Introduction
The sudden increase in Codeium's API average response time from 100ms to 500ms over the past 48 hours is a critical issue that demands immediate attention. This significant performance degradation could severely impact user experience, potentially leading to customer churn and reputational damage. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term solutions.
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 trigger performance issues. Expected answer: Yes, a major update was deployed. Impact on approach: If yes, we'd focus on rollback options and code review.
Why it matters: Helps narrow down the scope of the problem. Expected answer: It's affecting all endpoints. Impact on approach: If isolated, we'd investigate those specific endpoints first.
Why it matters: Sudden traffic increases can overwhelm systems. Expected answer: Traffic has remained relatively stable. Impact on approach: If there's a spike, we'd look into scaling issues and potential DDoS attacks.
Why it matters: External dependencies can significantly impact API performance. Expected answer: No known issues with third-party services. Impact on approach: If yes, we'd engage with the third-party provider and consider fallback options.
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