# INCIDENT REVIEW
**Payment Service Deployment – Checkout Error Spike**

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## 1. OBSERVED IMPACT
- Checkout error rate increased from 0.2% to 8% (40x spike) between 09:10–09:18 UTC
- Duration: ~13 minutes from detection to rollback completion
- Recovery: Error rate returned to 0.3% within 5 minutes of rollback
- User-facing effect: Estimated 7.8% of checkout attempts failed during the incident window
- Financial impact: No duplicate charges confirmed to date; potential revenue loss from failed transactions not yet quantified

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## 2. LIKELY CAUSE WITH UNCERTAINTY
**Probable cause:** The payment-service deployment at 09:05 introduced a retry mechanism that aggressively retries upstream timeouts without exponential backoff, causing cascading load on downstream services and timeout exhaustion.

**Uncertainty acknowledged:**
- Whether timeouts originated from a specific upstream dependency or multiple services
- Whether the retry logic was newly added or a configuration change to existing logic
- Whether the spike was driven by retry amplification, increased latency, or both
- Why database latency remained normal despite the error spike

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## 3. EVIDENCE STILL NEEDED
- Application logs from the new payment-service version showing retry counts and upstream timeout patterns (09:05–09:18)
- Upstream service metrics (latency, error rates, request volume) during the incident window
- Code diff between previous and deployed versions, specifically retry/timeout configuration
- Distributed trace samples from failed checkout requests to identify which service(s) timed out
- Comparison of request volume and latency patterns before/after 09:05

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## 4. RECOMMENDED FOLLOW-UP
**Investigation:**
- Review the payment-service deployment change log and code diff for retry logic modifications
- Analyze upstream service behavior during 09:05–09:18 to determine if they were the source of timeouts or victims of retry amplification
- Examine whether similar retry patterns exist in other services

**Prevention:**
- Implement pre-deployment testing for retry behavior under simulated upstream latency/timeout conditions
- Add circuit breaker or adaptive backoff to retry logic to prevent cascading failures
- Establish alerting on retry rates and upstream timeout frequency to catch similar patterns earlier
- Consider canary deployment for payment-service changes to limit blast radius