS logs into broader monitoring or alerting workflows.
Example use case:
- Automatically fetch the "webserver" log file after a scheduled job run to analyze errors or warnings.
Properties
| Name | Meaning |
|---|---|
| Name | The name of the log file to retrieve from the DSS administration logs. This should correspond to one of the available log files on the DSS instance (e.g., "webserver", "notebook", "core"). |
Output
The output contains the retrieved log data in the json field under the key corresponding to the log content.
- If the log content is JSON-formatted, it will be parsed and returned as a JSON object.
- If the log content is plain text, it will be returned as a string in the
jsonoutput. - The node does not output binary data for this operation.
Output example (JSON):
{
"logContent": {
"timestamp": "2024-06-01T12:00:00Z",
"level": "INFO",
"message": "Service started successfully"
}
}
Or if plain text:
{
"logContent": "2024-06-01 12:00:00 INFO Service started successfully\n..."
}
Dependencies
- Requires an active connection to a Dataiku DSS instance.
- Requires valid API credentials with sufficient permissions to access DSS administration logs.
- The node expects the DSS server URL and an API key credential to authenticate requests.
- No additional external dependencies beyond the standard n8n environment and the Dataiku DSS API.
Troubleshooting
- Missing Credentials Error: If the node throws an error about missing credentials, ensure that the API key credential for the DSS instance is configured correctly in n8n.
- Name Parameter Required: The "Name" property must be provided; otherwise, the node will throw an error indicating the missing log name.
- HTTP Errors: If the DSS server URL is incorrect or unreachable, or if the API key lacks permission, the node will return an error. Verify network connectivity and API key permissions.
- Parsing Errors: If the log content is not valid JSON but the node attempts to parse it, it will fallback to returning raw text. This is expected behavior.
Links and References
- Dataiku DSS API Documentation - Logs (official documentation for DSS administration logs)
- Dataiku DSS API Authentication (details on API key usage)
This summary focuses exclusively on the DSS Administration resource and the Get Log operation as requested.