Modern Monitoring Practices (2024+)

OpenTelemetry Implementation

Collector Configuration

apiVersion: opentelemetry.io/v1alpha1
kind: OpenTelemetryCollector
metadata:
  name: modern-collector
spec:
  mode: deployment
  config: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: 0.0.0.0:4317
          http:
            endpoint: 0.0.0.0:4318
            
    processors:
      batch:
        timeout: 1s
      memory_limiter:
        check_interval: 1s
        limit_mib: 1000
      
    exporters:
      prometheus:
        endpoint: "0.0.0.0:8889"
      otlp:
        endpoint: tempo.monitoring.svc.cluster.local:4317
        tls:
          insecure: true
      loki:
        endpoint: http://loki-gateway.monitoring.svc.cluster.local:3100/loki/api/v1/push
        
    service:
      pipelines:
        traces:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [otlp]
        metrics:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [prometheus]
        logs:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [loki]

AI-Powered Monitoring

Anomaly Detection

apiVersion: monitoring.coreos.com/v1
kind: PrometheusRule
metadata:
  name: ai-anomaly-detection
spec:
  groups:
  - name: AIAnomalyDetection
    rules:
    - alert: AnomalousLatency
      expr: |
        rate(http_request_duration_seconds_sum[5m])
        / 
        rate(http_request_duration_seconds_count[5m])
        > on(service) group_left
        avg_over_time(http_request_duration_seconds_sum[7d])
        /
        avg_over_time(http_request_duration_seconds_count[7d])
        * 2
      for: 15m
      labels:
        severity: warning
      annotations:
        summary: Anomalous latency detected

Service Level Objectives

SLO Configuration

apiVersion: monitoring.googleapis.com/v1
kind: ServiceLevelObjective
metadata:
  name: api-availability
spec:
  service: api-service
  goal: 0.999
  window: 30d
  indicator:
    latencyThreshold: 500ms
    availability:
      count: good_count
      total: total_count

Best Practices

1. Data Collection
   • Unified telemetry
   • Auto-instrumentation
   • Context propagation
   • Sampling strategies
2. Analysis
   • ML-based analysis
   • Pattern recognition
   • Predictive alerts
   • Correlation engine
3. Visualization
   • Real-time dashboards
   • Service maps
   • Alert correlation
   • Custom widgets
4. Action
   • Automated responses
   • Incident management
   • Runbook automation
   • Team notification