docs/ADVANCED_MONITORING.md

Advanced Monitoring & Alerting Guide

Date: 2025-01-27 Purpose: Guide for advanced monitoring and alerting setup Status: Complete

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Overview

This guide provides strategies for implementing advanced monitoring and alerting across the integrated workspace.

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Monitoring Stack

Components

1. Prometheus - Metrics collection
2. Grafana - Visualization and dashboards
3. Loki - Log aggregation
4. Alertmanager - Alert routing
5. Jaeger - Distributed tracing

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Metrics Collection

Application Metrics

Custom Metrics

import { Counter, Histogram } from 'prom-client';

const requestCounter = new Counter({
  name: 'http_requests_total',
  help: 'Total HTTP requests',
  labelNames: ['method', 'route', 'status'],
});

const requestDuration = new Histogram({
  name: 'http_request_duration_seconds',
  help: 'HTTP request duration',
  labelNames: ['method', 'route'],
});

Business Metrics

• Transaction volume
• User activity
• Revenue metrics
• Conversion rates

Infrastructure Metrics

System Metrics

• CPU usage
• Memory usage
• Disk I/O
• Network traffic

Kubernetes Metrics

• Pod status
• Resource usage
• Node health
• Cluster capacity

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Dashboards

Application Dashboard

Key Panels:

• Request rate
• Response times (p50, p95, p99)
• Error rates
• Active users

Infrastructure Dashboard

Key Panels:

• Resource utilization
• Pod status
• Node health
• Network traffic

Business Dashboard

Key Panels:

• Transaction volume
• Revenue metrics
• User activity
• Conversion rates

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Alerting Rules

Critical Alerts

groups:
  - name: critical
    rules:
      - alert: HighErrorRate
        expr: rate(http_requests_total{status=~"5.."}[5m]) > 0.1
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "High error rate detected"

      - alert: ServiceDown
        expr: up{job="api"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Service is down"

Warning Alerts

      - alert: HighLatency
        expr: histogram_quantile(0.95, http_request_duration_seconds) > 1
        for: 10m
        labels:
          severity: warning
        annotations:
          summary: "High latency detected"

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Log Aggregation

Structured Logging

import winston from 'winston';

const logger = winston.createLogger({
  format: winston.format.json(),
  transports: [
    new winston.transports.Console(),
  ],
});

logger.info('Request processed', {
  method: 'GET',
  path: '/api/users',
  status: 200,
  duration: 45,
  userId: '123',
});

Log Levels

• ERROR: Errors requiring attention
• WARN: Warnings
• INFO: Informational messages
• DEBUG: Debug information

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Distributed Tracing

OpenTelemetry

import { trace } from '@opentelemetry/api';

const tracer = trace.getTracer('my-service');

const span = tracer.startSpan('process-request');
try {
  // Process request
  span.setStatus({ code: SpanStatusCode.OK });
} catch (error) {
  span.setStatus({ code: SpanStatusCode.ERROR });
  span.recordException(error);
} finally {
  span.end();
}

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Best Practices

Metrics

• Use consistent naming
• Include relevant labels
• Avoid high cardinality
• Document metrics

Alerts

• Set appropriate thresholds
• Avoid alert fatigue
• Use alert grouping
• Test alert delivery

Logs

• Use structured logging
• Include correlation IDs
• Don't log sensitive data
• Set appropriate levels

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Last Updated: 2025-01-27