Introduction
The sudden 150% increase in AWS S3 data retrieval latency is a critical issue that demands immediate attention and a thorough root cause analysis. This significant performance degradation could have far-reaching consequences for our customers and our business. I'll approach this problem systematically, starting with clarifying questions to gather essential context, then moving through hypothesis generation, validation, and solution development.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Helps pinpoint potential triggers and narrows the investigation timeframe. Expected answer: Within the last 24-48 hours. Impact on approach: Recent change suggests looking at recent deployments or configuration changes.
Why it matters: Determines if it's a global issue or localized to specific infrastructure. Expected answer: Varies by region, with some more affected than others. Impact on approach: Focus on regional differences and potential infrastructure bottlenecks.
Why it matters: Gauges real-world impact and urgency of the situation. Expected answer: Yes, significant increase in complaints, especially from high-volume users. Impact on approach: Prioritize high-impact customers and consider temporary workarounds.
Why it matters: Identifies potential triggers for the latency increase. Expected answer: A minor update to S3's backend infrastructure was rolled out recently. Impact on approach: Investigate the update's impact and consider rollback options.
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