Rate limiting with CL.THROTTLE prevents ad fatigue by controlling impression frequency—allowing controlled bursts while maintaining smooth ad delivery at scale.

If you’re a company operating in the AdTech space, you understand how important it is to optimize ad impressions. Show too few ads, and you’re leaving money on the table. Show too many of the same ads, and people get annoyed. Ensuring ads reach your target audience effectively without becoming intrusive can be a struggle to manage.

Ad fatigue is a known phenomenon in digital advertising. While repeated exposure increases brand retention, bombarding users with the same ad too often can cause annoyance and negative brand perception. Finding the right balance between ad exposure and user experience is crucial. One of the key strategies used to maintain this balance is frequency capping, also known as rate limiting.

Frequency capping ensures that a user does not see the same ad too many times within a specific period. For example, as an advertiser, you might want to set a cap of no more than seven impressions per day for a particular user for a specific ad. To implement frequency capping effectively, AdTech companies need a fast and scalable rate-limiting mechanism. Traditional solutions are no longer able to support the scale at which today’s growing AdTech platforms operate.

Dragonfly is able to do significantly better in this area thanks to its native support for rate limiting. In this blog, we’ll learn about what Dragonfly is and what features it offers that make it the perfect choice for such a use case.

With these arguments, we control how often an ad (ID 123) is delivered to a user (ID user_456), allowing precisely 10 impressions per hour. This means an ad delivery request is permitted every 360 seconds, and any additional requests within that window are rejected—effectively distributing impressions evenly without allowing bursts.

However, this configuration is quite restrictive. What if we want to permit a small burst of deliveries to the same user? In that case, we can adjust the arguments as follows: