OpenFGA reduced P99 tail latency by up to 98% using a self-tuning strategy planner based on Thompson Sampling. The system treats graph traversal as a multi-armed bandit problem, maintaining probability distributions for each traversal strategy and continuously learning from production latency. By encoding domain knowledge

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Table of contents
The ProblemOur Approach: Why We Chose Thompson SamplingThe Art of the Prior: Encoding Domain KnowledgeProduction Results: Performance and the Self-Tuning ImpactTakeaways

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