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- ffsshhttiikk/opencode-agents-skills
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- 2026년 2월 28일 22:53
- 감지된 SKILL.md 언어
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소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
SKILL.md 표시 중
SKILL.md
소스 지침 · 읽기 전용 미리보기- name
- prometheus
- description
- Prometheus monitoring system for collecting and querying time-series metrics
- license
- MIT
- compatibility
- opencode
- metadata
- {"audience":"devops","category":"monitoring"}
## What I do
- Set up Prometheus metrics collection
- Write PromQL queries
- Configure alerting rules
- Use client libraries
- Set up service discovery
- Create Grafana dashboards
- Handle metric cardinality
## When to use me
When monitoring applications and infrastructure metrics.
## Configuration
```yaml
global:
scrape_interval: 15s
evaluation_interval: 15s
scrape_configs:
- job_name: 'prometheus'
static_configs:
- targets: ['localhost:9090']
- job_name: 'node'
static_configs:
- targets: ['node-exporter:9100']
- job_name: 'myapp'
metrics_path: '/metrics'
static_configs:
- targets: ['app:8080']
```
## Metrics Types
```go
import "github.com/prometheus/client_golang/prometheus"
var (
// Counter - only increases
requestsTotal = prometheus.NewCounterVec(
prometheus.CounterOpts{
Name: "http_requests_total",
Help: "Total HTTP requests",
},
[]string{"method", "status"},
)
// Gauge - can go up and down
temperature = prometheus.NewGauge(
prometheus.GaugeOpts{
Name: "room_temperature_celsius",
Help: "Current room temperature",
},
)
// Histogram - distributions
requestDuration = prometheus.NewHistogram(
prometheus.HistogramOpts{
Name: "http_request_duration_seconds",
Buckets: []float64{.005, .01, .025, .05, .1, .25, .5, 1, 2.5, 5},
},
)
// Summary - percentiles
responseSize = prometheus.NewSummary(
prometheus.SummaryOpts{
Name: "http_response_size_bytes",
Objectives: map[float64]float64{0.5: 0.05, 0.95: 0.05, 0.99: 0.01},
},
)
)
func init() {
prometheus.MustRegister(requestsTotal, temperature, requestDuration)
}
```
## PromQL Queries
```promql
# Rate - per second increase
rate(http_requests_total[5m])
# Increase over time window
increase(http_requests_total[1h])
# Average over time
avg(http_request_duration_seconds)
# Percentiles
histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m]))
# Count over time
count(http_requests_total{status="200"})
# Sum by label
sum by (method) (http_requests_total)
# Top queries
topk(10, http_requests_total)
# Subqueries
max_over_time(http_requests_total[1h:5m])
```
## Alerting Rules
```yaml
groups:
- name: example
rules:
- alert: HighErrorRate
expr: rate(http_requests_total{status=~"5.."}[5m]) > 0.05
for: 5m
labels:
severity: critical
annotations:
summary: "High error rate on {{ $labels.method }}"
- alert: InstanceDown
expr: up == 0
for: 2m
labels:
severity: critical
annotations:
summary: "Instance {{ $labels.instance }} down"
```
## Python Client
```python
from prometheus_client import Counter, Gauge, Histogram, start_http_server
REQUEST_COUNT = Counter('http_requests_total', 'Total HTTP requests', ['method', 'status'])
ACTIVE_USERS = Gauge('active_users', 'Number of active users')
REQUEST_LATENCY = Histogram('http_request_latency_seconds', 'Request latency')
@app.route('/api')
def handle_request():
with REQUEST_LATENCY.time():
# process request
REQUEST_COUNT.labels(method='GET', status='200').inc()
return 'OK'
if __name__ == '__main__':
start_http_server(8000)
```
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