We needed to send Slack notifications for specific events but had to enforce rate limits to avoid overwhelming the channel. Here’s how the limit

Hierarchical rate limiting with Redis sorted sets

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2025-01-13 09:30:06

We needed to send Slack notifications for specific events but had to enforce rate limits to avoid overwhelming the channel. Here’s how the limits worked:

In our case, the event types are limited, and the category limits are both uniform and significantly smaller than the global limit, so this isn’t a concern.

The notification sender service runs on multiple instances, each processing events and sending notifications independently. Without a shared system to enforce rate limits, these instances would maintain separate counters for global and category-specific limits. This would create inconsistencies because no instance would have a complete view of the overall activity, leading to conflicts and potential exceedance of limits.

Redis provides a centralized state that all instances can access, ensuring they share the same counters for rate limits. This removes inconsistencies and makes rate limiting reliable, even when the notification sender scales to multiple instances.

Sorted sets in Redis track notifications within a rolling time window by using timestamps as scores, which keeps entries ordered by time. The implementation: