Efficient Alerting: How to Prevent Your Team from Burning Out

“I quit.” This is what happens when an engineer gets paged 20 times a week for non-actionable alerts. Efficient alerting isn’t just a technical configuration; it’s a Retention Strategy.

Here is how to design an alerting pipeline that respects human beings.

1. Severity Levels (SEV-1 to SEV-5)

Not all alerts are created equal. Tag them.

• SEV-1 (Critical): Users are down. Revenue is stopped.
  • Action: PagerDuty (Phone Call). 24/7.
• SEV-2 (High): System degraded. Slow responses.
  • Action: PagerDuty (SMS). Wake up if > 15 mins.
• SEV-3 (Moderate): Internal tool down. Background job failed.
  • Action: Slack notification. Fix during business hours.
• SEV-4 (Low): Disk 80% full.
  • Action: Jira Ticket. Fix next sprint.

Cluster Uptime allows you to route alerts based on tags. Tag your monitors with #sev1 or #sev3 and create routing rules.

2. Deduplication (Storm Protection)

When “The Database” goes down, 50 API services dependent on it will also fail. Result: 51 Alerts at once. (Alert Storm).

Solution: Dependency Mapping.

• Configure Cluster Uptime: “API Service depends on Database”.
• If Database is DOWN, suppress alerts for API Service.
• You get 1 Alert: “Database is Down”. (The root cause).

3. Escalation Policies

What if the On-Call engineer is in the shower? Or asleep? Don’t let the alert die.

Level 1: Notify On-Call Engineer (Wait 5 mins). Level 2: Notify Tech Lead (Wait 10 mins). Level 3: Notify CTO (Everyone panics).

4. Runbooks

Every alert must have a “Runbook Link”. When I wake up at 3 AM, I have zero brain cells. Don’t make me think. Give me a link: wiki/how-to-restart-redis. If an alert doesn’t have a Runbook, delete the alert. It means it’s not actionable.

Respect the pager, and the pager will respect you.