---
name: Monitoring & Observability
slug: monitoring-observability
category: DevOps
description: Monitoring & Observability provides patterns for instrumenting Node.js services with OpenTelemetry, Prometheus metrics, Grafana dashboards, and structured logging. Use it when setting up observability for backend services or defining alerting rules based on SLOs.
github: "https://github.com/rohitg00/awesome-claude-code-toolkit/tree/main/skills/monitoring-observability"
language: JavaScript
stars: 2525
forks: 898
install: "npx degit https://github.com/rohitg00/awesome-claude-code-toolkit/tree/main/skills/monitoring-observability ~/.claude/skills/monitoring-observability"
installs_to: ~/.claude/skills/monitoring-observability
source_path: skills/monitoring-observability/SKILL.md
collection_size: 25
category_size: 798
collection_url: "https://dirskills.com/collections/rohitg00/awesome-claude-code-toolkit"
added: 2026-08-18T06:57:43.065Z
last_synced: 2026-08-18T06:57:43.065Z
canonical_url: "https://dirskills.com/skills/monitoring-observability"
---

# Monitoring & Observability

Monitoring & Observability provides patterns for instrumenting Node.js services with OpenTelemetry, Prometheus metrics, Grafana dashboards, and structured logging. Use it when setting up observability for backend services or defining alerting rules based on SLOs.

**Install:**

```bash
npx degit https://github.com/rohitg00/awesome-claude-code-toolkit/tree/main/skills/monitoring-observability ~/.claude/skills/monitoring-observability
```

## README

# Monitoring & Observability

## OpenTelemetry Setup

```typescript
import { NodeSDK } from "@opentelemetry/sdk-node";
import { OTLPTraceExporter } from "@opentelemetry/exporter-trace-otlp-http";
import { OTLPMetricExporter } from "@opentelemetry/exporter-metrics-otlp-http";
import { HttpInstrumentation } from "@opentelemetry/instrumentation-http";
import { PgInstrumentation } from "@opentelemetry/instrumentation-pg";
import { PeriodicExportingMetricReader } from "@opentelemetry/sdk-metrics";

const sdk = new NodeSDK({
  serviceName: "order-service",
  traceExporter: new OTLPTraceExporter({
    url: "http://otel-collector:4318/v1/traces",
  }),
  metricReader: new PeriodicExportingMetricReader({
    exporter: new OTLPMetricExporter({
      url: "http://otel-collector:4318/v1/metrics",
    }),
    exportIntervalMillis: 15000,
  }),
  instrumentations: [
    new HttpInstrumentation(),
    new PgInstrumentation(),
  ],
});

sdk.start();
process.on("SIGTERM", () => sdk.shutdown());
```

## Custom Spans and Metrics

```typescript
import { trace, metrics, SpanStatusCode } from "@opentelemetry/api";

const tracer = trace.getTracer("order-service");
const meter = metrics.getMeter("order-service");

const orderCounter = meter.createCounter("orders.created", {
  description: "Number of orders created",
});

const orderDuration = meter.createHistogram("orders.processing_duration_ms", {
  description: "Order processing duration in milliseconds",
  unit: "ms",
});

async function createOrder(input: CreateOrderInput) {
  return tracer.startActiveSpan("createOrder", async (span) => {
    try {
      span.setAttributes({
        "order.customer_id": input.customerId,
        "order.item_count": input.items.length,
      });

      const start = performance.now();
      const order = await db.order.create({ data: input });

      orderCounter.add(1, { status: "success" });
      orderDuration.record(performance.now() - start);

      span.setStatus({ code: SpanStatusCode.OK });
      return order;
    } catch (error) {
      span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
      orderCounter.add(1, { status: "error" });
      throw error;
    } finally {
      span.end();
    }
  });
}
```

## Prometheus Metrics

```yaml
# prometheus.yml
global:
  scrape_interval: 15s

scrape_configs:
  - job_name: "api-servers"
    static_configs:
      - targets: ["api-1:9090", "api-2:9090"]
    metrics_path: /metrics

  - job_name: "node-exporter"
    static_configs:
      - targets: ["node-exporter:9100"]
```

```typescript
import { collectDefaultMetrics, Counter, Histogram, Registry } from "prom-client";

const registry = new Registry();
collectDefaultMetrics({ register: registry });

const httpRequestDuration = new Histogram({
  name: "http_request_duration_seconds",
  help: "HTTP request duration in seconds",
  labelNames: ["method", "route", "status"],
  buckets: [0.01, 0.05, 0.1, 0.5, 1, 5],
  registers: [registry],
});

app.use((req, res, next) => {
  const end = httpRequestDuration.startTimer();
  res.on("finish", () => {
    end({ method: req.method, route: req.route?.path ?? req.path, status: res.statusCode });
  });
  next();
});

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

## Structured Logging

```typescript
import pino from "pino";

const logger = pino({
  level: process.env.LOG_LEVEL ?? "info",
  formatters: {
    level: (label) => ({ level: label }),
  },
  redact: ["req.headers.authorization", "password", "token"],
});

function requestLogger(req, res, next) {
  const start = Date.now();
  res.on("finish", () => {
    logger.info({
      method: req.method,
      url: req.url,
      status: res.statusCode,
      duration_ms: Date.now() - start,
      trace_id: req.headers["x-trace-id"],
    });
  });
  next();
}
```

## Alerting Rules

```yaml
groups:
  - name: api-alerts
    rules:
      - alert: HighErrorRate
        expr: rate(http_request_duration_seconds_count{status=~"5.."}[5m]) / rate(http_request_duration_seconds_count[5m]) > 0.05
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "Error rate above 5% for {{ $labels.route }}"

      - alert: HighLatency
        expr: histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m])) > 2
        for: 10m
        labels:
          severity: warning
```

## Anti-Patterns

- Logging sensitive data (passwords, tokens, PII) without redaction
- Using string interpolation in log messages instead of structured fields
- Creating unbounded cardinality in metric labels (e.g., user IDs as labels)
- Not correlating logs and traces with a shared trace ID
- Alerting on symptoms (high CPU) without understanding root cause
- Missing SLO definitions before building dashboards

## Checklist

- [ ] OpenTelemetry SDK initialized with auto-instrumentation for HTTP, DB, and messaging
- [ ] Custom spans added for business-critical operations
- [ ] Metrics use bounded label cardinality
- [ ] Structured logging with JSON output and secret redaction
- [ ] Trace context propagated across service boundaries
- [ ] Alerting rules based on SLOs (error rate, latency percentiles)
- [ ] Dashboards show RED metrics (Rate, Errors, Duration) per service
- [ ] Log retention and rotation policies configured