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Introduction
The recent 15% drop in active users for Datadog's Log Management feature over the past week is a concerning trend that requires immediate attention. To address this issue, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term implications for the product.
Framework overview
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 metric shifts. Expected answer: Yes, a new UI was rolled out. Impact on approach: If confirmed, I'd focus on UI-related hypotheses.
Why it matters: Helps identify if the issue is global or segment-specific. Expected answer: Enterprise customers are more affected. Impact on approach: I'd prioritize investigating enterprise-specific factors.
Why it matters: Log volume changes could impact feature usage. Expected answer: Log volumes have remained stable. Impact on approach: If stable, I'd focus more on feature usability than capacity issues.
Why it matters: External events can sometimes explain sudden metric changes. Expected answer: No significant external events noted. Impact on approach: I'd focus more on internal factors if external events are ruled out.
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