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maintainx-performance-tuning Optimize MaintainX API integration performance.
Use when experiencing slow API responses, optimizing data fetching,
or improving integration throughput with MaintainX.
Trigger with phrases like "maintainx performance", "maintainx slow",
"optimize maintainx", "maintainx caching", "maintainx faster".
الانتقال إلى التثبيت سوق المهارات اكتشف واستكشف مهارات الذكاء الاصطناعي التي بناها المجتمع.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
عرض تفاصيل Prompt يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill maintainx-performance-tuningيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
تحميل Zip جاري التحميل... المزيد من هذا المستودع Implement user sign-up and sign-in flows with Clerk.
Use when building authentication UI, customizing sign-in experience,
or implementing OAuth social login.
Trigger with phrases like "clerk sign-in", "clerk sign-up",
"clerk login flow", "clerk OAuth", "clerk social login".
Implement session management and middleware with Clerk.
Use when managing user sessions, configuring route protection,
or implementing token refresh and custom JWT templates.
Trigger with phrases like "clerk session", "clerk middleware",
"clerk route protection", "clerk token", "clerk JWT".
Configure enterprise SSO, role-based access control, and organization management.
Use when implementing SSO integration, configuring role-based permissions,
or setting up organization-level controls.
Trigger with phrases like "clerk SSO", "clerk RBAC",
"clerk enterprise", "clerk roles", "clerk permissions", "clerk organizations".
المهن ذات الصلة SOC
استنادا إلى تصنيف SOC المهني
name maintainx-performance-tuning description Optimize MaintainX API integration performance.
Use when experiencing slow API responses, optimizing data fetching,
or improving integration throughput with MaintainX.
Trigger with phrases like "maintainx performance", "maintainx slow",
"optimize maintainx", "maintainx caching", "maintainx faster".
allowed-tools Read, Write, Edit, Bash(npm:*) version 1.11.0 license MIT author Jeremy Longshore <jeremy@intentsolutions.io> tags ["saas","maintainx","api","performance"] compatibility Designed for Claude Code, also compatible with Codex and OpenClaw
MaintainX Performance Tuning
Overview
Optimize MaintainX integration performance with caching, connection pooling, efficient pagination, and request deduplication.
Prerequisites
MaintainX integration working
Node.js 18+
Redis (recommended for production caching)
Performance baseline measurements
Instructions
Step 1: Connection Pooling with Keep-Alive
import axios from 'axios' ;
import http from 'node:http' ;
import https from 'node:https' ;
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 ${process.env.MAINTAINX_API_KEY} ` ,
'Content-Type' : 'application/json' ,
},
httpAgent,
httpsAgent,
timeout : 30_000 ,
});
Step 2: Multi-Level Caching
interface CacheLayer <T> {
get (key : string ): Promise <T | undefined >;
set (key : string , value : T, ttlMs : number ): Promise <void >;
}
class MemoryCache <T> implements CacheLayer <T> {
private store = new Map <string , { value : T; expiresAt : number }>();
async get (key : string const entry = this .store .get (key);
if (entry && entry.expiresAt > Date .now ()) return entry.value ;
this .store .delete (key);
return undefined ;
}
async set (key : string , value : T, ttlMs : number this .store .set (key, { value, expiresAt : Date .now () + ttlMs });
}
}
class RedisCache <T> implements CacheLayer <T> {
constructor (private redis : any async get (key : string const data = await this .redis .get (`mx:${key} ` );
return data ? JSON .parse (data) : undefined ;
}
async set (key : string , value : T, ttlMs : number await this .redis .setex (`mx:${key} ` , Math .ceil (ttlMs / 1000 ), JSON .stringify (value));
}
}
class MultiCache <T> {
constructor (private l1 : CacheLayer <T>, private l2 : CacheLayer <T>async getOrFetch (key : string , ttlMs : number , fetcher : () => Promise <T>): Promise <T> {
let value = await this .l1 .get (key);
if (value !== undefined ) return value;
value = await this .l2 .get (key);
if (value !== undefined ) {
await this .l1 .set (key, value, ttlMs / 2 );
return value;
}
value = await fetcher ();
await this .l1 .set (key, value, ttlMs / 2 );
await this .l2 .set (key, value, ttlMs);
return value;
}
}
Step 3: DataLoader for Batch Loading When multiple parts of your app need the same work order, batch and deduplicate:
import DataLoader from 'dataloader' ;
const workOrderLoader = new DataLoader <number , any >(
async (ids : readonly number []) => {
const results = await Promise .all (
ids.map ((id ) =>
client.get (`/workorders/${id} ` ).then ((r ) => r.data )
),
);
return ids.map ((id ) => results.find ((r ) => r.id === id) || null );
},
{
maxBatchSize : 25 ,
cacheKeyFn : (id ) => String (id),
},
);
const [wo1, wo2, wo3] = await Promise .all ([
workOrderLoader.load (100 ),
workOrderLoader.load (200 ),
workOrderLoader.load (100 ),
]);
Step 4: Efficient Pagination
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 },
});
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;
}
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 };
}
Step 5: Request Deduplication
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 ();
async function getWorkOrder (id : number return dedup.dedupe (`wo:${id} ` , () => client.get (`/workorders/${id} ` ));
}
Performance Benchmarks 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
Output
Connection pooling with keep-alive (reuses TCP connections)
Multi-level cache (L1 in-memory + L2 Redis)
DataLoader for batching and deduplication of entity fetches
Efficient pagination with max page sizes
Request deduplication preventing redundant concurrent calls
Error Handling 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
Resources
Next Steps For cost optimization, see maintainx-cost-tuning.
Examples Benchmark your API response times :
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
