What caused the sudden spike in failed connections for Aiven's Kafka clusters yesterday afternoon?

Introduction

The sudden spike in failed connections for Aiven's Kafka clusters yesterday afternoon is a critical issue that demands immediate attention and thorough analysis. As we delve into this problem, we'll follow a systematic approach to identify the root cause, validate our hypotheses, and develop both short-term fixes and long-term solutions.

Our analysis will cover multiple angles, from technical infrastructure to user behavior, ensuring we leave no stone unturned. Let's begin by gathering essential information and ruling out external factors before diving deep into the product ecosystem and potential internal causes.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this might be related to a recent deployment or configuration change. Has there been any significant update to the Kafka clusters or related systems in the past 24-48 hours?

Why it matters: Recent changes are often the culprit in sudden performance issues. Expected answer: Yes, there was a minor configuration update. Impact on approach: If confirmed, we'd focus on rollback options and change management processes.

• Considering the nature of Kafka, I'm wondering about data volume and throughput. Have we seen any unusual spikes in data ingestion or processing rates leading up to the incident?

Why it matters: Unusual data patterns can overwhelm even well-designed systems. Expected answer: Data volumes have been within normal ranges. Impact on approach: If volumes are normal, we'd shift focus to infrastructure or configuration issues.

• Given that we're dealing with failed connections, I'm curious about network infrastructure. Have there been any reported issues with our network providers or data centers?

Why it matters: Network problems can cause widespread connection failures. Expected answer: No reported network issues from our providers. Impact on approach: If network is stable, we'd look more closely at application-level problems.

• Thinking about our user base, I'm wondering if this affected all users equally. Do we have data on whether the issue was geographically localized or widespread across all regions?

Why it matters: Localized issues might point to regional infrastructure problems. Expected answer: The issue affected users across all regions. Impact on approach: If global, we'd focus on core infrastructure or configuration issues rather than regional factors.