algolia-rate-limits
Handle Algolia rate limits and throttling: per-key limits, indexing queue limits, 429 responses, and backoff strategies. Trigger: "algolia rate limit", "algolia throttling", "algolia 429", "algolia retry", "algolia backoff", "algolia too many requests".
What this skill does
# Algolia Rate Limits
## Overview
Algolia has two distinct rate limiting mechanisms: **per-API-key limits** (configurable, returns HTTP 429) and **server-side indexing limits** (protects cluster stability, returns HTTP 429 with specific messages). The `algoliasearch` v5 client has built-in retry with backoff, but you need to handle sustained rate limiting yourself.
## How Algolia Rate Limiting Works
### Per-API-Key Rate Limits
| Setting | Default | Where to Change |
|---------|---------|-----------------|
| `maxQueriesPerIPPerHour` | 0 (unlimited) | Dashboard > API Keys > Edit |
| `maxHitsPerQuery` | 1000 | Dashboard > API Keys > Edit |
| Search requests | Plan-dependent | Upgrade plan |
### Server-Side Indexing Limits
When the indexing queue is overloaded, Algolia returns 429 with these messages:
| Message | Meaning | Action |
|---------|---------|--------|
| `Too many jobs` | Queue full | Reduce batch frequency |
| `Job queue too large` | Too much pending work | Wait for queue to drain |
| `Old jobs on the queue` | Stuck tasks | Check dashboard > Indices > Operations |
| `Disk almost full` | Record quota near limit | Delete unused records or upgrade |
## Instructions
### Step 1: Configure Per-Key Rate Limits
```typescript
import { algoliasearch } from 'algoliasearch';
const client = algoliasearch(process.env.ALGOLIA_APP_ID!, process.env.ALGOLIA_ADMIN_KEY!);
// Create a rate-limited API key for frontend use
const { key } = await client.addApiKey({
apiKey: {
acl: ['search'],
description: 'Frontend search key — rate limited',
maxQueriesPerIPPerHour: 1000, // Per user IP
maxHitsPerQuery: 20,
indexes: ['products'], // Restrict to specific indices
validity: 0, // 0 = never expires
},
});
console.log(`Created rate-limited key: ${key}`);
```
### Step 2: Implement Backoff for Sustained 429s
```typescript
import { ApiError } from 'algoliasearch';
async function withBackoff<T>(
operation: () => Promise<T>,
config = { maxRetries: 5, baseDelayMs: 1000, maxDelayMs: 30000 }
): Promise<T> {
for (let attempt = 0; attempt <= config.maxRetries; attempt++) {
try {
return await operation();
} catch (error) {
if (attempt === config.maxRetries) throw error;
// Only retry on 429 or 5xx
if (error instanceof ApiError) {
if (error.status !== 429 && error.status < 500) throw error;
}
// Exponential backoff with jitter
const delay = Math.min(
config.baseDelayMs * Math.pow(2, attempt) + Math.random() * 500,
config.maxDelayMs
);
console.warn(`Rate limited (attempt ${attempt + 1}). Retrying in ${delay.toFixed(0)}ms`);
await new Promise(r => setTimeout(r, delay));
}
}
throw new Error('Unreachable');
}
// Usage
const { hits } = await withBackoff(() =>
client.searchSingleIndex({ indexName: 'products', searchParams: { query: 'laptop' } })
);
```
### Step 3: Throttled Batch Indexing
```typescript
import PQueue from 'p-queue';
// Limit concurrent indexing operations to avoid overloading the queue
const indexingQueue = new PQueue({
concurrency: 1, // One batch at a time
interval: 1000, // Per second
intervalCap: 2, // Max 2 operations per second
});
async function throttledBulkIndex(records: Record<string, any>[]) {
const BATCH_SIZE = 500;
const chunks: Record<string, any>[][] = [];
for (let i = 0; i < records.length; i += BATCH_SIZE) {
chunks.push(records.slice(i, i + BATCH_SIZE));
}
let indexed = 0;
await Promise.all(
chunks.map(chunk =>
indexingQueue.add(async () => {
const { taskID } = await client.saveObjects({
indexName: 'products',
objects: chunk,
});
await client.waitForTask({ indexName: 'products', taskID });
indexed += chunk.length;
console.log(`Indexed ${indexed}/${records.length}`);
})
)
);
}
```
### Step 4: Monitor Usage Approaching Limits
```typescript
// Check current API key usage via the dashboard or programmatically
async function checkKeyUsage(apiKey: string) {
const keyInfo = await client.getApiKey({ key: apiKey });
console.log({
description: keyInfo.description,
maxQueriesPerIPPerHour: keyInfo.maxQueriesPerIPPerHour,
acl: keyInfo.acl,
indexes: keyInfo.indexes,
});
}
// Check record count vs plan limit
async function checkRecordUsage() {
const { items } = await client.listIndices();
const totalRecords = items.reduce((sum, idx) => sum + (idx.entries || 0), 0);
console.log(`Total records across all indices: ${totalRecords.toLocaleString()}`);
}
```
## Error Handling
| Scenario | Detection | Response |
|----------|-----------|----------|
| Burst spike (429) | `ApiError` with status 429 | Built-in retry handles it; add backoff for persistence |
| Sustained overload | Repeated 429s across minutes | Reduce batch size and frequency |
| Indexing queue full | 429 with "Too many jobs" | Pause indexing, wait for queue drain |
| Plan limit reached | 429 with quota message | Upgrade plan or reduce record count |
## Resources
- [API Key Rate Limiting](https://support.algolia.com/hc/en-us/articles/4905140190353)
- [Indexing Rate Limits](https://support.algolia.com/hc/en-us/articles/4406975251089)
- [p-queue](https://github.com/sindresorhus/p-queue)
## Next Steps
For security configuration, see `algolia-security-basics`.
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