'Optimize Attio API performance -- caching, batch queries, pagination
Scanned 9/2/2026
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---
name: attio-performance-tuning
description: 'Optimize Attio API performance -- caching, batch queries, pagination
strategies, connection pooling, and latency reduction.
Trigger: "attio performance", "optimize attio", "attio slow",
"attio latency", "attio caching", "attio batch requests".
'
allowed-tools: Read, Write, Edit
version: 1.7.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- crm
- attio
compatibility: Designed for Claude Code
---
# Attio Performance Tuning
## Overview
Attio's REST API returns JSON over HTTPS. Performance optimization focuses on reducing request count (batching, caching), maximizing throughput (connection reuse, pagination), and minimizing latency (selective field fetching, parallel queries).
## Key Performance Facts
| Factor | Detail |
|--------|--------|
| Rate limit | Sliding 10-second window, shared across all tokens |
| Pagination default | `limit: 500` (max per page) |
| API base | `https://api.attio.com/v2` |
| Auth overhead | Bearer token in header (minimal) |
| Response format | JSON only (no binary/protobuf) |
## Instructions
### Strategy 1: Response Caching with LRU
Cache read-heavy data (object schemas, attribute definitions) that rarely change:
```typescript
import { LRUCache } from "lru-cache";
const cache = new LRUCache<string, unknown>({
max: 500, // Max entries
ttl: 5 * 60 * 1000, // 5 minutes for schema data
});
async function cachedGet<T>(
client: AttioClient,
path: string,
ttlMs?: number
): Promise<T> {
const cached = cache.get(path) as T | undefined;
if (cached) return cached;
const result = await client.get<T>(path);
cache.set(path, result, { ttl: ttlMs });
return result;
}
// Schema data: cache for 30 minutes (rarely changes)
const objects = await cachedGet(client, "/objects", 30 * 60 * 1000);
const attrs = await cachedGet(client, "/objects/people/attributes", 30 * 60 * 1000);
// Record data: cache for 1-5 minutes (changes more often)
const person = await cachedGet(client, `/objects/people/records/${id}`, 60 * 1000);
```
### Strategy 2: Batch Queries Instead of N+1
```typescript
// BAD: N+1 pattern -- one request per email lookup
const people = [];
for (const email of customerEmails) {
const res = await client.post("/objects/people/records/query", {
filter: { email_addresses: email },
limit: 1,
});
people.push(res.data[0]);
}
// Cost: N requests
// GOOD: Single query with $in operator
const allPeople = await client.post<{ data: AttioRecord[] }>(
"/objects/people/records/query",
{
filter: {
email_addresses: {
email_address: { $in: customerEmails },
},
},
limit: customerEmails.length,
}
);
// Cost: 1 request
```
### Strategy 3: Parallel Independent Queries
```typescript
// Fetch multiple object types in parallel
const [people, companies, deals] = await Promise.all([
client.post<{ data: AttioRecord[] }>(
"/objects/people/records/query",
{ limit: 100 }
),
client.post<{ data: AttioRecord[] }>(
"/objects/companies/records/query",
{ limit: 100 }
),
client.post<{ data: AttioRecord[] }>(
"/objects/deals/records/query",
{ limit: 100 }
),
]);
```
### Strategy 4: Efficient Pagination
```typescript
// Use maximum page size (500) to minimize round trips
async function fetchAllRecords(
client: AttioClient,
objectSlug: string,
filter?: Record<string, unknown>
): Promise<AttioRecord[]> {
const PAGE_SIZE = 500; // Attio's maximum
const allRecords: AttioRecord[] = [];
let offset = 0;
while (true) {
const page = await client.post<{ data: AttioRecord[] }>(
`/objects/${objectSlug}/records/query`,
{
...(filter ? { filter } : {}),
limit: PAGE_SIZE,
offset,
}
);
allRecords.push(...page.data);
// If we got fewer than PAGE_SIZE, we've reached the end
if (page.data.length < PAGE_SIZE) break;
offset += PAGE_SIZE;
}
return allRecords;
}
```
### Strategy 5: Streaming Pagination with AsyncGenerator
For processing large datasets without loading everything into memory:
```typescript
async function* streamRecords(
client: AttioClient,
objectSlug: string,
filter?: Record<string, unknown>
): AsyncGenerator<AttioRecord> {
const PAGE_SIZE = 500;
let offset = 0;
let hasMore = true;
while (hasMore) {
const page = await client.post<{ data: AttioRecord[] }>(
`/objects/${objectSlug}/records/query`,
{ ...(filter ? { filter } : {}), limit: PAGE_SIZE, offset }
);
for (const record of page.data) {
yield record;
}
hasMore = page.data.length === PAGE_SIZE;
offset += PAGE_SIZE;
}
}
// Process without loading all records into memory
let count = 0;
for await (const record of streamRecords(client, "people")) {
await processRecord(record);
count++;
}
console.log(`Processed ${count} records`);
```
### Strategy 6: Connection Keep-Alive
```typescript
import { Agent } from "https";
// Reuse TCP connections across requests
const keepAliveAgent = new Agent({
keepAlive: true,
maxSockets: 10,
maxFreeSockets: 5,
timeout: 30_000,
});
// Use with node-fetch or undici
import { fetch as undiciFetch, Agent as UndiciAgent } from "undici";
const dispatcher = new UndiciAgent({
keepAliveTimeout: 30_000,
keepAliveMaxTimeout: 60_000,
connections: 10,
});
const res = await undiciFetch("https://api.attio.com/v2/objects", {
headers: { Authorization: `Bearer ${process.env.ATTIO_API_KEY}` },
dispatcher,
});
```
### Strategy 7: Webhook-Driven Cache Invalidation
Instead of polling for changes, use webhooks to invalidate cached data:
```typescript
const recordCache = new LRUCache<string, AttioRecord>({ max: 5000, ttl: 300_000 });
// On webhook event
async function handleCacheInvalidation(event: AttioWebhookEvent): Promise<void> {
switch (event.event_type) {
case "record.updated":
case "record.deleted":
case "record.merged":
recordCache.delete(event.record?.id?.record_id || "");
break;
}
}
```
### Strategy 8: Request Timing and Monitoring
```typescript
async function timedRequest<T>(
name: string,
operation: () => Promise<T>
): Promise<T> {
const start = performance.now();
try {
const result = await operation();
const duration = performance.now() - start;
console.log(JSON.stringify({
metric: "attio_api_duration_ms",
operation: name,
duration: Math.round(duration),
status: "success",
}));
return result;
} catch (err) {
const duration = performance.now() - start;
console.error(JSON.stringify({
metric: "attio_api_duration_ms",
operation: name,
duration: Math.round(duration),
status: "error",
error: (err as Error).message,
}));
throw err;
}
}
// Usage
const people = await timedRequest("query_people", () =>
client.post("/objects/people/records/query", { limit: 100 })
);
```
## Prerequisites
Confirm that you have an Attio workspace appropriate to the task, a dedicated non-production record or workspace for testing, and only the API token scopes or administrative access required by the procedure.
## Output
Following this guide produces the Attio integration outcome for its topic—configuration, validation evidence, operational recovery, or a documented migration result. Record command output and relevant identifiers so a failed step is traceable.
## Examples
Start with the smallest applicable command or code example in the relevant section, using a dedicated test record or workspace and non-production credentials. Confirm the expected response or validation result before applying the pattern to production.
## Error Handling
| Performance issue | Symptom | Solution |
|------------------|---------|----------|
| N+1 queries | Slow bulk operations | Use `$in` filter in single query |
| Cache miss storm | Burst of identical requests | Use stale-while-revalidate or mutex |
| Memory pressure | Large dataset pagination | Use AsyncGenerator streaming |
| Connection overhead | High latency per request | Enable keep-alive agent |
| Stale cached data | Showing outdated records | Add webhook-driven invalidation |
## Resources
- [Attio Pagination Guide](https://docs.attio.com/rest-api/guides/pagination)
- Attio Filtering and Sorting
- [Attio Rate Limiting](https://docs.attio.com/rest-api/guides/rate-limiting)
- [LRU Cache Documentation](https://github.com/isaacs/node-lru-cache)
## Next Steps
For cost optimization, see `attio-cost-tuning`.
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