Algolia Cost Tuning
SkillSearchHelps your agent analyze and reduce Algolia search costs by understanding request and record pricing.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Algolia Cost Tuning skill
About this capability
Audit Algolia usage drivers and propose measurable cost controls without hard-coded plan prices. Use when search spend, request volume, record count, replicas, or optional features need investigation. Trigger with "Algolia cost audit", "reduce Algolia usage", or "Algolia bill".
What this skill tells your AI
The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/algolia-cost-tuning/SKILL.md and read by ahel’s review.
Overview
Algolia pricing is based on search requests and records. A search request is one API call (which may contain multiple queries via search({ requests: [...] })). Records are counted across all indices including replicas.
Prerequisites
- Access to current Algolia usage, billing, and index statistics for the application being reviewed.
- An Admin or monitoring credential used only from a trusted backend environment.
- A reporting window that distinguishes production traffic from load tests and bots.
Pricing Structure (2025)
| Plan | Records Included | Search Requests | Additional Cost |
|---|---|---|---|
| Build (Free) | 1M records | 10K requests/mo | N/A |
| Grow | 100K free, then $0.40/1K | 10K free, then $0.50/1K | Pay as you go |
| Grow Plus | 100K free, then $0.40/1K | 10K free, then $1.75/1K | + AI features |
| Premium | Custom | Custom | Volume discounts |
What Counts as Records
- Every object in every index = 1 record
- Standard replicas duplicate records (multiply your count)
- Virtual replicas share records (no extra cost)
- Synonyms and rules do NOT count as records
What Counts as Search Requests
searchSingleIndex()= 1 requestsearch({ requests: [q1, q2, q3] })= 1 request (multi-query)browse()= 1 request per pagesaveObjects()= NOT a search request (indexing operations are free)
Instructions
Examples
The audit and analytics calls below show how to measure records, requests, and no-result searches before changing replicas, caching, or query design. Measure a baseline first so savings claims are testable.
Step 1: Audit Current Usage
import { algoliasearch } from 'algoliasearch';
const client = algoliasearch(process.env.ALGOLIA_APP_ID!, process.env.ALGOLIA_ADMIN_KEY!);
// Check total records across all indices
const { items } = await client.listIndices();
let totalRecords = 0;
let replicaRecords = 0;
items.forEach(idx => {
const records = idx.entries || 0;
console.log(`${idx.name}: ${records.toLocaleString()} records, ${(idx.dataSize || 0 / 1024).toFixed(0)}KB`);
if (idx.name.includes('_replica') || idx.primary) {
replicaRecords += records;
}
totalRecords += records;
});
console.log(`\nTotal: ${totalRecords.toLocaleString()} records (${replicaRecords.toLocaleString()} in replicas)`);
Step 2: Replace Standard Replicas with Virtual Replicas
// Standard replicas: duplicate all records (doubles cost)
// Virtual replicas: share records with primary (no extra cost)
// BEFORE: 3 standard replicas = 4x record count
await client.setSettings({
indexName: 'products',
indexSettings: {
replicas: [
// 'products_price_asc', // Standard: costs records
// 'products_price_desc', // Standard: costs records
'virtual(products_price_asc)', // Virtual: FREE
'virtual(products_price_desc)', // Virtual: FREE
],
},
});
// Virtual replica limitation: can only customize ranking and customRanking
// If you need different searchableAttributes or attributesForFaceting, use standard
Step 3: Use Multi-Query to Reduce Request Count
// BAD: 3 separate requests = 3 search operations billed
const results1 = await client.searchSingleIndex({ indexName: 'products', searchParams: { query: 'laptop' } });
const results2 = await client.searchSingleIndex({ indexName: 'articles', searchParams: { query: 'laptop' } });
const results3 = await client.searchSingleIndex({ indexName: 'faq', searchParams: { query: 'laptop' } });
// GOOD: 1 multi-query request = 1 search operation billed
const { results } = await client.search({
requests: [
{ indexName: 'products', query: 'laptop', hitsPerPage: 5 },
{ indexName: 'articles', query: 'laptop', hitsPerPage: 3 },
{ indexName: 'faq', query: 'laptop', hitsPerPage: 3 },
],
});
Step 4: Cache Frequent Searches
import { LRUCache } from 'lru-cache';
// Cache popular searches — Algolia's own CDN caches are limited
const searchCache = new LRUCache<string, any>({
max: 1000,
ttl: 5 * 60 * 1000, // 5 minutes for product search
});
async function cachedSearch(query: string, filters?: string) {
const key = JSON.stringify({ query, filters });
const cached = searchCache.get(key);
if (cached) {
console.log('Cache hit — saved 1 search request');
return cached;
}
const result = await client.searchSingleIndex({
indexName: 'products',
searchParams: { query, filters },
});
searchCache.set(key, result);
return result;
}
Step 5: Delete Unused Indices
// Audit and clean up test/development indices
const { items } = await client.listIndices();
const devIndices = items.filter(i =>
i.name.startsWith('test_') ||
i.name.startsWith('dev_') ||
i.name.startsWith('ci_')
);
for (const idx of devIndices) {
console.log(`Deleting unused index: ${idx.name} (${idx.entries} records)`);
await client.deleteIndex({ indexName: idx.name });
}
Step 6: Monitor Usage with Analytics API
// Track search volume trends
const { count: searchCount } = await client.getSearchesCount({
index: 'products',
startDate: '2025-01-01',
endDate: '2025-01-31',
});
console.log(`Search requests this month: ${searchCount.toLocaleString()}`);
// Identify no-result queries (wasted searches users will retry)
const { searches } = await client.getSearchesNoResults({
index: 'products',
startDate: '2025-01-01',
endDate: '2025-01-31',
});
console.log('Top no-result searches (fix these to reduce retries):');
searches.slice(0, 10).forEach(s => console.log(` "${s.search}" — ${s.count} times`));
Cost Reduction Summary
| Strategy | Savings | Effort |
|---|---|---|
| Virtual replicas | 50-75% record cost | Low |
| Multi-query search | 60-80% fewer requests | Low |
| Client-side caching | 30-50% fewer requests | Low |
| Delete unused indices | Variable | Low |
| Fix no-result queries (synonyms) | 10-20% fewer retries | Medium |
| Reduce record size | Indirect (faster = cheaper) | Medium |
Output
The review identifies the record and request drivers of the current bill, produces a prioritized reduction plan, and gives measurable before/after signals for each change. It does not alter billing settings by itself.
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Unexpected bill spike | Uncached bot traffic | Add rate limiting, cache layer |
| Record count higher than expected | Standard replicas | Switch to virtual replicas |
| Search requests over budget | No caching | Add LRU cache in API layer |
| Analytics API returns empty | Wrong date range or region | Check region parameter matches your app |
Resources
Next Steps
For architecture patterns, see algolia-reference-architecture.
Signals
- GitHub stars
- 3k
- Forks
- 396
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
algolia-cost-tuning- Source
- github.com/jeremylongshore/tons-of-skills-marketplace