Pratica di Shadowing: System Design: How to Build an API Rate Limiter - Impara a parlare inglese con i video
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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.
6
Most engineers approach this problem with a counter.
7
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.
📺 Stesso Canale
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Vocabolario e note di pronuncia per questa lezione
Questa lezione di conversazione di livello C1 si basa sul video “System Design: How to Build an API Rate Limiter”. Le parole che ritornano più spesso: Api, user, request, bucket, token. Questo video contiene 42 frasi e 594 parole da ripetere con lo shadowing. Il parlato dura 2:47. Chi parla va veloce, circa 213 parole al minuto: aspettati suoni legati e ridotti. Il 82% delle parole rientra nelle 3.000 più comuni dell’inglese; conviene studiare le altre prima di iniziare.
Vocaboli chiave di questo video
Le 14 parole più avanzate del video, con pronuncia e significato:
| Parola | Pronuncia | Significato |
|---|---|---|
| bucket sostantivo | /ˈbʌkɪt/ | secchio |
| token sostantivo | /ˈtoʊkən/ | simbolo, segno |
| server sostantivo | /ˈsɝvɚ/ | server |
| burst verbo | /bɜːst/ | scoppiare, esplodere |
| clock sostantivo | /klɑk/ | contachilometri, tachimetro |
| crystal sostantivo | /ˈkɹɪstəl/ | cristallo |
| fundamental aggettivo | /ˌfʌn.dəˈmɛn.təl/ | fondamentale |
| implementation sostantivo | /ˌɪmplɪmənˈteɪʃən/ | implementazione, attuazione |
| drain sostantivo | /dɹiːn/ | scolo |
| gateway sostantivo | /ˈɡeɪtˌweɪ/ | portale |
| reset verbo | /ɹiːˈsɛt/ | azzerare, rimettere a zero |
| millisecond sostantivo | /ˈmɪlɪˌsɛkənd/ | millisecondo |
| refill sostantivo | /ˈɹiː.fɪl/ | ricarica, cartuccia |
| simplification sostantivo | /ˌsɪm.plɪ.fɪˈkeɪ.ʃən/ | semplificazione |
I phrasal verb che sentirai
| Parola | Significato |
|---|---|
| slow down verbo | rallentare, decelerare |
La grammatica di questo video
Le strutture che chi parla usa di più, con le parole esatte del video:
| Struttura | Nel video |
|---|---|
| Frasi condizionali if + frase, will/would + verbo — una condizione e il suo risultato | If the bucket is empty, we will reject |
| Forma passiva be + participio passato — conta ciò che accade, non chi lo fa | is allowed · is made · are sent |
Pronuncia a cui fare attenzione
- I suoni “sh” e “zh”: implementation /ˌɪmplɪmənˈteɪʃən/, simplification /ˌsɪm.plɪ.fɪˈkeɪ.ʃən/
- Parole lunghe — attenzione all’accento: fundamental /ˌfʌn.dəˈmɛn.təl/, implementation /ˌɪmplɪmənˈteɪʃən/, millisecond /ˈmɪlɪˌsɛkənd/, simplification /ˌsɪm.plɪ.fɪˈkeɪ.ʃən/
I suoni difficili per chi parla italiano:
- Consonante finale — senza aggiungere una vocale dopo: bucket /ˈbʌkɪt/, burst /bɜːst/, clock /klɑk/, reset /ɹiːˈsɛt/, millisecond /ˈmɪlɪˌsɛkənd/
Come esercitarsi con questo video
- Ascolta tutto il video una volta senza parlare e annota le parole che non conosci.
- Inizia a velocità 0,75×, fai shadowing frase per frase e torna alla velocità normale quando diventa facile.
- Registrati e confronta con l’originale, facendo attenzione a parole come bucket, token, server.
Cos'è la tecnica dello Shadowing?
Shadowing è una tecnica di apprendimento delle lingue supportata da studi scientifici, originariamente sviluppata per la formazione dei traduttori professionisti e resa popolare dal poliglotta Dr. Alexander Arguelles. Il metodo è semplice ma potente: ascolti un audio in inglese di madrelingua e lo ripeti immediatamente ad alta voce — come un'ombra che segue il parlante con un ritardo di solo 1–2 secondi. A differenza dell'ascolto passivo o degli esercizi di grammatica, lo shadowing costringe il tuo cervello e i muscoli della bocca a elaborare e riprodurre simultaneamente i modelli di discorso reale. La ricerca dimostra che migliora significativamente la precisione della pronuncia, l'intonazione, il ritmo, il discorso connesso, la comprensione dell'ascolto e la fluidità del parlato — rendendolo uno dei metodi più efficaci per la preparazione alla prova di speaking dell'IELTS e per la comunicazione reale in inglese.