Understand and manage Clerk rate limits and quotas. Use when hitting rate limits, optimizing API usage, or planning for high-traffic scenarios. Trigger with phrases like "clerk rate limit", "clerk quota", "clerk API limits", "clerk throttling".
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name: clerk-rate-limits description: | Understand and manage Clerk rate limits and quotas. Use when hitting rate limits, optimizing API usage, or planning for high-traffic scenarios. Trigger with phrases like "clerk rate limit", "clerk quota", "clerk API limits", "clerk throttling". allowed-tools: Read, Write, Edit, Grep version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io
Clerk Rate Limits
Overview
Understand Clerk's rate limiting system and implement strategies to avoid hitting limits.
Prerequisites
- Clerk account with API access
- Understanding of your application's traffic patterns
- Monitoring/logging infrastructure
Instructions
Step 1: Understand Rate Limits
Clerk API Rate Limits (as of 2024)
| Endpoint Category | Free Tier | Pro Tier | Enterprise |
|---|---|---|---|
| Authentication | 100/min | 500/min | Custom |
| User Management | 100/min | 500/min | Custom |
| Session Management | 200/min | 1000/min | Custom |
| Webhooks | Unlimited | Unlimited | Unlimited |
Client-Side Limits
- SDK requests are automatically throttled
- Browser session: 10 requests/second
- Token refresh: 1 per 50 seconds (automatic)
Step 2: Implement Rate Limit Handling
// lib/clerk-client.ts
import { clerkClient } from '@clerk/nextjs/server'
interface RateLimitConfig {
maxRetries: number
baseDelay: number
}
async function withRateLimitRetry<T>(
operation: () => Promise<T>,
config: RateLimitConfig = { maxRetries: 3, baseDelay: 1000 }
): Promise<T> {
let lastError: Error | null = null
for (let attempt = 0; attempt < config.maxRetries; attempt++) {
try {
return await operation()
} catch (error: any) {
lastError = error
// Check for rate limit error
if (error.status === 429 || error.code === 'rate_limit_exceeded') {
const delay = config.baseDelay * Math.pow(2, attempt)
console.warn(`Rate limited, retrying in ${delay}ms (attempt ${attempt + 1})`)
await new Promise(resolve => setTimeout(resolve, delay))
continue
}
// Non-rate-limit error, throw immediately
throw error
}
}
throw lastError
}
// Usage
export async function getUser(userId: string) {
const client = await clerkClient()
return withRateLimitRetry(() => client.users.getUser(userId))
}
Step 3: Batch Operations
// lib/clerk-batch.ts
import { clerkClient } from '@clerk/nextjs/server'
// Instead of multiple individual calls
async function getBatchedUsers(userIds: string[]) {
const client = await clerkClient()
// Use getUserList with userId filter (single API call)
const { data: users } = await client.users.getUserList({
userId: userIds,
limit: 100
})
return users
}
// Paginated fetching with rate limit awareness
async function getAllUsers(batchSize = 100, delayMs = 100) {
const client = await clerkClient()
const allUsers = []
let offset = 0
while (true) {
const { data: users, totalCount } = await client.users.getUserList({
limit: batchSize,
offset
})
allUsers.push(...users)
offset += batchSize
if (allUsers.length >= totalCount) break
// Rate limit friendly delay
await new Promise(resolve => setTimeout(resolve, delayMs))
}
return allUsers
}
Step 4: Caching Strategy
// lib/clerk-cache.ts
import { unstable_cache } from 'next/cache'
import { clerkClient } from '@clerk/nextjs/server'
// Cache user data to reduce API calls
export const getCachedUser = unstable_cache(
async (userId: string) => {
const client = await clerkClient()
return client.users.getUser(userId)
},
['clerk-user'],
{
revalidate: 60, // Cache for 60 seconds
tags: ['clerk-users']
}
)
// In-memory cache for high-frequency lookups
const userCache = new Map<string, { user: any; timestamp: number }>()
const CACHE_TTL = 30000 // 30 seconds
export async function getUserWithCache(userId: string) {
const cached = userCache.get(userId)
if (cached && Date.now() - cached.timestamp < CACHE_TTL) {
return cached.user
}
const client = await clerkClient()
const user = await client.users.getUser(userId)
userCache.set(userId, { user, timestamp: Date.now() })
return user
}
Step 5: Monitor Rate Limit Usage
// lib/clerk-monitor.ts
interface RateLimitMetrics {
endpoint: string
remaining: number
limit: number
resetAt: Date
}
const metrics: RateLimitMetrics[] = []
export function trackRateLimit(response: Response) {
const remaining = response.headers.get('x-ratelimit-remaining')
const limit = response.headers.get('x-ratelimit-limit')
const reset = response.headers.get('x-ratelimit-reset')
if (remaining && limit) {
metrics.push({
endpoint: response.url,
remaining: parseInt(remaining),
limit: parseInt(limit),
resetAt: reset ? new Date(parseInt(reset) * 1000) : new Date()
})
// Alert if approaching limit
if (parseInt(remaining) < parseInt(limit) * 0.1) {
console.warn('Approaching rate limit:', {
remaining,
limit,
endpoint: response.url
})
}
}
}
export function getRateLimitMetrics() {
return metrics.slice(-100) // Last 100 entries
}
Output
- Rate limit handling with retries
- Batched API operations
- Caching implementation
- Monitoring system
Rate Limit Headers
x-ratelimit-limit: 100
x-ratelimit-remaining: 95
x-ratelimit-reset: 1704067200
Best Practices
- Batch requests - Use getUserList instead of multiple getUser calls
- Cache aggressively - User data rarely changes in real-time
- Use webhooks - Let Clerk push updates instead of polling
- Exponential backoff - Retry with increasing delays
- Monitor usage - Track rate limit headers
Error Handling
| Error | Cause | Solution |
|---|---|---|
| 429 Too Many Requests | Rate limit exceeded | Implement backoff, cache more |
| quota_exceeded | Monthly quota hit | Upgrade plan or reduce usage |
| concurrent_limit | Too many parallel requests | Queue requests |
Resources
Next Steps
Proceed to clerk-security-basics for security best practices.
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