nomyo-router/doc/monitoring.md

Monitoring and Troubleshooting Guide

Monitoring Overview

NOMYO Router provides comprehensive monitoring capabilities to track performance, health, and usage patterns.

Monitoring Endpoints

Health Check

curl http://localhost:12434/health

Response:

{
  "status": "ok" | "error",
  "endpoints": {
    "http://endpoint1:11434": {
      "status": "ok" | "error",
      "version": "string" | "detail": "error message"
    }
  }
}

HTTP Status Codes:

• 200: All endpoints healthy
• 503: One or more endpoints unhealthy

Current Usage

curl http://localhost:12434/api/usage

Response:

{
  "usage_counts": {
    "http://endpoint1:11434": {
      "llama3": 2,
      "mistral": 1
    },
    "http://endpoint2:11434": {
      "llama3": 0,
      "mistral": 3
    }
  },
  "token_usage_counts": {
    "http://endpoint1:11434": {
      "llama3": 1542,
      "mistral": 876
    }
  }
}

Token Statistics

curl http://localhost:12434/api/token_counts

Response:

{
  "total_tokens": 2418,
  "breakdown": [
    {
      "endpoint": "http://endpoint1:11434",
      "model": "llama3",
      "input_tokens": 120,
      "output_tokens": 1422,
      "total_tokens": 1542
    },
    {
      "endpoint": "http://endpoint1:11434",
      "model": "mistral",
      "input_tokens": 80,
      "output_tokens": 796,
      "total_tokens": 876
    }
  ]
}

Model Statistics

curl http://localhost:12434/api/stats -X POST -d '{"model": "llama3"}'

Response:

{
  "model": "llama3",
  "input_tokens": 120,
  "output_tokens": 1422,
  "total_tokens": 1542,
  "time_series": [
    {
      "endpoint": "http://endpoint1:11434",
      "timestamp": 1712345600,
      "input_tokens": 20,
      "output_tokens": 150,
      "total_tokens": 170
    }
  ],
  "endpoint_distribution": {
    "http://endpoint1:11434": 1542
  }
}

Configuration Status

curl http://localhost:12434/api/config

Response:

{
  "endpoints": [
    {
      "url": "http://endpoint1:11434",
      "status": "ok" | "error",
      "version": "string" | "detail": "error message"
    }
  ]
}

Real-time Usage Stream

curl http://localhost:12434/api/usage-stream

This provides Server-Sent Events (SSE) with real-time updates:

data: {"usage_counts": {...}, "token_usage_counts": {...}}

data: {"usage_counts": {...}, "token_usage_counts": {...}}

Monitoring Tools

Prometheus Integration

Create a Prometheus scrape configuration:

scrape_configs:
  - job_name: 'nomyo-router'
    metrics_path: '/api/usage'
    params:
      format: ['prometheus']
    static_configs:
      - targets: ['nomyo-router:12434']

Grafana Dashboard

Create a dashboard with these panels:

• Endpoint health status
• Current connection counts
• Token usage (input/output/total)
• Request rates
• Response times
• Error rates

Logging

The router logs important events to stdout:

• Configuration loading
• Endpoint connection issues
• Token counting operations
• Error conditions

Troubleshooting Guide

Common Issues and Solutions

1. Endpoint Unavailable

Symptoms:

• Health check shows endpoint as "error"
• Requests fail with connection errors

Diagnosis:

curl http://localhost:12434/health
curl http://localhost:12434/api/config

Solutions:

• Verify Ollama endpoint is running
• Check network connectivity
• Verify firewall rules
• Check DNS resolution
• Test direct connection: curl http://endpoint:11434/api/version

2. Model Not Found

Symptoms:

• Error: "None of the configured endpoints advertise the model"
• Requests fail with model not found

Diagnosis:

curl http://localhost:12434/api/tags
curl http://endpoint:11434/api/tags

Solutions:

• Pull the model on the endpoint: curl http://endpoint:11434/api/pull -d '{"name": "llama3"}'
• Verify model name spelling
• Check if model is available on any endpoint
• For OpenAI endpoints, ensure model exists in their catalog

3. High Latency

Symptoms:

• Slow response times
• Requests timing out

Diagnosis:

curl http://localhost:12434/api/usage
curl http://localhost:12434/api/config

Solutions:

• Check if endpoints are overloaded (high connection counts)
• Increase max_concurrent_connections
• Add more endpoints to the cluster
• Monitor Ollama endpoint performance
• Check network latency between router and endpoints

4. Connection Limits Reached

Symptoms:

• Requests queuing
• High connection counts
• Slow response times

Diagnosis:

curl http://localhost:12434/api/usage

Solutions:

• Increase max_concurrent_connections in config.yaml
• Add more Ollama endpoints
• Scale your Ollama cluster
• Use MOE system for critical queries

5. Token Tracking Not Working

Symptoms:

• Token counts not updating
• Database errors

Diagnosis:

ls -la token_counts.db
curl http://localhost:12434/api/token_counts

Solutions:

• Verify database file permissions
• Check if database path is writable
• Restart router to rebuild database
• Check disk space
• Verify environment variable NOMYO_ROUTER_DB_PATH

6. Streaming Issues

Symptoms:

• Incomplete responses
• Connection resets during streaming
• Timeout errors

Diagnosis:

• Check router logs for errors
• Test with non-streaming requests
• Monitor connection counts

Solutions:

• Increase timeout settings
• Reduce max_concurrent_connections
• Check network stability
• Test with smaller payloads

Error Messages

"Failed to connect to endpoint"

Cause: Network connectivity issue Action: Verify endpoint is reachable, check firewall, test DNS

"None of the configured endpoints advertise the model"

Cause: Model not pulled on any endpoint Action: Pull the model, verify model name

"Timed out waiting for endpoint"

Cause: Endpoint slow to respond Action: Check endpoint health, increase timeouts

"Invalid JSON format in request body"

Cause: Malformed request Action: Validate request payload, check API documentation

"Missing required field 'model'"

Cause: Request missing model parameter Action: Add model parameter to request

Performance Tuning

Optimizing Connection Handling

1. Adjust concurrency limits:

   max_concurrent_connections: 4
   

2. Monitor connection usage:

   curl http://localhost:12434/api/usage
   

3. Scale horizontally:

   • Add more Ollama endpoints
   • Deploy multiple router instances

Reducing Latency

1. Keep models loaded:

   • Use frequently accessed models
   • Monitor /api/ps for loaded models

2. Optimize endpoint selection:

   • Distribute models across endpoints
   • Balance load evenly

3. Use caching:

   • Models cache (300s TTL)
   • Loaded models cache (30s TTL)

Memory Management

1. Monitor memory usage:

   • Token buffer grows with usage
   • Time-series data accumulates

2. Adjust flush interval:

   • Default: 10 seconds
   • Can be increased for less frequent I/O

3. Database maintenance:

   • Regular backups
   • Archive old data periodically

Database Management

Viewing Token Data

sqlite3 token_counts.db "SELECT * FROM token_counts;"
sqlite3 token_counts.db "SELECT * FROM time_series LIMIT 100;"

Aggregating Old Data

curl http://localhost:12434/api/aggregate_time_series_days \
  -X POST \
  -d '{"days": 30, "trim_old": true}'

Backing Up Database

cp token_counts.db token_counts.db.backup

Restoring Database

cp token_counts.db.backup token_counts.db

Advanced Troubleshooting

Debugging Endpoint Selection

Enable debug logging to see endpoint selection decisions:

uvicorn router:app --host 0.0.0.0 --port 12434 --log-level debug

Testing Individual Endpoints

# Test endpoint directly
curl http://endpoint:11434/api/version

# Test model availability
curl http://endpoint:11434/api/tags

# Test model loading
curl http://endpoint:11434/api/ps

Network Diagnostics

# Test connectivity
nc -zv endpoint 11434

# Test DNS resolution
dig endpoint

# Test latency
ping endpoint

Common Pitfalls

1. Using localhost in Docker:

   • Inside Docker, localhost refers to the container itself
   • Use host.docker.internal or Docker service names

2. Incorrect model names:

   • Ollama: llama3:latest
   • OpenAI: gpt-4 (no version suffix)

3. Missing API keys:

   • Remote endpoints require authentication
   • Set keys in config.yaml or environment variables

4. Firewall blocking:

   • Ensure port 11434 is open for Ollama
   • Ensure port 12434 is open for router

5. Insufficient resources:

   • Monitor CPU/memory on Ollama endpoints
   • Adjust max_concurrent_connections accordingly

Best Practices

Monitoring Setup

1. Set up health checks:

   • Monitor /health endpoint
   • Alert on status "error"

2. Track usage metrics:

   • Monitor connection counts
   • Track token usage
   • Watch for connection limits

3. Log important events:

   • Configuration changes
   • Endpoint failures
   • Recovery events

4. Regular backups:

   • Backup token_counts.db
   • Schedule regular backups
   • Test restore procedure

Performance Monitoring

1. Baseline metrics:

   • Establish normal usage patterns
   • Track trends over time

2. Alert thresholds:

   • Set alerts for high connection counts
   • Monitor error rates
   • Watch for latency spikes

3. Capacity planning:

   • Track growth in token usage
   • Plan for scaling needs
   • Monitor resource utilization

Incident Response

1. Quick diagnosis:

   • Check health endpoint first
   • Review recent logs
   • Verify endpoint status

2. Isolation:

   • Identify affected endpoints
   • Isolate problematic components
   • Fallback to healthy endpoints

3. Recovery:

   • Restart router if needed
   • Rebalance load
   • Restore from backup if necessary

Examples

See the examples directory for monitoring configuration examples.