intercom-performance-tuning

# Intercom Performance Tuning ## Overview Optimize Intercom API performance through response caching, efficient search queries, cursor-based pagination, connection pooling, and request batching. ## Prerequisites - `intercom-client` SDK installed - Understanding of Intercom data model - Redis or in-memory cache available (optional) ## Intercom API Latency Baselines | Operation | Typical P50 | Typical P95 | Notes | |-----------|-------------|-------------|-------| | `GET /me` (health check) | 50ms | 150ms | Lightest endpoint | | `GET /contacts/{id}` | 80ms | 200ms | Single lookup | | `POST /contacts/search` | 120ms | 400ms | Depends on query complexity | | `GET /conversations/{id}` | 100ms | 300ms | Heavier with parts (up to 500) | | `POST /contacts` (create) | 150ms | 400ms | Write operation | | `GET /contacts` (list) | 100ms | 350ms | Paginated, 50 per page | | `POST /messages` | 200ms | 500ms | Triggers delivery pipeline | ## Instructions ### Step 1: Response Caching Cache frequently accessed contacts and conversations to avoid repeated API calls. ```typescript import { LRUCache } from "lru-cache"; import { IntercomClient } from "intercom-client"; import { Intercom } from "intercom-client"; const contactCache = new LRUCache<string, Intercom.Contact>({ max: 5000, ttl: 5 * 60 * 1000, // 5 minutes }); const client = new IntercomClient({ token: process.env.INTERCOM_ACCESS_TOKEN!, }); async function getContact(contactId: string): Promise<Intercom.Contact> { ...