Comments (6)
I've implemented this 3 years ago for ASP.NET Web API, you can see the docs here.
Attribute-based rate limiting has a down side: action filters are executed after the middlewares. If you are using OAuth or any other type of authorization, the rate limit will happen after the auth logic, making the whole point of IP rate limiting useless. I agree that is easier to apply the limits using attributes and if you only want to rate limit based on client id then you probably don't care that the limiting is done after the middleware stack is executed. I will consider adding this in a future release.
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I didn't think about the fact that the current middleware approach comes before action filters, however, like you mentioned this would still work fine for client based rate limiting. Thanks for giving it a consideration.
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Even for client based rate limiting the attribute usage is very limited. If you have different limits for each subscription (like most API products have) then you can't use the attribute because the rate limit values are stored in the database and you clearly don't want to hardcode those in your code inside the attribute declaration. I think attribute-based rate limiting works only for public APIs that are applying the same limits to all their users, like Twitter does.
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You don't always have to query the database to get information like that. For example, JWT tokens could hold information about the client's rate limits.
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My approach is to store the client limits in cache (local or distributed). If it's local cache, then at app startup I load the rate limits from db in cache, then I can update the cache if a client gets removed or added while the app is running. If the app needs scaling, then I use Redis to store the limits so no matter the app instance a clients ends up on, the limit is applied. The JWT token approach will not work if your app has more then one instance because the load balancer in front of your app will forward a client to different instances based on the load. To rate limit a client that can call multiple app nodes in parallel, you need a mechanism to create a distributed lock and increment the rate limit counter atomically.
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I think we misunderstood each other. I was referring to the JWT token holding what the client's rate limit policies are (as opposed to having to query the DB for this information), not their counter. Having looked further into how client rate limiting works in this library though (I've just been using IP rate limiting for my current implementation), I don't think that is even supported by the library. It seems that client policies are also hard coded into settings.
Update: Nevermind. It seems you can:
I think I am overthinking this a bit and we're getting a bit off topic. I'll go ahead and close this issue for now since it seems there are many reasons at play as to why it can't be easily supported. Thanks!
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Related Issues (20)
- How to order rules so that more specific rules override more general rules HOT 2
- How can I disable rate limiting for google bots?
- Incremental Rate limiting
- No fallback if Redis isn't available
- How to let Get and Post use different Quota exceeded response
- ClientRateLimitOptions reload HOT 2
- rate limiting is not working for with .net6 and AspNetCoreRateLimit 5.0 HOT 1
- Getting CORS error instead of 429 (when using AspNetCoreRateLimit Nuget)
- Does it support interface access control based on queues
- Per user rate limit with seeding of the current usages HOT 1
- Endpoint path involving * (variable) not working correctly HOT 3
- Is there a way to rate limit globally on an end-point HOT 1
- same ip with different device in lan HOT 1
- Using Azure redis
- Post or put rule not working
- How to load client rules on execution, not startup HOT 1
- Release new version
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