Why has Redis's RediSearch module seen a 30% drop in query throughput over the past week?

Introduction

Redis's RediSearch module experiencing a 30% drop in query throughput over the past week is a critical issue that demands immediate attention. This performance degradation could significantly impact user experience and overall system reliability. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term solutions.

Step 1

Clarifying Questions (3 minutes)

• Given the sudden drop, I'm thinking there might have been a recent change. Has there been any recent update to RediSearch or the underlying Redis infrastructure?

Why it matters: Recent changes often correlate with performance issues. Expected answer: Yes, there was a minor update last week. Impact on approach: If confirmed, we'd focus on the update's impact.

• Considering the specificity of the 30% drop, I'm curious about our monitoring setup. Are we seeing this consistently across all instances and queries, or is it more pronounced in specific scenarios?

Why it matters: Helps narrow down if it's a global issue or specific to certain use cases. Expected answer: The drop is more significant for complex queries. Impact on approach: We'd analyze query patterns and complexity if this is the case.

• Looking at the timing, I'm wondering about any changes in user behavior or traffic patterns. Have we seen any unusual spikes or changes in query patterns over the past week?

Why it matters: External factors could be influencing the throughput. Expected answer: No significant changes in user behavior noted. Impact on approach: If confirmed, we'd focus more on internal system issues.

• Considering potential data growth, I'm curious about the dataset size. Has there been any significant increase in the volume of data being searched over the past week?

Why it matters: Data volume can impact search performance. Expected answer: Data growth has been steady, no unusual spikes. Impact on approach: If data volume is stable, we'd look more closely at query execution and indexing.