Prometheus

Overview When selecting a monitoring system, one of the most debated questions is “commercial platform or self-hosted open-source.” Datadog is the benchmark for commercial observability platforms — out-of-the-box, feature-complete, with rich integrations, but at a premium price. Prometheus + Grafana represents the open-source self-hosted approach — flexible, controllable, with no license fees, but requiring investment in operations personnel. This isn’t a simple “save money vs save effort” choice. For fast-growing startups, Datadog’s out-of-the-box experience may be more valuable than the license fees saved....

PromQL (Prometheus Query Language) is the query language of the Prometheus monitoring system and the core of the cloud-native monitoring stack. Whether you’re building Grafana dashboards, writing alerting rules, or running ad-hoc queries during incident troubleshooting, PromQL is indispensable. This article starts from the data model and progressively covers aggregation operations, common functions, practical queries, and advanced techniques like subqueries. Reference: Prometheus Official Documentation — Querying basics I. PromQL Data Model PromQL has four fundamental data types....

In the Prometheus ecosystem, Prometheus generates alerts based on alerting rules, while Alertmanager manages the entire alert lifecycle: grouping, routing, inhibition, deduplication, and notification delivery. A poorly configured Alertmanager can drown on-call engineers in a flood of duplicate alerts at 3 AM, whereas a well-designed routing and inhibition strategy ensures that “the right person receives the right alert at the right time.” Reference: Prometheus Official Documentation — Alertmanager I. Alertmanager Architecture Alertmanager’s processing pipeline consists of five stages:...

Architecture Exporter → Prometheus (storage) → Grafana (visualization) ↓ Alertmanager (alert routing) Docker Compose Deployment version: '3.8' services: prometheus: image: prom/prometheus:v2.52.0 ports: ["9090:9090"] volumes: - ./prometheus.yml:/etc/prometheus/prometheus.yml - ./rules:/etc/prometheus/rules - prom_data:/prometheus command: - '--storage.tsdb.retention.time=30d' restart: unless-stopped grafana: image: grafana/grafana:10.4.2 ports: ["3000:3000"] volumes: [grafana_data:/var/lib/grafana] restart: unless-stopped alertmanager: image: prom/alertmanager:v0.27.0 ports: ["9093:9093"] volumes: [./alertmanager.yml:/etc/alertmanager/config.yml] restart: unless-stopped node-exporter: image: prom/node-exporter:v1.8.1 ports: ["9100:9100"] restart: unless-stopped volumes: prom_data: grafana_data: Core Configuration # prometheus.yml global: scrape_interval: 15s evaluation_interval: 15s rule_files: - "rules/*....

Overview In the monitoring system space, Zabbix and Prometheus are the two giants. Zabbix comes from the traditional operations era, dominating physical machine/VM environments for nearly 25 years; Prometheus rose in the cloud-native era, becoming the de facto standard for the Kubernetes ecosystem. Many teams face a question when choosing a monitoring system: Zabbix or Prometheus? The answer isn’t either/or. Many mature teams run both systems simultaneously in production — Zabbix handles the infrastructure layer (network, hardware, OS), while Prometheus handles the application and cloud-native layers....