How we diagnosed and resolved Redis latency spikes with BPF and other tools

The article examines a persistent latency issue in a Redis instance used as a least recently used (LRU) cache for GitLab.com, focusing on the use of BPF and profiling tools to uncover the root cause. It details an iterative hypothesis-testing approach that reveals a three-phase cycle causing chronic latency spikes due to CPU saturation during eviction bursts. The investigation identifies client input/output buffers as the mystery memory consumer, which bloat during evictions and release memory rapidly afterward, leading to self-amplifying eviction bursts. The team ruled out externally triggered causes and explored potential mitigations, such as adjusting Redis settings and client behavior, to improve memory efficiency. The solution involved reducing cache time-to-live (TTL), switching to client-side caching for certain keys, and partitioning cache keys, which successfully eliminated the latency spikes and improved the user experience. The article highlights the importance of understanding Redis eviction behaviors and offers insights into preventing similar issues by avoiding memory and CPU saturation.

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