OpenAI Integration
Overview
The OpenAI integration in the Engineering Metrics Dashboard allows organizations to monitor OpenAI API usage, track model consumption, analyze user activity, and evaluate AI adoption metrics across teams. This integration is part of the LLM Metrics module. A valid OpenAI admin key with the required permissions is necessary for successful integration.Prerequisites
Before setting up the integration, ensure you have:- Access to the Engineering Metrics Dashboard
- An OpenAI Admin API Key
- Required permissions to configure integrations and projects
Step 1: Navigate to LLM Integrations
- Open the Engineering Metrics Dashboard.
- Navigate to Integrations.
- Select LLM Metrics Integrations.
- Choose OpenAI from the available providers.
Step 2: Create a New OpenAI Connection
- Click New Connection.
- Enter a unique Connection Name.
- Paste the OpenAI Admin Key into the provided field.
The admin key is generally managed by the organization administrator and is used to enable centralized AI usage tracking.
Step 3: Test the Connection
- Click Test Connection.
- Wait for validation to complete.
Expected Result
If the admin key is valid and configured correctly, the connection test succeeds. If the test fails, verify the API key and permissions before retrying.Step 4: Save the Connection
- After a successful test, click Save Connection.
- The OpenAI connection will appear in the available connections list.
Step 5: Create an LLM Metrics Project
After creating the OpenAI connection:- Navigate to Projects.
- Click Add Project.
- Select LLM Metrics as the project type.
- Enter the required project details.
Step 6: Select the OpenAI Data Source
Within the Data Source section:- Select OpenAI.
- Choose the saved OpenAI admin key connection.
- Confirm the selected connection.
Step 7: Configure Sync Behavior
The Sync Behavior section controls how frequently and for what duration data is collected.Data Collection Range
Choose the duration for which historical data should be collected. Examples:- Last 10 Days
- Last 30 Days
- Last 6 Months
- Last 1 Year
Sync Frequency
Select how often synchronization should run. Available options include:- Daily
- Weekly
- Monthly
- Custom Schedule
- Every 2 Hours
Schedule Status Options
| Status | Description |
|---|---|
| Active | Runs synchronization automatically according to the configured schedule |
| Inactive | Disables automatic synchronization |
| Pause | Temporarily pauses synchronization for the configured connection |
Scheduled Time
Users can configure a custom execution time for synchronization jobs.Step 8: Complete Project Setup
- Review all configuration settings.
- Click Complete Setup.
Step 9: Run Initial Synchronization
- Open the configured project.
- Click Run Sync Now.
- Collects the latest OpenAI usage data
- Processes metrics and usage information
- Updates the dashboard with the latest analytics
Understanding Sync Operations
Run Sync Now
The Run Sync Now option fetches the latest available usage data from OpenAI. Whenever new API activity occurs, synchronization updates the dashboard accordingly.Retransform Data
Retransform Data does not fetch new information. Instead, it reprocesses previously collected data to:- Correct formatting inconsistencies
- Standardize collected records
- Recalculate processed metrics
In most cases, normal synchronization automatically performs the required transformation process.
Monitoring Integration Status
The Status section provides:- Synchronization history
- Task execution details
- Success and failure status
- Processing duration
- Completed operations overview
Viewing OpenAI Metrics
After synchronization completes:- Navigate to the LLM Metrics Dashboard.
- Search for the configured OpenAI project.
- Open the project to view analytics and usage metrics.
- User Activity
- API Usage
- Model Consumption
- Organization-wide AI Adoption
- Usage Trends and Patterns
Available Insights
User-Level Usage Data
The dashboard displays API usage information for users consuming OpenAI services within the organization.API Key and Sub-Key Tracking
Projects may contain multiple API keys and sub-keys. The platform tracks usage across:- Projects
- Sub-Keys
- Individual API Keys
Model Usage Analytics
Organizations can monitor which OpenAI models are actively being used. Examples include:- GPT Models
- Different Model Versions
- Team-wise Usage Distribution
ROI and Business Impact Summary
The ROI and Business Impact section provides estimates related to:- Development Time Savings
- Productivity Improvements
- Operational Efficiency
- Estimated Cost Optimization
Executive Summary
The Executive Summary section provides a broader overview of AI adoption trends and organizational impact.Certain Executive Summary features may still be under active development depending on the deployment version.
Troubleshooting
Connection Test Failed
Possible Causes
- Invalid API Key
- Missing Permissions
- Expired Credentials
Resolution
- Verify the admin key
- Confirm permissions with the administrator
- Retry the connection test
No Data Appearing After Sync
Possible Causes
- Synchronization still in progress
- Incorrect project configuration
- Schedule disabled
Resolution
- Check the Status section
- Re-run synchronization manually
- Verify sync schedule settings
Schedule Not Running
Possible Causes
- Schedule set to Inactive
- Schedule currently Paused
Resolution
- Set the schedule status to Active
- Verify the configured sync frequency and execution time
Best Practices
Use Clear and Unique Connection Names
Use descriptive connection names that clearly identify the environment.Periodically Verify Admin Key Validity
Regularly confirm that the configured OpenAI Admin Key remains valid.Configure Regular Synchronization Schedules
Maintain consistent synchronization intervals to ensure accurate reporting.Monitor Synchronization Status Regularly
Review synchronization health and execution history to identify issues early.Review Usage and ROI Metrics Periodically
Regularly evaluate adoption, consumption, and business impact metrics.Summary
The OpenAI integration enables organizations to centralize and monitor AI usage directly within the Engineering Metrics Dashboard. By configuring the admin key connection, scheduling synchronization, and monitoring usage analytics, teams gain visibility into:- AI Adoption
- Model Usage
- User Activity
- ROI Metrics
- Business Impact

