skills/featbit/featbit-skills/featbit-opentelemetry

featbit-opentelemetry

Installation
SKILL.md

FeatBit OpenTelemetry Integration

Guide users in setting up comprehensive observability for FeatBit's backend services using OpenTelemetry to publish metrics, traces, and logs.

Overview

FeatBit's three backend services are fully instrumented with OpenTelemetry:

What you get: Metrics (CPU, memory, network), traces (request flows, latency), and logs (application events, errors).

Quick Start Configuration

To enable OpenTelemetry, set these environment variables for each service:

# Enable OpenTelemetry
ENABLE_OPENTELEMETRY=true

# Service identification (set appropriately for each service)
OTEL_SERVICE_NAME=featbit-api           # For Api service
OTEL_SERVICE_NAME=featbit-els           # For Evaluation-Server
OTEL_SERVICE_NAME=featbit-das           # For Data Analytic service

# Exporter endpoint (gRPC endpoint of OpenTelemetry collector)
OTEL_EXPORTER_OTLP_ENDPOINT=http://otel-collector:4317

Additional configuration options:

Ready-to-Run Example

Try the complete working example with Seq (logs), Jaeger (traces), and Prometheus (metrics):

# Clone the repository
git clone https://github.com/featbit/featbit.git
cd featbit

# Build the test images
docker compose --project-directory . -f ./docker/composes/docker-compose-dev.yml build

# Start OTEL collector, Seq, Jaeger, and Prometheus
docker compose --project-directory . -f ./docker/composes/docker-compose-otel-collector-contrib.yml up -d

# Start FeatBit services with OpenTelemetry enabled
docker compose --project-directory . -f ./docker/composes/docker-compose-otel.yml up -d

After starting, use FeatBit normally (create flags, evaluate, view insights), then access:

Common Use Cases

Setting Up Observability:

  1. Configure environment variables for each FeatBit service
  2. Deploy OpenTelemetry collector to receive telemetry data
  3. Connect to your backend (Seq, Jaeger, Prometheus, Datadog, New Relic, Grafana, or any OTEL-compatible system)

Monitoring & Troubleshooting:

  • Track request latency, throughput, and resource utilization
  • Use traces to identify bottlenecks in request flows
  • Correlate logs with traces for debugging
  • Set up alerts for performance anomalies

Production Deployment:

  • Use unique OTEL_SERVICE_NAME for each service to distinguish telemetry
  • Configure appropriate exporter endpoints (http/https, ports)
  • Set sampling rates to manage data volume
  • Monitor all three services for complete visibility

Best Practices

  1. Always set unique OTEL_SERVICE_NAME for each service
  2. Start with the ready-to-run example to understand the setup before customizing
  3. Configure sampling in production to manage telemetry data volume
  4. Correlate metrics, traces, and logs for comprehensive troubleshooting

References

Weekly Installs
2
GitHub Stars
11
First Seen
Mar 11, 2026
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