Why has Chronosphere's query performance dashboard shown a 30% increase in p99 latency over the past week?

Introduction

Chronosphere's query performance dashboard has shown a 30% increase in p99 latency over the past week, indicating a significant degradation in query response times for the slowest 1% of requests. This issue requires immediate attention as it directly impacts user experience and potentially affects Chronosphere's core value proposition of fast, scalable observability.

I'll approach this problem systematically, starting with clarifying questions to gather context, then ruling out external factors before diving deep into internal causes. We'll analyze the metric breakdown, form data-driven hypotheses, and conduct a thorough root cause analysis. Finally, we'll develop a comprehensive plan to address the issue and prevent future occurrences.

Step 1

Clarifying Questions (3 minutes)

• I'm noticing the specificity of the 30% increase. Has there been any change in how we measure or calculate p99 latency recently?

Why it matters: Ensures we're comparing apples to apples and not chasing a data anomaly. Expected answer: No changes in measurement methodology. Impact on approach: If changed, we'd need to investigate the measurement process first.

• Given the week-long timeframe, I'm wondering about any recent deployments or system changes. Have there been any significant updates to Chronosphere's infrastructure or codebase in the past 7-10 days?

Why it matters: Identifies potential direct causes linked to recent changes. Expected answer: A list of recent deployments or "no significant changes." Impact on approach: Guides us to focus on recent changes or look for external factors if no updates.

• Considering user impact, has this latency increase affected all customers equally, or are we seeing variations across different user segments or query types?

Why it matters: Helps narrow down the scope and potential causes of the issue. Expected answer: Details on affected user segments or query patterns. Impact on approach: Directs our investigation to specific areas of the system or user behaviors.

• Thinking about overall system health, have we observed any correlated changes in other performance metrics or error rates alongside this p99 latency increase?

Why it matters: Provides a broader context of system performance and potential interconnected issues. Expected answer: Information on other metrics' behavior. Impact on approach: Helps in forming more comprehensive hypotheses about system-wide issues vs. isolated problems.