31 lines
1.8 KiB
Markdown
31 lines
1.8 KiB
Markdown
# Purpose
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This repository contains my implementations and explorations of rate limiting, drawn initially from the book _System Design Interview_.
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I'm embarking on this in order to get a great software engineering (probably back-end) job, and at the moment I have Happy Scribe in mind since I have an interview with them on August 24th, directly after our family vacation in Greece.
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Over a year ago (early 2022) I did a job search, and some of the interview processes ended right before or after the system design phase, so it's obviously something I need in my portfolio to truly be considered for senior dev roles. While I'd love to get a job as a junior or mid-level, my salary requirements and age (45) push me towards senior. That, and maybe the fact that I'm a decent programmer by now.
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# TODO
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- [ ] implement token bucket
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- [ ] in-app
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- [x] in-memory
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- [ ] redis
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- [ ] implement leaky bucket
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- in-app
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- [x] redis
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- [ ] redis cluster
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- [ ] Flask middleware - https://flask.palletsprojects.com/en/2.1.x/quickstart/#hooking-in-wsgi-middleware
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- [ ] NGINX - https://leandromoreira.com/2019/01/25/how-to-build-a-distributed-throttling-system-with-nginx-lua-redis/
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- https://www.nginx.com/blog/rate-limiting-nginx/
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- [ ] AWS API Gateway
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- [ ] HAProxy Stick Tables - https://www.haproxy.com/blog/introduction-to-haproxy-stick-tables
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- [ ] Cloudflare (Spectrum?)
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- [ ] implement expiring tokens
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- [ ] implement fixed window counter
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- [ ] implement sliding window log
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- [ ] implement sliding window counter
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- [ ] use session IDs or API keys instead of IP address
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- [ ] set headers appropriately in each case: https://www.ietf.org/archive/id/draft-polli-ratelimit-headers-02.html#name-ratelimit-headers-currently
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- [ ] implement different rate limiting for each endpoint, using a `cost` variable for a given task |