Introduction
The issue of AWS Lambda functions timing out for 35% of executions is a critical problem that requires immediate attention. This high failure rate not only impacts user experience but also raises concerns about system reliability and efficiency. In this analysis, I'll systematically investigate the root cause, generate hypotheses, and propose solutions to address this performance bottleneck.
My approach will involve a thorough examination of the Lambda function ecosystem, potential technical issues, and user behavior patterns. I'll outline a clear path forward, considering both short-term fixes and long-term strategic improvements.
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: Helps determine if this is a new problem or an ongoing issue that's worsened. Expected answer: A sudden spike within the last week. Impact on approach: A sudden spike would suggest a recent change or event as the cause.
Why it matters: Narrows down the problem to specific function types or a system-wide issue. Expected answer: Primarily affecting data processing functions. Impact on approach: Would focus investigation on those specific function types and their dependencies.
Why it matters: Helps determine if the issue is related to inadequate timeout settings. Expected answer: Default 3-second timeout. Impact on approach: If too low, might suggest a simple configuration change as a quick fix.
Why it matters: Identifies potential triggers for the increased timeouts. Expected answer: Recent update to a connected database service. Impact on approach: Would investigate the impact of this update on Lambda function performance.
Why it matters: Ensures the reported issue isn't due to changes in measurement or definition. Expected answer: No changes in measurement or definition. Impact on approach: Confirms the issue is real and not a result of altered metrics.
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