인터페이스는 현지화되어 있으며, Skill 소개와 설명 문서는 선택한 언어로 AI가 자동 번역합니다. 코드·명령어·경로·전문 용어는 원문을 유지하며 원작자 문서가 우선합니다.
Skills 둘러보기
생산성 및 협업 · SKILL.md

prometheus

prometheus

Prometheus and Grafana Cloud Metrics overview including PromQL query language, Metrics Drilldown, alerting, recording rules, and integration patterns. Use when working with Prometheus, writing PromQL queries, configuring alerting, or discussing metrics architecture and best practices.

Independent GitHub snapshot · Automated classification · Original documentation governs

Ggrafana / skillsApache-2.0

Skill 문서

GitHub

name: prometheus license: Apache-2.0 description: > Prometheus and Grafana Cloud Metrics overview including PromQL query language, Metrics Drilldown, alerting, recording rules, and integration patterns. Use when working with Prometheus, writing PromQL queries, configuring alerting, or discussing metrics architecture and best practices.

Metrics with Prometheus and Grafana

Docs: https://prometheus.io/docs/ | Grafana Cloud Metrics: https://grafana.com/docs/grafana-cloud/send-data/metrics/

PromQL Quick Reference

Instant Vector Selectors

# By metric name
http_requests_total

# Label filter
http_requests_total{job="api-server"}

# Multiple labels (AND)
http_requests_total{job="api-server", method="GET"}

# Regex
http_requests_total{job=~"api.*", status=~"5.."}

# Negative
http_requests_total{status!="200"}

Range Vectors & Rates

# Per-second rate over 5 minutes
rate(http_requests_total[5m])

# Increase over interval
increase(http_requests_total[1h])

# Instant rate (last two samples)
irate(http_requests_total[5m])

# Offset (5 minutes ago)
rate(http_requests_total[5m] offset 5m)

Aggregations

# Sum by label
sum by (job) (rate(http_requests_total[5m]))

# Average
avg by (instance) (node_cpu_seconds_total)

# Top-K
topk(5, rate(http_requests_total[5m]))

# Histogram quantiles
histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m]))

# Count distinct
count(up{job="api"})

Common Patterns

# Error rate percentage
sum(rate(http_requests_total{status=~"5.."}[5m]))
  / sum(rate(http_requests_total[5m])) * 100

# Saturation (CPU usage %)
100 - (avg by(instance) (irate(node_cpu_seconds_total{mode="idle"}[5m])) * 100)

# Memory usage
node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes

# Predict disk full (linear extrapolation)
predict_linear(node_filesystem_free_bytes[6h], 24*3600) < 0

Alerting Rules

Prometheus Alerting Rule

groups:
  - name: api_alerts
    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 5xx error rate ({{ $value | humanizePercentage }})"

Alertmanager Routing

# alertmanager.yml
route:
  receiver: default
  group_by: [alertname, job]
  group_wait: 30s
  group_interval: 5m
  routes:
    - match:
        severity: critical
      receiver: pagerduty
    - match:
        severity: warning
      receiver: slack

receivers:
  - name: pagerduty
    pagerduty_configs:
      - service_key: "<key>"
  - name: slack
    slack_configs:
      - channel: "#alerts"
        api_url: "<webhook_url>"
  - name: default
    email_configs:
      - to: "oncall@example.com"

Validate Alerting Configuration

promtool check rules rules.yml
amtool check-config alertmanager.yml
amtool config routes test --config.file=alertmanager.yml severity=critical

Recording Rules

Pre-compute expensive PromQL for dashboard performance:

groups:
  - name: api_rules
    interval: 1m
    rules:
      - record: job:http_requests:rate5m
        expr: sum by (job) (rate(http_requests_total[5m]))
      - record: job:http_request_duration_seconds:p99
        expr: histogram_quantile(0.99, sum by (job, le) (rate(http_request_duration_seconds_bucket[5m])))

Deploy and Verify Recording Rules

# 1. Validate rule syntax
promtool check rules rules/recording.yml

# 2. Reload Prometheus (after adding to rule_files in prometheus.yml)
curl -X POST http://localhost:9090/-/reload

# 3. Verify rules are active
curl -s http://localhost:9090/api/v1/rules | jq '.data.groups[].rules[] | {name, health}'

Metrics Drilldown (Grafana 12+)

Queryless Prometheus exploration — browse metrics without writing PromQL. Navigate to Explore > Metrics Drilldown or use <grafana-url>/a/grafana-metricsdrilldown-app. Provides metric search with label breakdown, smart segmentation for anomaly detection, auto-visualization, and telemetry pivoting from metrics to related logs and traces.

Resources

저장한 Skills