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
bashpup auth login
Common Operations
List Monitors
bashpup monitors list pup monitors list --tags "team:platform"
Get Monitor
bashpup monitors get <id>
Create Monitor
bashpup monitors create --file monitor.json
Silence 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 window
2. 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
pythonmonitor = { "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
pythonmessage = """ ## 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):
pythondef 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
Monitor 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.json
Failure 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 |

