使い方
- インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
- 必要なツール、認証情報、対応環境を原文で確認します。
- 入力と成果物を指定し、出力を資料と照合します。
npx skills add https://github.com/datadog-labs/agent-skills --skill dd-monitors開始前の確認
- 導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
- スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。
リポジトリの原文
見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。
Datadog Monitors
Create, manage, and maintain monitors for alerting.
Prerequisites
This requires pup in your path. See Setup Pup.
Command Execution Order (Token-Efficient)
For scoped commands, use this order:
- Check context first (prior outputs, conversation, saved values).
- If a required value is missing, run a discovery command first.
- If still ambiguous, ask the user to confirm.
- Then run the target command.
- Avoid speculative commands likely to fail.
Quick Start
bash
pup auth loginCommon Operations
List Monitors
bash
pup monitors list
pup monitors list --tags "team:platform"Get Monitor
bash
pup monitors get <id>Create Monitor
bash
pup monitors create --file monitor.jsonSilence Alerts (Downtime)
bash
# No pup monitors mute/unmute commands.
# Use downtime payloads to silence monitor notifications.
pup downtime create --file downtime.json
pup downtime cancel <downtime_id>Monitor Creation Best Practices
1. Avoid Alert Fatigue
| 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 |
python
# 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 window2. Use Proper Scoping
python
# 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" # ✅3. Set Recovery Thresholds
python
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
}
}
}4. Include Context in Messages
python
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
"""NEVER Delete Monitors Directly
Use safe deletion workflow (same as dashboards):
python
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 TrueMonitor Types
| 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 |
Audit Monitors
bash
# 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}'Downtime vs Muting
| Use | When |
|---|---|
| Downtime | Any planned silence window |
| Monitor edit | Query/threshold behavior changes |
bash
# Downtime (preferred)
pup downtime create --file downtime.jsonFailure Handling
| 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 |
