Datadog Monitors

Create, manage, and maintain monitors for alerting.

Prerequisites

This requires the pup binary in your path.

pup - cargo install --git https://github.com/DataDog/pup

Quick Start

bash
pup auth login

Common Operations

List Monitors

bash
pup monitors list
pup monitors list --tags "team:platform"
pup monitors search --query "status:Alert"

Get Monitor

bash
pup monitors get <id>

Create Monitor

bash
pup monitors create --file monitor.json

Mute/Unmute

bash
# Mute with duration
pup monitors update 12345 --file monitor-muted.json

# Or mute with specific end time
pup monitors update 12345 --file monitor-muted-until.json

# Unmute
pup monitors update 12345 --file monitor-unmuted.json

⚠️ 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

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 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 | |-----|------| | Mute monitor | Quick one-off, < 1 hour | | Downtime | Scheduled maintenance, recurring |

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 |

References

• Monitor Types
• Alerting Best Practices
• SLO Monitors