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prometheus

prometheus

github.com/grafanaCloud & DevOps2955.3k installsUpdated 1d ago
Repository

About prometheus

prometheus is a reference skill for Prometheus metrics workflows, covering PromQL, alerting, and recording rules. It is for users querying and operating Prometheus or Grafana metrics, with examples for common analysis and configuration tasks.

Key features

  1. 01PromQL selectors, rates, and aggregations
  2. 02Common metric analysis patterns
  3. 03Alerting rule and routing examples
  4. 04Recording rule setup and validation
  5. 05Grafana Metrics Drilldown guidance

Use cases

  1. 01Write queries for request rates and errors
  2. 02Configure and validate Prometheus alerts
  3. 03Precompute dashboard metrics with recording rules
  4. 04Explore metrics without writing PromQL

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/grafana/skills --skill prometheus

After installing, type/prometheusin Claude Code to confirm it loaded.

Details

From the project README

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: "[email protected]"
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

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