openrouter-compliance-review
Review OpenRouter integration for regulatory compliance (SOC2, GDPR,
maintainx-performance-tuning
Optimize MaintainX API integration performance.
Full skill instructions
Optimize MaintainX integration performance with caching, connection pooling, efficient pagination, and request deduplication.
// src/performance/pooled-client.ts
import axios from 'axios';
import http from 'node:http';
import https from 'node:https';
// Reuse TCP connections instead of opening new ones per request
const httpAgent = new http.Agent({ keepAlive: true, maxSockets: 10 });
const httpsAgent = new https.Agent({ keepAlive: true, maxSockets: 10 });
const client = axios.create({
baseURL: 'https://api.getmaintainx.com/v1',
headers: {
Authorization: `Bearer ${process.env.MAINTAINX_API_KEY}`,
'Content-Type': 'application/json',
},
httpAgent,
httpsAgent,
timeout: 30_000,
});
// Benefit: Eliminates TCP handshake + TLS negotiation per request
// Typical improvement: 100-200ms saved per request
// src/performance/cache.ts
interface CacheLayer<T> {
get(key: string): Promise<T | undefined>;
set(key: string, value: T, ttlMs: number): Promise<void>;
}
// L1: In-memory (fastest, per-process)
class MemoryCache<T> implements CacheLayer<T> {
private store = new Map<string, { value: T; expiresAt: number }>();
async get(key: string) {
const entry = this.store.get(key);
if (entry && entry.expiresAt > Date.now()) return entry.value;
this.store.delete(key);
return undefined;
}
async set(key: string, value: T, ttlMs: number) {
this.store.set(key, { value, expiresAt: Date.now() + ttlMs });
}
}
// L2: Redis (shared across processes)
class RedisCache<T> implements CacheLayer<T> {
constructor(private redis: any) {}
async get(key: string) {
const data = await this.redis.get(`mx:${key}`);
return data ? JSON.parse(data) : undefined;
}
async set(key: string, value: T, ttlMs: number) {
await this.redis.setex(`mx:${key}`, Math.ceil(ttlMs / 1000), JSON.stringify(value));
}
}
// Multi-level cache: check L1 first, then L2, then fetch
class MultiCache<T> {
constructor(private l1: CacheLayer<T>, private l2: CacheLayer<T>) {}
async getOrFetch(key: string, ttlMs: number, fetcher: () => Promise<T>): Promise<T> {
// Check L1
let value = await this.l1.get(key);
if (value !== undefined) return value;
// Check L2
value = await this.l2.get(key);
if (value !== undefined) {
await this.l1.set(key, value, ttlMs / 2); // L1 shorter TTL
return value;
}
// Fetch from API
value = await fetcher();
await this.l1.set(key, value, ttlMs / 2);
await this.l2.set(key, value, ttlMs);
return value;
}
}
When multiple parts of your app need the same work order, batch and deduplicate:
// src/performance/dataloader.ts
import DataLoader from 'dataloader';
const workOrderLoader = new DataLoader<number, any>(
async (ids: readonly number[]) => {
// Batch: fetch multiple work orders in parallel
const results = await Promise.all(
ids.map((id) =>
client.get(`/workorders/${id}`).then((r) => r.data)
),
);
// Return in same order as input ids
return ids.map((id) => results.find((r) => r.id === id) || null);
},
{
maxBatchSize: 25,
cacheKeyFn: (id) => String(id),
},
);
// These 3 calls collapse into 1 batched operation:
const [wo1, wo2, wo3] = await Promise.all([
workOrderLoader.load(100),
workOrderLoader.load(200),
workOrderLoader.load(100), // deduped, same as first
]);
// Fetch only the fields you need (if API supports field selection)
// Use larger page sizes to reduce round trips
async function efficientFetchAll(client: any, endpoint: string, key: string) {
const all = [];
let cursor: string | undefined;
let pageCount = 0;
const startTime = Date.now();
do {
const { data } = await client.get(endpoint, {
params: { limit: 100, cursor }, // Max page size
});
all.push(...data[key]);
cursor = data.cursor;
pageCount++;
} while (cursor);
const elapsed = Date.now() - startTime;
console.log(`Fetched ${all.length} items in ${pageCount} pages (${elapsed}ms)`);
return all;
}
// Parallel pagination for independent resources
async function fetchAllResources(client: any) {
const [workOrders, assets, locations] = await Promise.all([
efficientFetchAll(client, '/workorders', 'workOrders'),
efficientFetchAll(client, '/assets', 'assets'),
efficientFetchAll(client, '/locations', 'locations'),
]);
return { workOrders, assets, locations };
}
// src/performance/dedup.ts
class RequestDeduplicator {
private inflight = new Map<string, Promise<any>>();
async dedupe<T>(key: string, fetcher: () => Promise<T>): Promise<T> {
if (this.inflight.has(key)) {
return this.inflight.get(key)! as Promise<T>;
}
const promise = fetcher().finally(() => {
this.inflight.delete(key);
});
this.inflight.set(key, promise);
return promise;
}
}
const dedup = new RequestDeduplicator();
// 10 concurrent calls to getWorkOrder(123) = 1 actual API call
async function getWorkOrder(id: number) {
return dedup.dedupe(`wo:${id}`, () => client.get(`/workorders/${id}`));
}
| Optimization | Before | After | Improvement |
|---|---|---|---|
| Connection pooling | 350ms/req | 150ms/req | 57% faster |
| L1 cache (hot path) | 150ms/req | < 1ms/req | 99% faster |
| DataLoader batching | 10 calls | 1 call | 90% fewer requests |
| Max page size (100) | 50 pages | 10 pages | 5x fewer round trips |
| Request dedup | N calls | 1 call | (N-1) saved |
| Issue | Cause | Solution |
|---|---|---|
| Stale cache data | TTL too long | Reduce TTL, invalidate on writes |
| Memory growth | Unbounded cache | Set max size, use LRU eviction |
| DataLoader errors | One item in batch fails | Handle per-item errors in batch function |
| Connection pool exhaustion | Too many concurrent requests | Increase maxSockets or add queue |
For cost optimization, see maintainx-cost-tuning.
Benchmark your API response times:
# Measure latency for 10 sequential requests
for i in $(seq 1 10); do
curl -s -o /dev/null -w "Request $i: %{time_total}s\n" \
"https://api.getmaintainx.com/v1/workorders?limit=1" \
-H "Authorization: Bearer $MAINTAINX_API_KEY"
done
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