Uygulama Monitoring: Prometheus, Grafana ve Alerting

Monitoring Neden Kritik?

Monitoring olmadan production'da kör uçuş yaparsınız. Sorunları kullanıcılardan önce tespit etmek için kapsamlı izleme şarttır.

Monitoring Stack

• Prometheus: Metrics collection ve storage
• Grafana: Visualization ve dashboards
• AlertManager: Alert routing ve notification
• Loki: Log aggregation

Prometheus Kurulumu

# docker-compose.yml
services:
  prometheus:
    image: prom/prometheus:latest
    ports:
      - "9090:9090"
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml
      - prometheus_data:/prometheus
    command:
      - "--config.file=/etc/prometheus/prometheus.yml"
      - "--storage.tsdb.retention.time=15d"

  grafana:
    image: grafana/grafana:latest
    ports:
      - "3000:3000"
    volumes:
      - grafana_data:/var/lib/grafana
    environment:
      - GF_SECURITY_ADMIN_PASSWORD=secret

volumes:
  prometheus_data:
  grafana_data:

prometheus.yml

global:
  scrape_interval: 15s
  evaluation_interval: 15s

alerting:
  alertmanagers:
    - static_configs:
        - targets:
          - alertmanager:9093

rule_files:
  - "alerts/*.yml"

scrape_configs:
  - job_name: "prometheus"
    static_configs:
      - targets: ["localhost:9090"]

  - job_name: "laravel"
    static_configs:
      - targets: ["app:9000"]
    metrics_path: /metrics

  - job_name: "nginx"
    static_configs:
      - targets: ["nginx-exporter:9113"]

  - job_name: "mysql"
    static_configs:
      - targets: ["mysql-exporter:9104"]

Laravel Metrics

// composer require spatie/laravel-prometheus

// routes/web.php
Route::get("/metrics", function () {
    return response(Prometheus::export(), 200, [
        "Content-Type" => "text/plain; version=0.0.4"
    ]);
})->middleware("auth.basic");

// app/Providers/PrometheusServiceProvider.php
public function boot()
{
    // Request duration histogram
    Prometheus::histogram("http_request_duration_seconds")
        ->labels(["method", "route", "status"])
        ->observe(microtime(true) - LARAVEL_START);

    // Active users gauge
    Prometheus::gauge("active_users_total")
        ->set(User::where("last_seen_at", ">", now()->subMinutes(5))->count());

    // Queue jobs counter
    Prometheus::counter("queue_jobs_total")
        ->labels(["queue", "status"])
        ->increment();
}

Alert Rules

# alerts/app.yml
groups:
  - name: application
    rules:
      - alert: HighErrorRate
        expr: |
          sum(rate(http_requests_total{status=~"5.."}[5m]))
          / sum(rate(http_requests_total[5m])) > 0.05
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "High error rate detected"
          description: "Error rate is {{ $value | humanizePercentage }}"

      - alert: SlowResponseTime
        expr: |
          histogram_quantile(0.95,
            rate(http_request_duration_seconds_bucket[5m])
          ) > 2
        for: 10m
        labels:
          severity: warning
        annotations:
          summary: "Slow response times"
          description: "95th percentile latency is {{ $value }}s"

      - alert: HighMemoryUsage
        expr: |
          (node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)
          / node_memory_MemTotal_bytes > 0.9
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "High memory usage"

AlertManager Config

# alertmanager.yml
global:
  slack_api_url: "https://hooks.slack.com/services/xxx"

route:
  receiver: "slack-notifications"
  group_by: ["alertname", "severity"]
  group_wait: 30s
  group_interval: 5m
  repeat_interval: 4h

  routes:
    - match:
        severity: critical
      receiver: "pagerduty"
    - match:
        severity: warning
      receiver: "slack-notifications"

receivers:
  - name: "slack-notifications"
    slack_configs:
      - channel: "#alerts"
        title: "{{ .GroupLabels.alertname }}"
        text: "{{ .CommonAnnotations.description }}"

  - name: "pagerduty"
    pagerduty_configs:
      - service_key: "xxx"

Grafana Dashboard

Önemli paneller:

• Request rate (RPM)
• Error rate percentage
• Response time (p50, p95, p99)
• CPU ve memory kullanımı
• Database query performansı
• Queue backlog

Sonuç

Monitoring, production sistemlerinin vazgeçilmez parçasıdır. Prometheus + Grafana kombinasyonu ile hem metriklerinizi izleyin hem de proaktif alerting kurun.