Skillshub algolia-rate-limits

install
source · Clone the upstream repo
git clone https://github.com/ComeOnOliver/skillshub
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ComeOnOliver/skillshub "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/jeremylongshore/claude-code-plugins-plus-skills/algolia-rate-limits" ~/.claude/skills/comeonoliver-skillshub-algolia-rate-limits && rm -rf "$T"
manifest: skills/jeremylongshore/claude-code-plugins-plus-skills/algolia-rate-limits/SKILL.md
source content

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

SettingDefaultWhere to Change
maxQueriesPerIPPerHour
0 (unlimited)Dashboard > API Keys > Edit
maxHitsPerQuery
1000Dashboard > API Keys > Edit
Search requestsPlan-dependentUpgrade plan

Server-Side Indexing Limits

When the indexing queue is overloaded, Algolia returns 429 with these messages:

MessageMeaningAction
Too many jobs
Queue fullReduce batch frequency
Job queue too large
Too much pending workWait for queue to drain
Old jobs on the queue
Stuck tasksCheck dashboard > Indices > Operations
Disk almost full
Record quota near limitDelete unused records or upgrade

Instructions

Step 1: Configure Per-Key Rate Limits

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

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

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

// 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

ScenarioDetectionResponse
Burst spike (429)
ApiError
with status 429
Built-in retry handles it; add backoff for persistence
Sustained overloadRepeated 429s across minutesReduce batch size and frequency
Indexing queue full429 with "Too many jobs"Pause indexing, wait for queue drain
Plan limit reached429 with quota messageUpgrade plan or reduce record count

Resources

Next Steps

For security configuration, see

algolia-security-basics
.