What caused the sudden spike in error rates for Watershed's carbon accounting dashboard last week?

Introduction

The sudden spike in error rates for Watershed's carbon accounting dashboard last week is a critical issue that demands immediate attention and thorough analysis. As we delve into this problem, we'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term fixes and long-term implications for our product ecosystem.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this could be related to a recent deployment. Has there been any significant update or change to the dashboard in the past week?

Why it matters: Recent changes often correlate with sudden performance issues. Expected answer: Yes, there was a minor update to improve data visualization. Impact on approach: If confirmed, we'd focus on the new code and its integration.

• Considering user segments, I'm curious about the error distribution. Are we seeing this spike across all user types, or is it concentrated in a particular segment?

Why it matters: Helps narrow down if it's a global issue or specific to certain users. Expected answer: The errors are more prevalent among enterprise users. Impact on approach: We'd investigate enterprise-specific features or data loads.

• Given the nature of carbon accounting, I'm wondering about data sources. Have there been any changes in how we're ingesting or processing external data?

Why it matters: Data integrity is crucial for accurate carbon accounting. Expected answer: No known changes to data ingestion processes. Impact on approach: If true, we'd shift focus to internal data handling and calculations.

• Thinking about system health, I'm interested in overall performance metrics. Have we noticed any unusual patterns in server load or response times coinciding with the error spike?

Why it matters: System overload could explain increased error rates. Expected answer: There's been a slight increase in average response times. Impact on approach: We'd investigate potential bottlenecks in our infrastructure.