Prática de Shadowing: System Design: How to Build an API Rate Limiter - Aprenda a falar inglês com vídeo
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1
Let's design an API rate limiter for an application that takes thousands of requests per second.
2
User journey is simple.
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User can make API calls to your server to do something.
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Each user is allowed to make 100 API calls per minute.
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If a user makes more than 100 calls per minute, then your server will not process those API calls.
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Most engineers approach this problem with a counter.
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For each user, you store user ID, count of API calls, and current minute.
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Every time a request is made by user, you increase this count, and you will reject the requests once it passes 100 requests.
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This implementation is good enough for internal API calls, but let's take two specific examples why this solution is not good.
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Let's say user Alan is a burst user, and makes 100 API calls in first two seconds.
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Then he will get rejected for the next 58 seconds.
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Alan will be able to make calls when next minute starts.
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And our second user, John, sends 100 API requests, but these requests are sent at the last second of the current minute.
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The next second clock will reset to new minute, and John can send another 100 requests.
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Basically, John sent 200 requests in 2 seconds, because according to Counter, these 100 requests belong to different minutes.
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Basically, users will experience different behavior of APIs based on when they make the API call.
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There is a fundamental issue with the approach we just discussed.
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The Counter is watching the clock instead of watching the user.
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Let's see a better approach.
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So, we will give every user a bucket that holds 100 tokens.
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Every API request from user takes one token out, and we will keep filling the bucket at a rate of 100 tokens per minute, which is approximately 1.67 tokens per second.
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For simplification, let's assume we will fill two tokens per second.
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If user doesn't make any API call, the bucket will remain at 100, and we don't need to fill.
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If the bucket is empty, we will reject the request.
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This token bucket approach is what Stripe, GitHub, and most API gateways actually use for tracking API calls.
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Now let's take a look at Alan and John's requests again, and see how this bucket system will work.
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Alan drains all 100 tokens in 2 seconds.
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Then Alan has to slow down.
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Bucket fills about 2 tokens per second.
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That's why he can now make 2 calls per second.
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John, who is making 100 API calls at the end of the minute, will also need to wait for Bucket to fill, because once he makes 100 requests in a second, Bucket will get empty.
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So he can also make about 2 per second, as Bucket fills with time.
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Next question is, how do we store these buckets?
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We just need to store the token count, and the time of the last refill, so that you can add tokens per second.
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But what if your app works at large scale, and you have 20 different servers accepting API calls.
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Two requests for the same user can land on two servers in the same millisecond.
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Therefore, you keep the bucket outside the servers, in one common shared storage.
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This storage needs to be fast, and that's why we usually use Redis.
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When any of these 20 servers processes any API call, we change the count at this common Redis.
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To make this crystal clear in your mind, you need to remember that request limit is not just one number.
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It's two numbers.
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First, how much a user can burst in one go, and second, how fast they can go after the burst.
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Vocabulário e dicas de fala para esta lição
Esta aula de conversação de nível C1 usa o vídeo “System Design: How to Build an API Rate Limiter”. As palavras que mais se repetem: Api, user, request, bucket, token. Este vídeo tem 42 frases e 594 palavras para praticar shadowing. A fala dura 2:47. O falante fala rápido, cerca de 213 palavras por minuto, então espere sons ligados e reduzidos. 82% das palavras estão entre as 3.000 mais comuns do inglês; vale a pena estudar o restante antes de começar.
Vocabulário principal deste vídeo
As 14 palavras mais avançadas do vídeo, com pronúncia e significado:
| Palavra | Pronúncia | Significado |
|---|---|---|
| bucket substantivo | /ˈbʌkɪt/ | balde |
| token substantivo | /ˈtoʊkən/ | símbolo, sinal |
| server substantivo | /ˈsɝvɚ/ | servidor, server |
| burst verbo | /bɜːst/ | arrebentar, estourar |
| clock substantivo | /klɑk/ | velocímetro |
| crystal substantivo | /ˈkɹɪstəl/ | cristal |
| belong verbo | /bɪˈlɒŋ/ | pertencer |
| fundamental adjetivo | /ˌfʌn.dəˈmɛn.təl/ | fundamental |
| implementation substantivo | /ˌɪmplɪmənˈteɪʃən/ | implementação |
| drain substantivo | /dɹiːn/ | dreno, ralo |
| reset verbo | /ɹiːˈsɛt/ | repor, restaurar |
| millisecond substantivo | /ˈmɪlɪˌsɛkənd/ | milissegundo |
| refill substantivo | /ˈɹiː.fɪl/ | refill |
| simplification substantivo | /ˌsɪm.plɪ.fɪˈkeɪ.ʃən/ | simplificação |
Phrasal verbs que você vai ouvir
| Palavra | Significado |
|---|---|
| slow down verbo | desacelerar |
Gramática neste vídeo
As estruturas que o falante mais usa, com as palavras exatas do vídeo:
| Estrutura | No vídeo |
|---|---|
| Frases condicionais if + oração, will/would + verbo — uma condição e seu resultado | If the bucket is empty, we will reject |
| Voz passiva be + particípio passado — o foco está no que acontece, não em quem faz | is allowed · is made · are sent |
Pronúncia para ficar de olho
- Os sons de “sh” e “zh”: implementation /ˌɪmplɪmənˈteɪʃən/, simplification /ˌsɪm.plɪ.fɪˈkeɪ.ʃən/
- Palavras longas — acerte a sílaba tônica: fundamental /ˌfʌn.dəˈmɛn.təl/, implementation /ˌɪmplɪmənˈteɪʃən/, millisecond /ˈmɪlɪˌsɛkənd/, simplification /ˌsɪm.plɪ.fɪˈkeɪ.ʃən/
Sons difíceis para falantes de português:
- Consoante final — sem acrescentar um “i” depois: bucket /ˈbʌkɪt/, burst /bɜːst/, clock /klɑk/, reset /ɹiːˈsɛt/, millisecond /ˈmɪlɪˌsɛkənd/
- /l/ final — a língua toca o céu da boca, não vira “u”: crystal /ˈkɹɪstəl/, fundamental /ˌfʌn.dəˈmɛn.təl/, refill /ˈɹiː.fɪl/
Como praticar com este vídeo
- Ouça o vídeo inteiro uma vez sem falar e anote as palavras que você não conhece.
- Comece na velocidade 0,75×, faça shadowing frase por frase e volte à velocidade normal quando ficar fácil.
- Grave a sua voz e compare com o original, prestando atenção a palavras como bucket, token, server.
O que é a Técnica de Shadowing?
Shadowing é uma técnica de aprendizado de idiomas com base científica, originalmente desenvolvida para o treinamento de intérpretes profissionais. O método é simples, mas poderoso: você ouve áudio em inglês nativo e repete imediatamente em voz alta — como uma sombra seguindo o falante com 1-2 segundos de atraso. Pesquisas mostram melhora significativa na precisão da pronúncia, entonação, ritmo, sons conectados, compreensão auditiva e fluência na fala.