I have a feeling this design is way too high level and basic.

Can please make a video explaining database used by popular techs for specific usecase

how we scale this kind of operation lets say on 1M rows

Wait a minute...what if zookeeper is down?

If to a 2Mb chunk, (say 5th chunk), I add 3 characters, It becomes 2Mb 3 bytes. So, Do I add chunks 5.i and 5.ii back to the file store?

The good old days, when tech thrived without the constant promotion of courses

@26:14 : If the devices are offline, for that I think, we are using Clients in our services...I think queues will be used for scaling. @33:19 : Seems statement got incomplete during editing?

I didnt get how the time complexity is calculated here

good explanation!! Thank you

00:04 Rate limiting is essential for managing API usage and protecting against misuse and attacks. 04:46 Rate-limiting algorithm for token management 09:30 The algorithm for managing tokens and requests can be memory efficient but may cause race conditions in a distributed environment. 13:57 Using sliding locks algorithm to calculate the rate in real time 18:28 Implement sliding-window counter for efficient memory usage 22:47 The solution optimizes memory usage by using counters instead of storing every request entry 27:11 Inconsistency in rate limiting leads to exceeding request limits 31:28 Syncing data between distributed systems can result in latency and race conditions.

Thanks

isn't DB is Redis?

shard by stock name in RDBMS, partition by stock name in the first mq. How do you trade off between hot spot issue with access latency? latency >> hot spot(could cause availability issue)

Thanks a lot for this wonderful series

excellent video

Hi Narendra, Relaxing Rate Limit and Local Memory + sync service is almost similar because in both the solution we might serve couple of extra request. what is your thought on my understanding?

He is the best

❤ Best video out there

Nice content + Nice shirt

If we have listed an end point that calls 2-3 services, how will the api gateway combine the response and send it back to client, does that mean we need to deploy an another service , at API end point level

Very good explanation

Rate limiter system design in Hindi : kzbin.info/www/bejne/oZnLlmqXq9iqZ8k Easy to understand...

kzbin.info/www/bejne/oZnLlmqXq9iqZ8k

Really a great explanation. 🎉

Boss 4166/3600 is 1.15 not 150, so wrong capacity estimation

Please start making the videos again. We are waiting!!!!!

Nice visualization, thanks!

This is a SysD primer disguised as Netflix use case. You can really fit these pieces anywhere. Thanks for your effort!

like the video thanks for sharing. But i think the math is wrong for cap estimation. 100K / 24 / 3600 is not 150 writes per second - it's 1.15 - not sure if anyone else caught that - and the video is 4 years old. i didn't scan all the comments

the base62 of random numbers in the ranges of lakhs gives the output of length 4 or 5 characters only. I observed that Base62 will start giving 7chars code starting from 62^6. Now, the question is how do we keep these counter values which are in big range?

Thanks for sharing this knowledge

isn't this ridiculously wrong? you don't build bit map index, you build a btree index bitmap is index access, the way planner decides to access the btree index. dude, wtf, bitmap index access is all about not accessing the same block page

Good one. You said that there could be more than one server which will be registered with zookeeper. But what if there is more than one instance of given server? how two instances will coordinate to not create same counter?

Nice explanation, thank you so much...🙏

Best explanation I've seen online 👍

do we not consider zookeeper going down? Is it not single point of failure?

I am confused between area server and game server? as you say game server will have information about map

kutta chilla raha hai

Thanks

Bad video!

Quite good explanation.

You explained it in excellent way....thanks

Great Explanation !!!!

How it Works Rider Request: When a rider requests a ride, the request is sent to Disco. Driver Availability: Disco identifies nearby drivers who are available and meet the rider's requirements. Matching: Using complex algorithms, Disco matches the rider with the most suitable driver. Notification: Both the rider and driver are notified about the match.

Thank you very much

thanks

Thanks

Thanks

Thanks

Thanks