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observability-setup

observability-setup

github.com/patricio0312revCloud & DevOps63276 installsUpdated 41w ago
Repository

About observability-setup

observability-setup is a skill for configuring application observability across traces, metrics, and logs. It provides implementation examples and an output checklist for teams setting up instrumentation, dashboards, and alerts.

Key features

  1. 01OpenTelemetry tracing setup
  2. 02Prometheus metric instrumentation
  3. 03Structured logging with pino
  4. 04Grafana dashboard example
  5. 05Alert rule examples

Use cases

  1. 01Instrumenting an API with traces and metrics
  2. 02Adding structured logs to an application
  3. 03Drafting dashboards and alert rules

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/patricio0312rev/skills --skill observability-setup

After installing, type/observability-setupin Claude Code to confirm it loaded.

Details

From the project README

Observability Setup

Implement the three pillars: Traces, Metrics, and Logs.

OpenTelemetry Tracing

// tracing.ts
import { NodeTracerProvider } from "@opentelemetry/sdk-trace-node";
import { Resource } from "@opentelemetry/resources";
import { SemanticResourceAttributes } from "@opentelemetry/semantic-conventions";
import { registerInstrumentations } from "@opentelemetry/instrumentation";
import { HttpInstrumentation } from "@opentelemetry/instrumentation-http";
import { ExpressInstrumentation } from "@opentelemetry/instrumentation-express";
import { PrismaInstrumentation } from "@prisma/instrumentation";

const provider = new NodeTracerProvider({
  resource: new Resource({
    [SemanticResourceAttributes.SERVICE_NAME]: "my-api",
    [SemanticResourceAttributes.SERVICE_VERSION]: "1.0.0",
  }),
});

registerInstrumentations({
  instrumentations: [
    new HttpInstrumentation(),
    new ExpressInstrumentation(),
    new PrismaInstrumentation(),
  ],
});

provider.register();

// Custom spans
import { trace } from "@opentelemetry/api";

const tracer = trace.getTracer("my-app");

async function processOrder(orderId: string) {
  const span = tracer.startSpan("processOrder");
  span.setAttribute("order.id", orderId);

  try {
    await validateOrder(orderId);
    await chargePayment(orderId);
    await fulfillOrder(orderId);
    span.setStatus({ code: 0 }); // OK
  } catch (error) {
    span.setStatus({ code: 2, message: error.message }); // ERROR
    throw error;
  } finally {
    span.end();
  }
}

Prometheus Metrics

// metrics.ts
import { Registry, Counter, Histogram, Gauge } from "prom-client";

const register = new Registry();

// HTTP request counter
export const httpRequestCounter = new Counter({
  name: "http_requests_total",
  help: "Total HTTP requests",
  labelNames: ["method", "route", "status_code"],
  registers: [register],
});

// HTTP request duration
export const httpRequestDuration = new Histogram({
  name: "http_request_duration_seconds",
  help: "HTTP request duration in seconds",
  labelNames: ["method", "route", "status_code"],
  buckets: [0.1, 0.5, 1, 2, 5, 10],
  registers: [register],
});

// Active connections
export const activeConnections = new Gauge({
  name: "active_connections",
  help: "Number of active connections",
  registers: [register],
});

// Business metrics
export const ordersProcessed = new Counter({
  name: "orders_processed_total",
  help: "Total orders processed",
  labelNames: ["status"],
  registers: [register],
});

// Middleware
app.use((req, res, next) => {
  const start = Date.now();

  res.on("finish", () => {
    const duration = (Date.now() - start) / 1000;
    const route = req.route?.path || "unknown";

    httpRequestCounter.inc({
      method: req.method,
      route,
      status_code: res.statusCode,
    });

    httpRequestDuration.observe(
      { method: req.method, route, status_code: res.statusCode },
      duration
    );
  });

  next();
});

// Metrics endpoint
app.get("/metrics", async (req, res) => {
  res.set("Content-Type", register.contentType);
  res.end(await register.metrics());
});

Structured Logging

// logger.ts
import pino from "pino";

export const logger = pino({
  level: process.env.LOG_LEVEL || "info",
  formatters: {
    level: (label) => ({ level: label }),
  },
  base: {
    service: "my-api",
    environment: process.env.NODE_ENV,
  },
});

// Usage
logger.info({ userId: "123", action: "login" }, "User logged in");
logger.error({ err: error, orderId: "456" }, "Order processing failed");

Sample Dashboard (Grafana)

{
  "dashboard": {
    "title": "API Overview",
    "panels": [
      {
        "title": "Request Rate",
        "targets": [{
          "expr": "rate(http_requests_total[5m])"
        }]
      },
      {
        "title": "Error Rate",
        "targets": [{
          "expr": "rate(http_requests_total{status_code=~"5.."}[5m])"
        }]
      },
      {
        "title": "p95 Latency",
        "targets": [{
          "expr": "histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m]))"
        }]
      },
      {
        "title": "Active Connections",
        "targets": [{
          "expr": "active_connections"
        }]
      }
    ]
  }
}

Alert Candidates

# alerts.yml
groups:
  - name: api_alerts
    interval: 30s
    rules:
      - alert: HighErrorRate
        expr: rate(http_requests_total{status_code=~"5.."}[5m]) > 0.05
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "High error rate detected"

      - alert: HighLatency
        expr: histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m])) > 2
        for: 10m
        labels:
          severity: warning
        annotations:
          summary: "p95 latency above 2s"

      - alert: LowAvailability
        expr: rate(http_requests_total{status_code="200"}[5m]) / rate(http_requests_total[5m]) < 0.95
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "Availability below 95%"

Output Checklist

  • OpenTelemetry tracing configured
  • Prometheus metrics instrumented
  • Structured logging implemented
  • Sample dashboards created
  • Alert rules defined
  • Metrics endpoint exposed
  • Instrumentation tested ENDFILE

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