Introduction
ShowingTime's ShowingCart service has experienced a sudden increase in error rates during peak hours this week, indicating a critical issue that requires immediate attention. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term implications.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Recent changes often correlate with sudden performance issues. Expected answer: Yes, there was a minor update to the database schema. Impact on approach: If confirmed, we'd focus on database-related hypotheses.
Why it matters: Understanding load patterns helps identify capacity-related issues. Expected answer: Peak hours are typically 9-11 AM and 2-4 PM, with 3x normal traffic. Impact on approach: High load during specific times points to potential scaling problems.
Why it matters: User behavior changes can sometimes trigger unexpected system behaviors. Expected answer: No significant changes in user behavior have been observed. Impact on approach: This would lead us to focus more on technical rather than user-related issues.
Why it matters: Helps determine if this is a localized or system-wide problem. Expected answer: No, other services seem to be functioning normally. Impact on approach: We'd focus specifically on ShowingCart's architecture and dependencies.
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