Automate Log Anomaly Detector — Operations AI

Operations teams manage complex processes across systems. Manual coordination creates bottlenecks and errors.

Fields Extracted

300s

Max Processing

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Common Pain Points

Process delays impact customer satisfaction
Manual handoffs introduce errors
Incident response takes too long
Lack of visibility into operational status

What This Template Does

AI-powered extraction using gemini-2.5-flash. Part of 113 production-ready templates.

Capabilities

Incident Response
Monitoring
Document Processing
Log Anomaly
Monitoring

Output Schema

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "title": "Log Anomaly Detector",
  "description": "Log Anomaly Detector: Detect anomalies in log file and label severity.",
  "type": "object",
  "properties": {
    "anomaly_detected": {
      "type": "string",
      "description": "Anomaly detected"
    },
    "anomaly_type": {
      "type": "string",
      "description": "Anomaly type"
    },
    "severity": {
      "type": "string",
      "description": "Severity"
    },
    "start_
...

Quick Start

$ pip install doclayer

$ doclayer process document.pdf --agent ops.log-anomaly

See It In Action

Real extraction example showing input document and structured output.

Input Document

APPLICATION LOGS - api-gateway-prod

2024-01-15 14:30:01 ERROR [RequestHandler] Connection timeout to database after 30s
2024-01-15 14:30:02 ERROR [RequestHandler] Connection timeout to database after 30s
2024-01-15 14:30:03 ERROR [RequestHandler] Connection timeout to database after 30s
2024-01-15 14:30:15 WARN [HealthCheck] Database connection pool exhausted (0/100 available)
2024-01-15 14:30:20 ERROR [PaymentService] Failed to process payment: DB_UNAVAILABLE
2024-01-15 14:30:21 INFO [CircuitB

Extracted Data

{
  "anomaly_detected": "true",
  "anomaly_type": "Database Connection Failure",
  "severity": "Critical",
  "start_time": "2024-01-15 14:30:01",
  "end_time": "2024-01-15 14:32:01",
  "duration": "2 minutes",
  "error_count": "5",
  "affected_services": "RequestHandler, PaymentService",
  "root_cause": "Database connection pool exhausted",
  "resolution": "Circuit breaker activated, auto-recovered",
  "document_type": "log_anomaly_report"
}

Application logs showing database connection pool exhaustion anomaly with error rate spike and circuit breaker activation. Demonstrates pattern detection from request handler timeouts through health check recovery sequence.

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Frequently Asked Questions

What documents can Log Anomaly Detector process?

The Log Anomaly Detector template processes ops documents including various formats and layouts. See the instructions for specific document types supported.

How accurate is the Log Anomaly Detector extraction?

The Log Anomaly Detector template uses Gemini 2.5 Flash for high-accuracy extraction. Results include confidence scores for each field.

Can I customize the Log Anomaly Detector template?

Yes, you can modify the extraction schema, add custom fields, or adjust the instructions to match your specific requirements.

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