Prometheus Configuration
Complete guide to Prometheus setup, metric collection, scrape configuration, and recording rules.
Purpose
Configure Prometheus for comprehensive metric collection, alerting, and monitoring of infrastructure and applications.
When to Use Set up Prometheus monitoring Configure metric scraping Create recording rules Design alert rules Implement service discovery Prometheus Architecture ┌──────────────┐ │ Applications │ ← Instrumented with client libraries └──────┬───────┘ │ /metrics endpoint ↓ ┌──────────────┐ │ Prometheus │ ← Scrapes metrics periodically │ Server │ └──────┬───────┘ │ ├─→ AlertManager (alerts) ├─→ Grafana (visualization) └─→ Long-term storage (Thanos/Cortex)
Installation Kubernetes with Helm helm repo add prometheus-community https://prometheus-community.github.io/helm-charts helm repo update
helm install prometheus prometheus-community/kube-prometheus-stack \ --namespace monitoring \ --create-namespace \ --set prometheus.prometheusSpec.retention=30d \ --set prometheus.prometheusSpec.storageVolumeSize=50Gi
Docker Compose version: "3.8" 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.path=/prometheus" - "--storage.tsdb.retention.time=30d"
volumes: prometheus-data:
Configuration File
prometheus.yml:
global: scrape_interval: 15s evaluation_interval: 15s external_labels: cluster: "production" region: "us-west-2"
Alertmanager configuration
alerting: alertmanagers: - static_configs: - targets: - alertmanager:9093
Load rules files
rule_files: - /etc/prometheus/rules/*.yml
Scrape configurations
scrape_configs: # Prometheus itself - job_name: "prometheus" static_configs: - targets: ["localhost:9090"]
# Node exporters - job_name: "node-exporter" static_configs: - targets: - "node1:9100" - "node2:9100" - "node3:9100" relabel_configs: - source_labels: [address] target_label: instance regex: "([^:]+)(:[0-9]+)?" replacement: "${1}"
# Kubernetes pods with annotations - job_name: "kubernetes-pods" kubernetes_sd_configs: - role: pod relabel_configs: - source_labels: [meta_kubernetes_pod_annotation_prometheus_io_scrape] action: keep regex: true - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path] action: replace target_label: __metrics_path regex: (.+) - source_labels: [address, meta_kubernetes_pod_annotation_prometheus_io_port] action: replace regex: ([^:]+)(?::\d+)?;(\d+) replacement: $1:$2 target_label: __address - source_labels: [__meta_kubernetes_namespace] action: replace target_label: namespace - source_labels: [__meta_kubernetes_pod_name] action: replace target_label: pod
# Application metrics - job_name: "my-app" static_configs: - targets: - "app1.example.com:9090" - "app2.example.com:9090" metrics_path: "/metrics" scheme: "https" tls_config: ca_file: /etc/prometheus/ca.crt cert_file: /etc/prometheus/client.crt key_file: /etc/prometheus/client.key
Reference: See assets/prometheus.yml.template
Scrape Configurations Static Targets scrape_configs: - job_name: "static-targets" static_configs: - targets: ["host1:9100", "host2:9100"] labels: env: "production" region: "us-west-2"
File-based Service Discovery scrape_configs: - job_name: "file-sd" file_sd_configs: - files: - /etc/prometheus/targets/.json - /etc/prometheus/targets/.yml refresh_interval: 5m
targets/production.json:
[ { "targets": ["app1:9090", "app2:9090"], "labels": { "env": "production", "service": "api" } } ]
Kubernetes Service Discovery scrape_configs: - job_name: "kubernetes-services" kubernetes_sd_configs: - role: service relabel_configs: - source_labels: [meta_kubernetes_service_annotation_prometheus_io_scrape] action: keep regex: true - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme] action: replace target_label: __scheme regex: (https?) - source_labels: [meta_kubernetes_service_annotation_prometheus_io_path] action: replace target_label: __metrics_path regex: (.+)
Reference: See references/scrape-configs.md
Recording Rules
Create pre-computed metrics for frequently queried expressions:
/etc/prometheus/rules/recording_rules.yml
groups: - name: api_metrics interval: 15s rules: # HTTP request rate per service - record: job:http_requests:rate5m expr: sum by (job) (rate(http_requests_total[5m]))
# Error rate percentage
- record: job:http_requests_errors:rate5m
expr: sum by (job) (rate(http_requests_total{status=~"5.."}[5m]))
- record: job:http_requests_error_rate:percentage
expr: |
(job:http_requests_errors:rate5m / job:http_requests:rate5m) * 100
# P95 latency
- record: job:http_request_duration:p95
expr: |
histogram_quantile(0.95,
sum by (job, le) (rate(http_request_duration_seconds_bucket[5m]))
)
-
name: resource_metrics interval: 30s rules: # CPU utilization percentage
- record: instance:node_cpu:utilization expr: | 100 - (avg by (instance) (rate(node_cpu_seconds_total{mode="idle"}[5m])) * 100)
# Memory utilization percentage - record: instance:node_memory:utilization expr: | 100 - ((node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes) * 100)
# Disk usage percentage - record: instance:node_disk:utilization expr: | 100 - ((node_filesystem_avail_bytes / node_filesystem_size_bytes) * 100)
Reference: See references/recording-rules.md
Alert Rules
/etc/prometheus/rules/alert_rules.yml
groups: - name: availability interval: 30s rules: - alert: ServiceDown expr: up{job="my-app"} == 0 for: 1m labels: severity: critical annotations: summary: "Service {{ $labels.instance }} is down" description: "{{ $labels.job }} has been down for more than 1 minute"
- alert: HighErrorRate
expr: job:http_requests_error_rate:percentage > 5
for: 5m
labels:
severity: warning
annotations:
summary: "High error rate for {{ $labels.job }}"
description: "Error rate is {{ $value }}% (threshold: 5%)"
- alert: HighLatency
expr: job:http_request_duration:p95 > 1
for: 5m
labels:
severity: warning
annotations:
summary: "High latency for {{ $labels.job }}"
description: "P95 latency is {{ $value }}s (threshold: 1s)"
-
name: resources interval: 1m rules:
-
alert: HighCPUUsage expr: instance:node_cpu:utilization > 80 for: 5m labels: severity: warning annotations: summary: "High CPU usage on {{ $labels.instance }}" description: "CPU usage is {{ $value }}%"
-
alert: HighMemoryUsage expr: instance:node_memory:utilization > 85 for: 5m labels: severity: warning annotations: summary: "High memory usage on {{ $labels.instance }}" description: "Memory usage is {{ $value }}%"
-
alert: DiskSpaceLow expr: instance:node_disk:utilization > 90 for: 5m labels: severity: critical annotations: summary: "Low disk space on {{ $labels.instance }}" description: "Disk usage is {{ $value }}%"
-
Validation
Validate configuration
promtool check config prometheus.yml
Validate rules
promtool check rules /etc/prometheus/rules/*.yml
Test query
promtool query instant http://localhost:9090 'up'
Reference: See scripts/validate-prometheus.sh
Best Practices Use consistent naming for metrics (prefix_name_unit) Set appropriate scrape intervals (15-60s typical) Use recording rules for expensive queries Implement high availability (multiple Prometheus instances) Configure retention based on storage capacity Use relabeling for metric cleanup Monitor Prometheus itself Implement federation for large deployments Use Thanos/Cortex for long-term storage Document custom metrics Troubleshooting
Check scrape targets:
curl http://localhost:9090/api/v1/targets
Check configuration:
curl http://localhost:9090/api/v1/status/config
Test query:
curl 'http://localhost:9090/api/v1/query?query=up'
Reference Files assets/prometheus.yml.template - Complete configuration template references/scrape-configs.md - Scrape configuration patterns references/recording-rules.md - Recording rule examples scripts/validate-prometheus.sh - Validation script Related Skills grafana-dashboards - For visualization slo-implementation - For SLO monitoring distributed-tracing - For request tracing