Full-Stack Observability: Implementing Prometheus, Alertmanager, and Grafana
Set up the four golden signals of monitoring, write high-precision PromQL alerting queries, and eliminate alert fatigue across your cloud infrastructure.
CloudPlatformLabs Engineering
Platform Architecture Team
1. The Four Golden Signals of Distributed Systems
Effective monitoring avoids instrumenting arbitrary metrics that distract on-call engineers. Instead, base your core service dashboards and alerting rules on the Four Golden Signals defined by Google Site Reliability Engineering: Latency, Traffic, Errors, and Saturation.
Prometheus collects multi-dimensional time series metrics via HTTP pull scraping. With PromQL, we can calculate rate of errors, 99th percentile request latency, and thread saturation with sub-second precision.
groups:
- name: api-service-alerts
rules:
# High Error Rate Alert (> 2% 5xx errors over 5 minutes)
- alert: HighHttpErrorRate
expr: |
sum(rate(http_requests_total{status=~"5.."}[5m]))
/
sum(rate(http_requests_total[5m])) * 100 > 2
for: 5m
labels:
severity: critical
annotations:
summary: "High HTTP 5xx error rate detected on {{ $labels.service }}"
description: "Error rate is currently {{ $value | printf '%.2f' }}% on namespace {{ $labels.namespace }}"2. Measuring Latency Correctly with Histograms
Averages lie. If 95% of users receive a response in 50ms but 5% wait 10 seconds, average latency looks healthy while your most valuable users experience catastrophic latency. Use Prometheus histograms with `histogram_quantile` to measure p95 and p99 latency distributions.
histogram_quantile(
0.99,
sum(rate(http_request_duration_seconds_bucket{job="api"}[5m])) by (le)
)Related Topics & Tags
Written by CloudPlatformLabs Engineering
Platform Architecture Team
CloudPlatformLabs publishes independent, peer-reviewed cloud and DevOps architecture blueprints, hands-on tutorials, and infrastructure case studies. Our mission is to make advanced infrastructure engineering transparent, resilient, and developer-friendly.