# Observability Across Services — Monolith vs Microservices

Source: https://www.skillbyai.com/en/monolith-microservices/r-observe

> Trace requests across services and centralise logs and metrics.

## One request, many services

Debugging a monolith often means reading one log file. In microservices, one user request may touch ten services, each with many instances. You need three things working together. **Distributed tracing**: each request carries a trace ID (the W3C `traceparent` header), every service records spans, and a tracing backend (Jaeger, Grafana Tempo, Zipkin, or a commercial tool) shows the whole path with timings; **OpenTelemetry** provides vendor-neutral SDKs and auto-instrumentation. **Centralised, structured logs** that include the trace ID and service name, so you can jump from a slow span to its logs. **Metrics** per service using RED (rate, errors, duration) plus saturation, with SLOs and alerts owned by the service's team. Add **service catalogues** (such as Backstage) listing owners, dashboards, runbooks and dependencies so on-call engineers know who to call.

## OpenTelemetry auto-instrumentation for a Python service

Spans for incoming and outgoing HTTP calls are created and linked automatically.

```bash
pip install opentelemetry-distro opentelemetry-exporter-otlp
opentelemetry-bootstrap -a install          # adds instrumentations for detected libraries

export OTEL_SERVICE_NAME=checkout
export OTEL_EXPORTER_OTLP_ENDPOINT=http://otel-collector.observability:4317
export OTEL_RESOURCE_ATTRIBUTES=deployment.environment=prod,service.version=1.8.2

opentelemetry-instrument gunicorn app:app --bind 0.0.0.0:8080
```

## Put the trace ID in every log line

When a customer reports an error, a trace ID in the error page or response header lets support find every related log line across all services in seconds.

**Quiz:** What lets you see the full path and timing of one request across many services?

- [x] Distributed tracing with propagated trace context
- [ ] A bigger log file
- [ ] More CPU
- [ ] A shared database

*Answer:* Distributed tracing with propagated trace context. Trace context propagated between services links spans into one end-to-end trace.