Introduction
The sudden spike in error rates for Atomic's Direct Deposit API last week is a critical issue that demands immediate attention and thorough analysis. As we delve into this problem, we'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term fixes and long-term implications for our product ecosystem.
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 performance issues. Expected answer: Yes, there was a minor update to improve processing speed. Impact on approach: If confirmed, we'd focus on the recent changes and their potential side effects.
Why it matters: Unusual load could explain performance degradation. Expected answer: Transaction volumes have been within normal ranges. Impact on approach: If volumes are normal, we'd shift focus to internal system issues rather than capacity problems.
Why it matters: Ensures we're working with accurate data and haven't missed earlier warning signs. Expected answer: No changes to monitoring systems have been reported. Impact on approach: If confirmed, we can trust our error rate data and focus on the API itself.
Why it matters: External changes could impact our API's performance. Expected answer: No significant changes reported from partner institutions. Impact on approach: If true, we'd focus more on internal factors rather than external integrations.
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