# Instrumenting an Application — Prometheus + Grafana

Source: https://www.skillbyai.com/en/prometheus-grafana/i-client

> Client libraries and what to measure.

## Measure requests, errors and duration

Official and community client libraries exist for Go, Java, Python, Ruby, .NET, Node.js and more. Define metrics once at start-up, update them in code paths, and expose them on `/metrics`. For every service, start with the **RED** metrics: request **R**ate, **E**rrors and **D**uration, labelled by a bounded route template (`/orders/{id}`, not the actual ID). Many frameworks have middleware that does this automatically, and OpenTelemetry can export metrics to Prometheus too.

## RED metrics in Python

Using the prometheus_client library (a sketch; adapt to your framework).

```python
from prometheus_client import Counter, Histogram, start_http_server
import time

REQUESTS = Counter("http_requests_total", "HTTP requests", ["route", "method", "status"])
LATENCY = Histogram("http_request_duration_seconds", "Request latency", ["route"],
                    buckets=[0.05, 0.1, 0.25, 0.3, 0.5, 1, 2.5])

def handle(route_template, method, handler):
    start = time.perf_counter()
    status = "500"
    try:
        status = str(handler())
        return status
    finally:
        REQUESTS.labels(route_template, method, status).inc()
        LATENCY.labels(route_template).observe(time.perf_counter() - start)

start_http_server(8000)   # serves /metrics on port 8000
```

## Use route templates, never raw paths

Labelling by /orders/12345 creates a new series per order and can overwhelm Prometheus.

**Quiz:** What do the RED metrics stand for?

- [ ] Requests, Exports, Disks
- [ ] Reads, Edits, Deletes
- [ ] Red, Easy, Done
- [x] Rate, Errors, Duration

*Answer:* Rate, Errors, Duration. A starting set for every service.