Introduction
The sudden 200% increase in Google Cloud storage read latency is a critical issue that demands immediate attention and a thorough root cause analysis. This significant performance degradation could severely impact user experience, application functionality, and overall system reliability. I'll approach this problem systematically, considering various factors that could contribute to such a drastic latency increase.
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: The timeline helps determine if this is an acute issue or a chronic problem. Expected answer: It's a sudden increase within the last 24 hours. Impact on approach: A sudden increase would point towards a recent change or event, while a gradual increase might suggest a scaling or capacity issue.
Why it matters: This helps isolate the problem to specific components or use cases. Expected answer: The increase is more pronounced for large file reads. Impact on approach: If it's specific to certain operations, we'd focus on those particular components or data access patterns.
Why it matters: This information helps determine if it's a global infrastructure issue or localized to certain data centers. Expected answer: The issue is primarily affecting two specific regions. Impact on approach: If it's region-specific, we'd investigate regional infrastructure or network issues.
Why it matters: Recent changes are often the culprit in sudden performance degradations. Expected answer: There was a minor security patch applied 48 hours ago. Impact on approach: This would lead us to investigate the impact of the recent patch on read operations.
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