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Overview

The BE Monorepo implements a complete observability solution using OpenTelemetry for instrumentation and the Grafana LGTM stack for visualization and analysis.

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Observability Stack

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OpenTelemetry

OpenTelemetry is used as the instrumentation layer, providing:
  • Distributed Tracing: Track requests across services
  • Metrics Collection: Monitor system performance
  • Structured Logging: Correlated logs with traces

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Grafana LGTM Stack

The LGTM stack provides a unified observability backend:
  • Loki: Log aggregation and querying
  • Grafana: Visualization and dashboards
  • Tempo: Distributed tracing backend
  • Mimir/Prometheus: Metrics storage and querying
  • Pyroscope: Continuous profiling

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Architecture

┌─────────────────┐
│   Hono App      │
│  (Port 3333)    │
└────────┬────────┘
         │ OTLP Protocol
         │ (HTTP/gRPC)
         ▼
┌─────────────────┐
│  otel-lgtm      │
│  - Port 4317    │ ◄── gRPC
│  - Port 4318    │ ◄── HTTP
└────────┬────────┘
         │
         ├──► Tempo (Traces)
         ├──► Loki (Logs)
         ├──► Prometheus (Metrics)
         └──► Pyroscope (Profiles)
         
┌─────────────────┐
│  Grafana UI     │
│  localhost:3111 │
└─────────────────┘

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Why Observability Matters

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1. Debugging Production Issues

With distributed tracing, you can:
  • Track requests across multiple services
  • Identify bottlenecks and slow operations
  • Correlate logs with specific traces
  • Understand the full request lifecycle

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2. Performance Monitoring

Metrics help you:
  • Monitor HTTP request durations
  • Track error rates by endpoint
  • Identify database query performance issues
  • Set up alerts for anomalies

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3. Proactive Problem Detection

Structured logging enables:
  • Quick searching and filtering
  • Pattern recognition
  • Anomaly detection
  • Historical analysis

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4. Business Intelligence

Observability data provides:
  • Usage patterns
  • User behavior insights
  • Feature adoption metrics
  • System capacity planning

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Key Features

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Automatic Instrumentation

The application automatically instruments:
  • HTTP requests (incoming and outgoing)
  • Database queries (PostgreSQL)
  • DNS lookups
  • Network operations
  • Node.js runtime metrics

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Context Propagation

Trace context is automatically propagated:
  • Between HTTP requests
  • Across async operations
  • Through middleware chains
  • To external services

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Resource Attributes

All telemetry data includes:
  • Service name and version
  • Request ID for correlation
  • HTTP method and route
  • Status codes
  • Custom attributes

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Getting Started

To start using observability:
  1. Start the LGTM stack: See Grafana Setup
  2. Configure logging: See Logging
  3. Add custom traces: See Tracing
  4. Create custom metrics: See Metrics

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Configuration

The observability stack is configured through environment variables: 
# OpenTelemetry Configuration
OTEL_LOG_LEVEL=info
OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318
OTEL_SERVICE_NAME=be-monorepo
OTEL_SERVICE_VERSION=1.0.0

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Next Steps

Logging

Learn about structured logging with OpenTelemetry

Tracing

Implement distributed tracing in your code

Metrics

Collect and visualize custom metrics

Grafana Setup

Set up and access Grafana dashboards

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