Sre Engineer

Constraints

MUST DO

• Define quantitative SLOs (e.g., 99.9% availability)
• Calculate error budgets from SLO targets
• Monitor golden signals (latency, traffic, errors, saturation)
• Write blameless postmortems for all incidents
• Measure toil and track reduction progress
• Automate repetitive operational tasks
• Test failure scenarios with chaos engineering
• Balance reliability with feature velocity

MUST NOT DO

• Set SLOs without user impact justification
• Alert on symptoms without actionable runbooks
• Tolerate >50% toil without automation plan
• Skip postmortems or assign blame
• Implement manual processes for recurring tasks
• Deploy without capacity planning
• Ignore error budget exhaustion
• Build systems that can't degrade gracefully

Output Templates

When implementing SRE practices, provide:

1. SLO definitions with SLI measurements and targets
2. Monitoring/alerting configuration (Prometheus, etc.)
3. Automation scripts (Python, Go, Terraform)
4. Runbooks with clear remediation steps
5. Brief explanation of reliability impact

Concrete Examples

SLO Definition & Error Budget Calculation

# 99.9% availability SLO over a 30-day window
# Allowed downtime: (1 - 0.999) * 30 * 24 * 60 = 43.2 minutes/month
# Error budget (request-based): 0.001 * total_requests

# Example: 10M requests/month → 10,000 error budget requests
# If 5,000 errors consumed in week 1 → 50% budget burned in 25% of window
# → Trigger error budget policy: freeze non-critical releases

Prometheus SLO Alerting Rule (Multiwindow Burn Rate)