implementing-observability

# Production Observability with OpenTelemetry

## Purpose

Implement production-grade observability using OpenTelemetry as the 2025 industry standard. Covers the three pillars (metrics, logs, traces), LGTM stack deployment, and critical log-trace correlation patterns.

## When to Use

Use when:
- Building production systems requiring visibility into performance and errors
- Debugging distributed systems with multiple services
- Setting up monitoring, logging, or tracing infrastructure
- Implementing structured logging with trace correlation
- Configuring alerting rules for production systems

Skip if:
- Building proof-of-concept without production deployment
- System has < 100 requests/day (console logging may suffice)

## The OpenTelemetry Standard (2025)

OpenTelemetry is the CNCF graduated project unifying observability:

```
┌────────────────────────────────────────────────────────┐
│          OpenTelemetry: The Unified Standard           │
├────────────────────────────────────────────────────────┤
│                                                         │
│  ONE SDK for ALL signals:                              │
│  ├── Metrics (Prometheus-compatible)                   │
│  ├── Logs (structured, correlated)                     │
│  ├── Traces (distributed, standardized)                │
│  └── Context (propagates across services)              │
│                                                         │
│  Language SDKs:                                         │
│  ├── Python: opentelemetry-api, opentelemetry-sdk      │
│  ├── Rust: opentelemetry, tracing-opentelemetry        │
│  ├── Go: go.opentelemetry.io/otel                      │
│  └── TypeScript: @opentelemetry/api                    │
│                                                         │
│  Export to ANY backend:                                │
│  ├── LGTM Stack (Loki, Grafana, Tempo, Mimir)          │
│  ├── Prometheus + Jaeger                               │
│  ├── Datadog, New Relic, Honeyco