Error Tracking
Automatic error grouping, deduplication, and AI-powered root cause analysis. identify, prioritize, and fix issues with surgical precision.
Overview
LuminaLog automatically tracks and groups errors from your logs, making it easy to identify, prioritize, and fix issues. Every log with level: "error" is tracked, fingerprinted, and grouped with similar errors instantly.
Automatic Grouping
Errors are fingerprinted by message and stack trace to prevent noise.
Occurrence Tracking
See frequency trends and when an error first/last appeared.
Real-time Alerts
Get notified via Slack or Discord the moment a critical error spikes.
AI Analysis
AI-powered root cause analysis and fix suggestions for every trace.
How It Works
Any log with `level: error` is automatically flagged as a trackable event.
The error message and stack trace are hashed to create a unique, immutable fingerprint.
LuminaLog checks if this fingerprint exists and groups it into an existing issue or creates a new one.
User IDs, request paths, and metadata are attached to each specific occurrence.
Our LLM engine analyzes the stack trace to explain the root cause and provide a fix.
Logging Errors
Simple Error Level
// Use the .error() method for manual reporting
logger.error('Payment processing failed', {
order_id: 'ORD-12345',
user_id: 'user-789',
amount: 99.99
});Detailed Error Objects
// Passing error fields manually
try {
await processPayment(order);
} catch (err) {
logger.error('Payment failed', {
error: err.message,
stack: err.stack,
order_id: order.id
});
}Capture Error Recommended
The captureError() method is the most efficient way to log exceptions as it automatically handles extraction.
try {
await processPayment(order);
} catch (error) {
logger.captureError(error, {
order_id: order.id,
user_id: order.user_id,
amount: order.amount
});
throw error;
}Why captureError()?
captureError() extracts the error type, message, and full stack trace automatically, ensuring perfect grouping and AI analysis compatibility.Error Quotas & Tiers
| Tier | Error Quota | AI Analysis |
|---|---|---|
| Indie (Free) | 10,000 / mo | ❌ Not included |
| Bootstrapper | 20,000 / mo | ✓ 25 analyses / mo |
| Compliance | 50,000 / mo | ✓ 50 analyses / mo |
| Scale | 1,000,000 / mo | ✓ 500 analyses / mo |
AI-Powered Analysis
On Bootstrapper+ tiers, LuminaLog uses proprietary LLM engines to analyze errors and provide instant feedback loop acceleration.
Understands exactly what code path led to the failure.
Generates code snippets to resolve the specific exception.
Calculates which users and features are most affected.
Cross-references your organization to find historical solutions.
// AI Analysis Result:
// Root Cause: The error occurs because the payment gateway API returned a 402,
// indicating insufficient funds.
// Suggested Fix:
try {
const result = await paymentGateway.charge(amount);
} catch (error) {
if (error.statusCode === 402) {
return { success: false, code: 'INSUFFICIENT_FUNDS' };
}
throw error;
}Status Management
Unresolved
Active errors that require developer attention.
Resolved
Errors marked as fixed. Reopens automatically on recurrence.
Ignored
Muted errors from specific environments or sources.
Best Practices
Ensures stack traces are preserved and grouped correctly.
Include IDs for users, orders, and requests in every error log.
Don't depend on checking the dashboard manually.
Catch regression bugs immediately after production deployments.
Next Steps
AI Debugging
Deep dive into our LLM engine's error analysis capabilities.
Alerts & Notifications
Learn how to route errors to your team's communication channels.
Real-time Logs
See errors appear in the dashboard the second they happen.
SDK Reference
Implement specialized error tracking in Node.js or Python.