What's causing the sudden 50% increase in query latency for sharded collections in MongoDB 6.0?

Introduction

The sudden 50% increase in query latency for sharded collections in MongoDB 6.0 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 our database performance and overall product stability.

I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into the product architecture, metric breakdown, and potential internal causes. We'll generate data-driven hypotheses, conduct root cause analysis, and develop a comprehensive plan for validation and resolution.

Step 1

Clarifying Questions (3 minutes)

• Given the specificity of the issue to sharded collections, I'm wondering about the overall system architecture. Could you confirm if this latency increase is isolated to sharded collections, or are we seeing any impact on non-sharded data as well?

Why it matters: This helps us narrow down whether the issue is specific to sharding or a broader MongoDB problem. Expected answer: The issue is primarily affecting sharded collections. Impact on approach: If it's sharding-specific, we'll focus on shard-related components; if not, we'll consider broader MongoDB optimizations.

• Considering the timing, I'm curious about recent changes. Have there been any significant updates to the MongoDB configuration, schema changes, or increased data volume in the past week?

Why it matters: Recent changes often correlate with performance issues. Expected answer: There was a recent increase in data volume and a minor configuration change. Impact on approach: We'll prioritize investigating the impact of these recent changes on query performance.

• Looking at the user impact, I'm thinking about query patterns. Can you share if this latency increase is uniform across all query types, or are certain operations (e.g., aggregations, joins) more affected?

Why it matters: Different query types stress the system differently, helping us pinpoint the problem area. Expected answer: Complex queries involving multiple shards are more affected. Impact on approach: We'll focus on optimizing cross-shard query execution and data distribution strategies.

• Considering the scale of the issue, I'm curious about our monitoring setup. Are we seeing any corresponding spikes in CPU, memory usage, or network traffic coinciding with this latency increase?

Why it matters: Resource constraints often manifest as performance issues. Expected answer: There's a noticeable increase in CPU usage across shard servers. Impact on approach: We'll investigate potential CPU bottlenecks and query optimization strategies.