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- 2026년 5월 29일 18:02
- 감지된 SKILL.md 언어
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/datadog-labs/agent-skills --skill dd-monitors명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Datadog skills for AI agents. Essential monitoring, logging, tracing and observability.
Set up the Datadog AWS integration with Terraform - creates the cross-account IAM role Datadog assumes (external ID, no stored credentials), attaches the permission policies Datadog publishes, and registers the account through datadog_integration_aws_account so AWS metrics, the resource catalog, and CSPM findings start flowing. Use when the user has AWS resources they want to monitor, wants to connect an AWS account to Datadog, asks to set up or repair the AWS integration, or needs the Datadog IAM role and external ID provisioned. Does not set up log forwarding.
Set up the Datadog Azure integration with Terraform - creates an Entra ID app registration and service principal, assigns Monitoring Reader across the chosen subscriptions and management groups, grants the Microsoft Graph permissions Datadog needs for resource discovery, and registers the tenant so Azure metrics and resource collection start flowing. Use when the user wants to monitor Azure VMs, App Service, SQL Database, or AKS, wants to connect an Azure subscription or management group or tenant to Datadog, or asks to set up or repair the Azure integration. Does not set up log forwarding.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | dd-monitors |
| description | Monitor management - list, search, file-based create, and alerting best practices. |
| metadata | {"version":"1.0.1","author":"datadog-labs","repository":"https://github.com/datadog-labs/agent-skills","tags":"datadog,monitors,alerting,alerts,dd-monitors","globs":"**/datadog*.yaml,**/*monitor*","alwaysApply":"false"} |
Create, manage, and maintain monitors for alerting.
This requires pup in your path. See Setup Pup.
For scoped commands, use this order:
pup auth login
pup monitors list
pup monitors list --tags "team:platform"
pup monitors get <id>
pup monitors create --file monitor.json
# No pup monitors mute/unmute commands.
# Use downtime payloads to silence monitor notifications.
pup downtime create --file downtime.json
pup downtime cancel <downtime_id>
| Rule | Why |
|---|---|
| No flapping alerts | Use last_Xm not last_1m |
| Meaningful thresholds | Based on SLOs, not guesses |
| Actionable alerts | If no action needed, don't alert |
| Include runbook | @runbook-url in message |
# WRONG - will flap constantly
query = "avg(last_1m):avg:system.cpu.user{*} > 50" # ❌ Too sensitive
# CORRECT - stable alerting
query = "avg(last_5m):avg:system.cpu.user{env:prod} by {host} > 80" # ✅ Reasonable window
# WRONG - alerts on everything
query = "avg(last_5m):avg:system.cpu.user{*} > 80" # ❌ No scope
# CORRECT - scoped to what matters
query = "avg(last_5m):avg:system.cpu.user{env:prod,service:api} by {host} > 80" # ✅
monitor = {
"query": "avg(last_5m):avg:system.cpu.user{env:prod} > 80",
"options": {
"thresholds": {
"critical": 80,
"critical_recovery": 70, # ✅ Prevents flapping
"warning": 60,
"warning_recovery": 50
}
}
}
message = """
## High CPU Alert
Host: {{host.name}}
Current Value: {{value}}
Threshold: {{threshold}}
### Runbook
1. Check top processes: `ssh {{host.name}} 'top -bn1 | head -20'`
2. Check recent deploys
3. Scale if needed
@slack-ops @pagerduty-oncall
"""
Use safe deletion workflow (same as dashboards):
def safe_mark_monitor_for_deletion(monitor_id: str, client) -> bool:
"""Mark monitor instead of deleting."""
monitor = client.get_monitor(monitor_id)
name = monitor.get("name", "")
if "[MARKED FOR DELETION]" in name:
print(f"Already marked: {name}")
return False
new_name = f"[MARKED FOR DELETION] {name}"
client.update_monitor(monitor_id, {"name": new_name})
print(f"✓ Marked: {new_name}")
return True
| Type | Use Case |
|---|---|
metric alert | CPU, memory, custom metrics |
query alert | Complex metric queries |
service check | Agent check status |
event alert | Event stream patterns |
log alert | Log pattern matching |
composite | Combine multiple monitors |
apm | APM metrics |
# Find monitors without owners
pup monitors list | jq '.[] | select(.tags | contains(["team:"]) | not) | {id, name}'
# Find noisy monitors (high alert count)
pup monitors list | jq 'sort_by(.overall_state_modified) | .[:10] | .[] | {id, name, status: .overall_state}'
| Use | When |
|---|---|
| Downtime | Any planned silence window |
| Monitor edit | Query/threshold behavior changes |
# Downtime (preferred)
pup downtime create --file downtime.json
| Problem | Fix |
|---|---|
| Alert not firing | Check query returns data, thresholds |
| Too many alerts | Increase window, add recovery threshold |
| No data alerts | Check agent connectivity, metric exists |
| Auth error | pup auth refresh |