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Distributed Tracing

Ahnlich supports distributed tracing using OpenTelemetry for production observability.

Quick Enable​

Add these flags to enable tracing:

# For Ahnlich DB
ahnlich-db run \
  --enable-tracing \
  --otel-endpoint http://jaeger:4317

# For Ahnlich AI  
ahnlich-ai run \
  --enable-tracing \
  --otel-endpoint http://jaeger:4317

Docker Compose Example​

version: "3.8"

services:
  jaeger:
    image: jaegertracing/all-in-one:latest
    ports:
      - "16686:16686"  # Jaeger UI
      - "4317:4317"    # OTLP gRPC receiver

  ahnlich_db:
    image: ghcr.io/deven96/ahnlich-db:latest
    command: >
      ahnlich-db run --host 0.0.0.0
      --enable-tracing
      --otel-endpoint http://jaeger:4317
    ports:
      - "1369:1369"

  ahnlich_ai:
    image: ghcr.io/deven96/ahnlich-ai:latest
    command: >
      ahnlich-ai run --host 0.0.0.0
      --db-host ahnlich_db
      --enable-tracing
      --otel-endpoint http://jaeger:4317
    ports:
      - "1370:1370"

Access Jaeger UI at http://localhost:16686

What Gets Traced​

  • Client requests and responses
  • DB operations (similarity search, indexing)
  • AI model inference (embedding generation)
  • Inter-service communication (AI → DB)

Detailed Documentation​

For comprehensive tracing setup and configuration:

Production Tips​

  1. Use a dedicated collector - Don't send traces directly to Jaeger in production
  2. Sample traces - Configure sampling to reduce overhead (not yet configurable, coming soon)
  3. Aggregate traces - Use centralized tracing backends (Jaeger, Tempo, Honeycomb)
  4. Monitor overhead - Tracing adds ~5-10% latency overhead