Why has GoodData's dashboard loading time increased by 30% over the past week for enterprise customers?

Introduction

GoodData's dashboard loading time increase of 30% for enterprise customers over the past week is a critical issue that demands immediate attention. This performance degradation directly impacts user experience and could potentially lead to customer churn if not addressed promptly. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term solutions.

Step 1

Clarifying Questions (3 minutes)

• Given the sudden increase, I'm thinking there might have been a recent deployment. Has there been any significant update or change to the system in the past 1-2 weeks?

Why it matters: Recent changes often correlate with performance issues. Expected answer: Yes, there was a deployment last week. Impact on approach: If confirmed, I'd focus on changes in that deployment.

• Considering the specificity to enterprise customers, I'm wondering about data volume. Has there been any significant increase in data processing for enterprise accounts recently?

Why it matters: Enterprise customers often have larger datasets, which could strain the system. Expected answer: Some enterprise customers have increased their data volume. Impact on approach: I'd investigate data processing optimizations and scaling solutions.

• The 30% increase seems quite precise. How is dashboard loading time being measured, and has there been any change to the measurement system?

Why it matters: Ensures we're dealing with accurate data and not a measurement anomaly. Expected answer: No changes to measurement; it's end-to-end load time from request to full render. Impact on approach: If confirmed, I'd focus on actual performance issues rather than measurement discrepancies.

• Given the enterprise focus, I'm curious about geographical distribution. Are we seeing this issue uniformly across all regions, or is it concentrated in specific areas?

Why it matters: Could indicate infrastructure or CDN issues if localized. Expected answer: The issue is seen across all regions, but more pronounced in certain areas. Impact on approach: I'd investigate both global and region-specific factors in our infrastructure.