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OpenFGA Implements Self-Tuning Strategy Planner with Thompson Sampling to Reduce P99 Latency by 98%

By

elbuo

4mo ago· 12 min readenInsight

Summary

The article details how OpenFGA, an open-source authorization system modeled after Google's Zanzibar, addressed tail latency challenges in its critical Check operation. The system implemented a self-tuning strategy planner using Thompson Sampling to dynamically optimize graph traversal strategies, resulting in a 98% reduction in P99 latency. This approach moved from static rules to adaptive decision-making for authorization queries, significantly improving performance for latency-critical systems.

Key quotes

· 5 pulled
Operating a latency-critical system means the inevitable work of reducing tail latency. Tail latency refers to the response time experienced by the slowest requests (the outliers), rather than the average.
Since authorization happens on every request, these decisions must be fast; otherwise, they directly add overhead to the total response time.
For OpenFGA, an open-source authorization system modeled after Google's Zanzibar, that powers up Auth0 FGA, this challenge manifests in its most critical operation: Check.
Answering 'Can user X access resource Y?' requires traversing relationship gra
Learn how OpenFGA used Thompson Sampling to reduce P99 latency by 98%, moving from static rules to a dynamic, self-tuning strategy planner for graph traversals.
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Learn how OpenFGA used Thompson Sampling to reduce P99 latency by 98%, moving from static rules to a dynamic, self-tuning strategy planner for graph traversals.

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