Automate 21risk tasks via Rube MCP (Composio). Always search tools first for current schemas.
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Set up alerting rules, configure on-call rotations, and manage incident response workflows.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Configure effective alerting and on-call management for production systems.
# Severity levels
critical:
- Service completely down
- Data loss imminent
- Security breach
response: Immediate page, wake people up
high:
- Service degraded significantly
- Error rate above SLO
- Capacity near limit
response: Page during business hours, notify after hours
medium:
- Performance degradation
- Non-critical component failure
- Warning thresholds exceeded
response: Notify via Slack, review next business day
low:
- Informational alerts
- Capacity planning triggers
- Routine maintenance needed
response: Email notification, weekly review
# Good alert characteristics
alerts:
actionable:
- Every alert should require human action
- Include runbook links
- Clear remediation steps
relevant:
- Alert on symptoms, not causes
- Focus on user impact
- Avoid alerting on expected behavior
timely:
- Appropriate thresholds
- Suitable evaluation windows
- Account for normal variance
unique:
- No duplicate alerts
- Proper alert grouping
- Clear ownership
# prometheus/rules/alerts.yml
groups:
- name: service_alerts
rules:
# High-level service health
- alert: ServiceDown
expr: up{job="myapp"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Service {{ $labels.instance }} is down"
description: "{{ $labels.job }} on {{ $labels.instance }} has been down for more than 1 minute."
runbook_url: "https://wiki.example.com/runbooks/service-down"
# Error rate alert
- alert: HighErrorRate
expr: |
sum(rate(http_requests_total{status=~"5.."}[5m])) by (service)
/ sum(rate(http_requests_total[5m])) by (service) > 0.05
for: 5m
labels:
severity: critical
annotations:
summary: "High error rate for {{ $labels.service }}"
description: "Error rate is {{ $value | humanizePercentage }} for the last 5 minutes"
# Latency alert (SLO-based)
- alert: HighLatency
expr: |
histogram_quantile(0.95,
sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service)
) > 0.5
for: 5m
labels:
severity: high
annotations:
summary: "P95 latency above 500ms for {{ $labels.service }}"
# alertmanager.yml
global:
resolve_timeout: 5m
slack_api_url: 'https://hooks.slack.com/services/xxx'
pagerduty_url: 'https://events.pagerduty.com/v2/enqueue'
templates:
- '/etc/alertmanager/templates/*.tmpl'
route:
receiver: 'default-receiver'
group_by: ['alertname', 'service']
group_wait: 30s
group_interval: 5m
repeat_interval: 4h
routes:
# Critical alerts go to PagerDuty
- match:
severity: critical
receiver: 'pagerduty-critical'
group_wait: 0s
repeat_interval: 1h
# High severity during business hours
- match:
severity: high
receiver: 'slack-high'
active_time_intervals:
- business-hours
# Route by team
- match_re:
team: platform.*
receiver: 'platform-team'
receivers:
- name: 'default-receiver'
slack_configs:
- channel: '#alerts'
send_resolved: true
- name: 'pagerduty-critical'
pagerduty_configs:
- service_key: 'xxx'
severity: critical
description: '{{ .CommonAnnotations.summary }}'
details:
firing: '{{ template "pagerduty.firing" . }}'
- name: 'slack-high'
slack_configs:
- channel: '#alerts-high'
title: '{{ .CommonAnnotations.summary }}'
text: '{{ .CommonAnnotations.description }}'
actions:
- type: button
text: 'Runbook'
url: '{{ .CommonAnnotations.runbook_url }}'
- type: button
text: 'Dashboard'
url: '{{ .CommonAnnotations.dashboard_url }}'
- name: 'platform-team'
slack_configs:
- channel: '#platform-alerts'
time_intervals:
- name: business-hours
time_intervals:
- weekdays: ['monday:friday']
times:
- start_time: '09:00'
end_time: '17:00'
inhibit_rules:
- source_match:
severity: critical
target_match:
severity: high
equal: ['service']
# Terraform example
resource "pagerduty_service" "myapp" {
name = "MyApp Production"
description = "Production application service"
escala
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Automate 21risk tasks via Rube MCP (Composio). Always search tools first for current schemas.
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Automate 2chat tasks via Rube MCP (Composio). Always search tools first for current schemas.
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Usar al iniciar o mejorar un proyecto de IA: diagnostica código y restricciones, propone skills existentes y redacta tareas y un plan de implementación en español.
中文简介正在准备中。当前显示原文说明。
Usar para crear o mejorar una skill de Andru.ia: define entradas y resultados, redacta SKILL.md con ejemplos y límites, valida la estructura y prepara una PR.
中文简介正在准备中。当前显示原文说明。
Usar tras definir el sector de un proyecto: prepara un dossier en español con contexto, normas aplicables, patrones UX y riesgos, distinguiendo fuentes verificadas de hipótesis.
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AI-powered presentation generation via the 2slides API — create slides from text, match a reference image style, summarize documents into decks, add AI voice narration, and export pages/audio. Use f
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