A bug in the GitHub's Rate Limiter

Summary

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Takeaways

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• 😀 The script outlines strategies for managing conflicts through effective communication.
• 😀 Empathy is essential for connecting with others and understanding their perspectives.
• 😀 Continuous improvement in communication skills is necessary for personal and professional growth.

Q & A

What is the main purpose of rate limiting in systems like GitHub?

Rate limiting is essential to keep products stable and prevent abuse by controlling the number of requests a user can make within a specific time frame.

What were the initial problems GitHub faced with their rate limiter using MCache?

The initial problems included key eviction by MCache, which led to inconsistencies in user experience, and the limitation of having a single MCache cluster that didn't scale well across multiple data centers.

Why did GitHub decide to switch to Redis for rate limiting?

GitHub switched to Redis due to its simple sharding and replication setup, application-level routing of requests, easy creation of read replicas, built-in TTL for key expiration, and support for complex Lua scripts.

What issue did GitHub encounter after implementing Redis for rate limiting?

GitHub experienced a problem known as 'wobbling,' where the rate limit reset headers showed inconsistent values due to network latency and processing time between requests.

What does the rate limit reset header indicate in GitHub's API responses?

The rate limit reset header indicates the exact time at which the user's rate limit will reset, which helps users manage their API request limits effectively.

How did the 'wobbling' issue manifest in API responses?

The 'wobbling' issue appeared when the reset header showed fluctuating values due to timing discrepancies in request processing, leading to some users receiving different reset times for their rate limits.

What was the root cause of the wobbling problem?

The root cause was the time that passed between the request being sent to Redis and the response being computed, leading to inconsistent values in the rate limit reset header.

What solution did GitHub implement to fix the wobbling issue?

GitHub fixed the wobbling issue by adding an additional key in the database to persist the reset time, ensuring it remained stable and was not recalculated at runtime.

What role do Lua scripts play in GitHub's rate limiting mechanism?

Lua scripts are used to adjust the counters for rate limit keys atomically in Redis, allowing GitHub to manage rate limiting efficiently and handle concurrent requests accurately.

What did GitHub prioritize to resolve the issues they faced after implementing Redis?

To resolve the issues, GitHub prioritized accuracy in their rate limit headers, even if it meant increasing their storage footprint by persisting additional data in the database.