Tanvi Handa

Frontend Developer skilled in React.js JavaScript and Next.js.

[Tanvi Handa @T_dev02]

@AKirtesh Left

[Tanvi Handa @T_dev02]

@UtkarshSolves Js

[Tanvi Handa @T_dev02]

For Comparision of algos refer the given image :
Which rate limiting algorithm do you use the most and why?
#SystemDesign #Backend #RateLimiting

[Tanvi Handa @T_dev02]

If all Rate Limiting algorithms solve the same problem...
Why do we need 5 different ones?

After studying them one by one, I realized the answer isn't about finding the "best" algorithm.
It's about understanding trade-offs.
Here's a simple breakdown👇

[Tanvi Handa @T_dev02]

This thread is a quick revision of all 5 algorithms.
I've already shared detailed threads on each one with diagrams and visualizations.
If you want to understand any algorithm in depth check out the previous posts on my profile.

[Tanvi Handa @T_dev02]

Formula
Estimated Count =
(Previous Count × Remaining %)
+ Current Count

- Prevents burst traffic
- More accurate than Fixed Window
- Efficient & scalable

#SystemDesign #Backend #RateLimiting

[Tanvi Handa @T_dev02]

Learning Sliding Window Counter Algorithm

Instead of resetting requests every fixed interval it uses a rolling time window for more accurate and fair rate limiting.

[Tanvi Handa @T_dev02]

@ccodyy69 Vs code

[Tanvi Handa @T_dev02]

Building these animations is helping me learn system design concepts more deeply while sharing them with others.

Feedback is always welcome!

#SystemDesign #Backend #RateLimiting #SlidingWindowLog

[Tanvi Handa @T_dev02]

I created a short animation explaining the Sliding Window Log Algorithm.

Before explaining it, I first covered why the Fixed Window Counter isn't always the best choice.

[Tanvi Handa @T_dev02]

Cons:
• Stores every request timestamp
• Higher memory usage
• Slightly slower because old timestamps must be removed
• Doesn't scale as well for very high traffic compared to Token Bucket or Sliding Window Counter