What factors are contributing to the sudden 20% increase in error rates for Infogain's automated testing platform this month?

Introduction

The sudden 20% increase in error rates for Infogain's automated testing platform this month is a critical issue that demands immediate attention. As we delve into this product root cause analysis, we'll systematically investigate potential factors contributing to this significant performance decline. Our approach will involve clarifying the context, examining both internal and external factors, and developing data-driven hypotheses to identify the root cause.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a recent change in the platform. Has there been any significant update or deployment to the automated testing platform in the past month?

Why it matters: Recent changes often correlate with performance issues. Expected answer: Yes, there was a major update. Impact on approach: If yes, we'd focus on the changes made; if no, we'd look at external factors or gradual degradation.

• Considering the scale of the increase, I'm wondering about the distribution. Is this 20% increase consistent across all types of tests, or is it concentrated in specific areas?

Why it matters: Helps narrow down the problem scope. Expected answer: The increase is primarily in integration tests. Impact on approach: Concentrated issues would lead us to investigate specific test types or components.

• Given the nature of automated testing, I'm curious about the infrastructure. Have there been any changes to the testing environment or underlying infrastructure recently?

Why it matters: Infrastructure changes can significantly impact test reliability. Expected answer: No major infrastructure changes. Impact on approach: If yes, we'd focus on infrastructure; if no, we'd look more closely at the platform itself.

• Thinking about potential external factors, has there been any change in the volume or complexity of tests being run compared to previous months?

Why it matters: Changes in usage patterns can affect error rates. Expected answer: Test volume has increased by 15%. Impact on approach: Significant changes would lead us to investigate scalability issues.