What factors are contributing to the sudden 50% increase in error rates for Grafana Labs's Tempo distributed tracing system?

Introduction

The sudden 50% increase in error rates for Grafana Labs's Tempo distributed tracing system is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term implications for the product.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into the product's user journey and metrics. From there, I'll generate data-driven hypotheses, conduct root cause analysis, and propose a comprehensive validation and resolution plan.

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 to Tempo or related systems in the past week?

Why it matters: Recent changes often correlate with sudden performance shifts. Expected answer: Yes, a new version was deployed 3 days ago. Impact on approach: If confirmed, I'd focus on changes in that deployment.

• Considering the scale, I'm wondering if this is affecting all users equally. Are we seeing this 50% increase across all customer segments or is it concentrated in specific groups?

Why it matters: Helps narrow down potential causes and affected components. Expected answer: The issue is more pronounced in enterprise customers. Impact on approach: I'd investigate enterprise-specific features or scaling issues.

• Given the nature of distributed tracing, I'm curious about the error types. What specific types of errors are we seeing an increase in?

Why it matters: Different error types point to different root causes. Expected answer: Mostly timeout errors and data loss. Impact on approach: I'd focus on network issues or data processing bottlenecks.

• Thinking about system dependencies, has there been any change in the underlying infrastructure or related services that Tempo relies on?

Why it matters: Distributed systems often have complex dependencies. Expected answer: Cloud provider reported some network issues recently. Impact on approach: I'd investigate how these issues might be affecting Tempo specifically.