proposal: x/time/rate: add tokens apart of time

[clwluvw]

What did you do?

I'm trying to add tokens to the bucket apart of the time so this can help to have distributed rate-limiting so that another process can update tokens in the other one if the token is used there.

What did you expect to see?

There can be a function called AddToken that let you add tokens to the bucket apart of the time, but because the scenarios that anyone can have are different (like using AllowN and not waiting to fill the tokens again) there should be also a function called Tokens to return the current tokens apart of time so based on the current tokens there can be a possibility to decrease the tokens apart of the time.

// AddTokens will decrease the remaining tokens by n
func (lim *Limiter) AddTokens(n float64) {
	lim.tokens -= n
}

// Tokens will return the current Limiter tokens apart of time
func (lim *Limiter) Tokens() float64 {
	return lim.tokens
}

func (lim *Limiter) AddToken() {
	lim.AddTokens(1)
}

If it makes sense I can propose my change for it. I've tested it locally and I could achieve my goal with it!

[seankhliao]

cc @Sajmani

[Sajmani]

I'm sorry but I do not understand this proposal. There is an accepted proposal to expose Tokens, but not one to change the number of tokens directly:
#50035 (comment)

[clwluvw]

@Sajmani well actually as I described above I wanted to add tokens to the bucket (limiter) apart of time which means for example If I have two threads that are using different limiters they can update each other by adding a token to their bucket (limiter).
Do you have any better idea to add tokens to the limiter apart from the time? because if you use AllowN or other functions they are based on the time so if another thread wants to add tokens it won't make sense.

A good example is to assume you have two HTTP servers and you want to rate-limit requests. Both of them are active and exposed to the user so they should have the same value of current req/s for rate-limiting otherwise user can heat the API double than what it should be.
With this proposal, we can add tokens to the buckets from other threads/processes so it can help to solve this problem.

[Sajmani]

Is the goal to enable balancing of rates across multiple instances of rate.Limiter (possibly in multiple processes)?

[clwluvw]

@Sajmani Actually the goal is to replicate the rates to the multiple instances of rate.Limiter by making fake tokens, so it can assume that there are more tokens gone without needing to call AllowN/ReserveN that updates the tokens by time durations.

[Sajmani]

Are you replicating the rates or the rate limits? SetLimit and SetBurst allow you to sync the rate limits across multiple rate limiters.

[clwluvw]

@Sajmani I'm not going to sync the limits and bursts with the rate.Limiter instances. I'm going to replicate/aggregate the current tokens (rate) between the rate.Limiter so if one token is gone from one rate.Limiter, it would be gone from the others as well.
So in this case no matter the user is hitting which rate.Limiter, all have the same consumed tokens (rate).

[Sajmani]

Ah, got it! So you have per-user rate limiters on multiple servers, and you want to deduct tokens on all servers whenever the user consumes tokens on any of the servers.
In theory if the user's requests were distributed evenly across the servers, then you could just set the per-user rate at each server to limit/(number of servers) and not do any synchronization.
But if you're using a load-balancing policy that's not evenly distributed (or intentionally keeps users on a single server for improved locality, cache use, DB client reuse, etc), then they will only consume tokens at the servers they're using.
If I'm understanding this correctly, the problem mainly occurs when the user's requests are distributed among a subset of K servers, is that right?
If so, wouldn't it be more efficient to update the rate at each of the servers that the users' requests are hitting to limit/K? This should involve a lot less synchronization than updating the tokens at each server, and you can use the existing SetLimit functionality.

[clwluvw]

the problem mainly occurs when the user's requests are distributed among a subset of K servers, is that right?

That is correct.

If so, wouldn't it be more efficient to update the rate at each of the servers that the users' requests are hitting to limit/K?

@Sajmani I didn't get that clearly what you mean. If you mean to stick a user to a server, actually, for scaling and being HA I'm going to expose 3 (n) load balancers to the user so a single client (source IP) can for example do 10k req/s and is being distributed (with some DNS tricks that let's skip this part =) ) to all of my load balancers (each 3.3k req/s). Now all of my load-balancers should be aware that the client (source IP) is doing 10k req/s not (3.3k req/s - or in some scenarios 1k on one server 3k on the other and 6k on the third one).
How can it be possible with SetLimit? In my implementation I'm setting the limit to 10k so how can setting a new limit help here? Can you provide me with an example, please?

[clwluvw]

ping @Sajmani =)

[blevz]

Any updates here? We have some use cases for getting current number of tokens for observability reasons

[Sajmani]

@blevz I think that's covered in #50035

[Sajmani]

@clwluvw Unfortunately, I really don't understand your use case. The approved proposal #50035 will add the Tokens accessor, but AddTokens does not seem like an appropriate addition. If you need it, please consider forking this package and modifying it yourself.