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Overview

The token bucket algorithm limits requests by continuously adding tokens to a bucket at a fixed rate. Each request consumes tokens, and requests are denied when insufficient tokens are available.
A token bucket limits the rate of requests by continuously adding tokens to be consumed when servicing requests. The rate is the number of tokens added per period. The capacity is the maximum number of tokens that can accumulate.

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How It Works

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Continuous Token Addition

Unlike fixed window, tokens are added continuously rather than in bulk:
  1. Tokens are added at a rate of rate / period tokens per millisecond
  2. The bucket can hold up to capacity tokens (defaults to rate)
  3. When a request arrives, the system:
    • Calculates how many tokens have been added since the last request
    • Adds those tokens to the current value (up to capacity)
    • Attempts to consume the requested number of tokens

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Capacity and Rollover

The capacity parameter controls how many tokens can accumulate:
  • When capacity equals rate: No burst allowance, strict rate limiting
  • When capacity exceeds rate: Allows bursts if user has been inactive
// Strict rate limiting - no burst
{
  kind: "token bucket",
  rate: 10,
  period: MINUTE,
  capacity: 10,  // Same as rate
}

// Burst allowance - up to 20 messages if user was inactive
{
  kind: "token bucket",
  rate: 10,
  period: MINUTE,
  capacity: 20,  // Double the rate
}

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Visual Explanation

Here’s how tokens accumulate over time: 
Capacity: 20 tokens
Rate: 10 tokens/minute (0.167 tokens/second)

Time    Tokens  Action
0s      20      (full capacity)
1s      20      User sends 5 messages → 15 tokens remain
5s      15.67   Tokens added: 4s × 0.167 = 0.67
10s     16.5    Tokens added: 5s × 0.167 = 0.83
60s     20      Refilled to capacity (can't exceed 20)
Tokens are added continuously based on elapsed time, not in discrete intervals. This provides the smoothest possible rate limiting.

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Configuration

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Type Definition

From src/shared.ts: 
export const tokenBucketValidator = v.object({
  kind: v.literal("token bucket"),
  rate: v.number(),
  period: v.number(),
  capacity: v.optional(v.number()),
  maxReserved: v.optional(v.number()),
  shards: v.optional(v.number()),
  start: v.optional(v.null()),  // Always null for token bucket
});

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Parameters

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rate (required)

The number of tokens added per period. 
{ rate: 10 }  // 10 tokens per period

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period (required)

The time period in milliseconds. Use the provided constants: 
import { SECOND, MINUTE, HOUR, DAY } from "@convex-dev/rate-limiter";

{ period: MINUTE }  // 60,000 milliseconds

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capacity (optional)

Maximum tokens that can accumulate. Defaults to rate. 
{
  rate: 10,
  period: MINUTE,
  capacity: 30,  // Can accumulate up to 30 tokens
}

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maxReserved (optional)

Maximum tokens that can be reserved into the future. 
{
  rate: 100,
  period: MINUTE,
  maxReserved: 50,  // Can reserve up to 50 tokens ahead
}

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shards (optional)

Number of shards for high-throughput scenarios. See Scaling with Shards. 
{
  rate: 40000,
  period: MINUTE,
  shards: 10,  // Split across 10 shards
}

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Real Code Examples

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Basic Message Rate Limiting

import { RateLimiter, MINUTE } from "@convex-dev/rate-limiter";
import { components } from "./_generated/api";

const rateLimiter = new RateLimiter(components.rateLimiter, {
  // Allow one message every ~6 seconds (10 per minute)
  // Allows up to 3 in quick succession if they haven't sent many recently
  sendMessage: {
    kind: "token bucket",
    rate: 10,
    period: MINUTE,
    capacity: 3,
  },
});

// In your mutation:
export const sendMessage = mutation({
  args: { text: v.string() },
  handler: async (ctx, args) => {
    const userId = await getCurrentUser(ctx);
    const { ok, retryAfter } = await rateLimiter.limit(
      ctx,
      "sendMessage",
      { key: userId }
    );

    if (!ok) {
      throw new Error(`Rate limited. Retry in ${retryAfter}ms`);
    }

    // Send the message...
  },
});

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LLM API Rate Limiting

const rateLimiter = new RateLimiter(components.rateLimiter, {
  // LLM APIs often have token-based limits
  llmTokens: {
    kind: "token bucket",
    rate: 40000,      // 40k tokens per minute
    period: MINUTE,
    shards: 10,       // High throughput
  },
});

export const generateText = mutation({
  args: { prompt: v.string() },
  handler: async (ctx, args) => {
    const estimatedTokens = args.prompt.length / 4;  // Rough estimate

    const { ok, retryAfter } = await rateLimiter.limit(
      ctx,
      "llmTokens",
      { count: estimatedTokens }  // Consume multiple tokens
    );

    if (!ok) {
      throw new Error(`Rate limited. Retry in ${retryAfter}ms`);
    }

    // Call LLM API...
  },
});

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Failed Login Attempts

const rateLimiter = new RateLimiter(components.rateLimiter, {
  failedLogins: {
    kind: "token bucket",
    rate: 10,
    period: HOUR,
  },
});

export const login = mutation({
  args: { email: v.string(), password: v.string() },
  handler: async (ctx, args) => {
    const user = await getUserByEmail(ctx, args.email);

    if (!user || !verifyPassword(args.password, user.passwordHash)) {
      // Rate limit failed login attempts
      await rateLimiter.limit(
        ctx,
        "failedLogins",
        { key: args.email, throws: true }
      );
      throw new Error("Invalid credentials");
    }

    // Reset on successful login
    await rateLimiter.reset(ctx, "failedLogins", { key: args.email });

    // Create session...
  },
});

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Implementation Details

The token bucket calculation from src/shared.ts: 
if (config.kind === "token bucket") {
  const elapsed = now - state.ts;
  const rate = config.rate / config.period;
  value = Math.min(state.value + elapsed * rate, max) - count;
  ts = now;
  if (value < 0) {
    retryAfter = -value / rate;
  }
}
Key points:
  • elapsed: Time since last update in milliseconds
  • rate: Tokens per millisecond (rate / period)
  • New value: Previous value + (elapsed × rate), capped at capacity
  • retryAfter: Calculated as the time needed to accumulate missing tokens

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Use Cases

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Smooth Rate Limiting

Token bucket is ideal when you want the smoothest possible rate limiting without sudden boundaries: 
// Smooth API calls - tokens constantly replenishing
{
  kind: "token bucket",
  rate: 100,
  period: MINUTE,
}

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LLM and Streaming APIs

Many LLM APIs (OpenAI, Anthropic) use token-based limits: 
{
  kind: "token bucket",
  rate: 40000,      // Tokens per minute
  period: MINUTE,
  capacity: 60000,  // Allow some burst capacity
}

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User Actions with Burst Allowance

Allow users to perform bursts of actions if they’ve been inactive: 
// Allow 10 per minute, but up to 20 if user was inactive
{
  kind: "token bucket",
  rate: 10,
  period: MINUTE,
  capacity: 20,
}

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Advantages

  • Smoothest rate limiting: Tokens added continuously, not in chunks
  • Flexible burst handling: Capacity can be tuned independently of rate
  • Fair to bursty traffic: Inactive users accumulate tokens for later use
  • Works well with reservations: Can calculate exact retry times

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Limitations

  • No predictable resets: Tokens are always being added, no fixed “reset time”
  • Less intuitive: “10 per minute” doesn’t mean “10 at the start of each minute”
  • Requires calculation: Token count must be calculated on every check

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Next Steps

Fixed Window

Learn about the alternative fixed window strategy

Basic Usage

Start using token bucket rate limiting

Scaling with Shards

Handle high throughput scenarios

Reservations

Reserve capacity ahead of time

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