Skip to main content الرئيسية المنشئون comeonoliver skillshub brightdata-performance-tuning
brightdata-performance-tuning Optimize Bright Data API performance with caching, batching, and connection pooling.
Use when experiencing slow API responses, implementing caching strategies,
or optimizing request throughput for Bright Data integrations.
Trigger with phrases like "brightdata performance", "optimize brightdata",
"brightdata latency", "brightdata caching", "brightdata slow", "brightdata batch".
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/ComeOnOliver/skillshub --skill brightdata-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 Review product and feature risk before an AI coding agent starts implementation.
Use Xquik for X data and confirmation-gated X actions: tweet search, user lookup, follower export, media download, monitors, webhooks, MCP, and SDK workflows.
Canton Network open-source ecosystem guide covering DAML SDK, Canton runtime, and Splice applications. Use when working with Canton Network, DAML smart contracts, or building decentralized applications.
المهن ذات الصلة SOC
استنادا إلى تصنيف SOC المهني
name brightdata-performance-tuning description Optimize Bright Data API performance with caching, batching, and connection pooling.
Use when experiencing slow API responses, implementing caching strategies,
or optimizing request throughput for Bright Data integrations.
Trigger with phrases like "brightdata performance", "optimize brightdata",
"brightdata latency", "brightdata caching", "brightdata slow", "brightdata batch".
allowed-tools Read, Write, Edit version 1.0.0 license MIT author Jeremy Longshore <jeremy@intentsolutions.io> tags ["saas","scraping","data","brightdata"] compatible-with claude-code
Bright Data Performance Tuning
Overview
Optimize Bright Data scraping performance through connection pooling, response caching, concurrent request tuning, and smart product selection. Web Unlocker latency is typically 5-30s due to CAPTCHA solving; Scraping Browser sessions are 10-60s.
Prerequisites
Bright Data zone configured
Understanding of async patterns
Redis or file cache available (optional)
Latency Benchmarks
Product P50 P95 P99 Notes Web Unlocker (simple) 3s 8s 15s No CAPTCHA Web Unlocker (CAPTCHA) 10s 25s 45s With CAPTCHA solving Scraping Browser 8s 20s 40s Full browser render SERP API (sync) 2s 5s 10s Search results Residential Proxy 1s 3s 8s Raw proxy, no unblocking
Instructions
Step 1: Choose the Right Product
function selectProduct (target : { js: boolean ; captcha: boolean ; structured: boolean }if (target.structured ) return 'serp_api' ;
if (!target.js && !target.captcha ) return 'residential' ;
if (target.js ) return 'scraping_browser' ;
return
'web_unlocker'
Step 2: Connection Pooling with Keep-Alive import { Agent } from 'https' ;
import axios from 'axios' ;
const httpsAgent = new Agent ({
keepAlive : true ,
maxSockets : 25 ,
maxFreeSockets : 5 ,
timeout : 120000 ,
rejectUnauthorized : false ,
});
const client = axios.create ({
proxy : { host : 'brd.superproxy.io' , port : 33335 , auth : { username : proxyUser, password : proxyPass } },
httpsAgent,
timeout : 60000 ,
});
Step 3: Response Caching Layer
import { createHash } from 'crypto' ;
import { LRUCache } from 'lru-cache' ;
const memoryCache = new LRUCache <string , string >({
max : 500 ,
maxSize : 100_000_000 ,
sizeCalculation : (v ) => Buffer .byteLength (v),
ttl : 3600000 ,
});
export async function cachedScrape (
url : string ,
scraper : (url: string ) => Promise <string >,
ttlMs ?: number
): Promise <string > {
const key = createHash ('sha256' ).update (url).digest ('hex' );
const cached = memoryCache.get (key);
if (cached) {
console .log (`Cache HIT: ${url} ` );
return cached;
}
const html = await scraper (url);
memoryCache.set (key, html, { ttl : ttlMs });
console .log (`Cache MISS: ${url} (${Buffer.byteLength(html)} bytes)` );
return html;
}
Step 4: Concurrent Scraping with Backpressure import PQueue from 'p-queue' ;
const scrapeQueue = new PQueue ({
concurrency : 10 ,
interval : 1000 ,
intervalCap : 15 ,
});
async function scrapeMany (urls : string []Promise <Map <string , string >> {
const results = new Map <string , string >();
await Promise .allSettled (
urls.map (url =>add (async () => {
const html = await cachedScrape (url, (u ) => client.get (u).then (r =>data ));
results.set (url, html);
})
)
);
console .log (`Scraped ${results.size} /${urls.length} successfully` );
return results;
}
Step 5: Use Async API for Bulk Jobs For 100+ URLs, use the Web Scraper API instead of individual proxy requests:
async function bulkScrape (urls : string []const response = await fetch (
`https://api.brightdata.com/datasets/v3/trigger?dataset_id=${DATASET_ID} &format=json` ,
{
method : 'POST' ,
headers : {
'Authorization' : `Bearer ${process.env.BRIGHTDATA_API_TOKEN} ` ,
'Content-Type' : 'application/json' ,
},
body : JSON .stringify (urls.map (url =>return response.json ();
}
Step 6: Performance Monitoring class ScrapeMetrics {
private timings : number [] = [];
private errors = 0 ;
private cacheHits = 0 ;
record (durationMs : number this .timings .push (durationMs); }
recordError (this .errors ++; }
recordCacheHit (this .cacheHits ++; }
report (const sorted = [...this .timings ].sort ((a, b ) => a - b);
return {
count : sorted.length ,
errors : this .errors ,
cacheHits : this .cacheHits ,
p50 : sorted[Math .floor (sorted.length * 0.5 )] || 0 ,
p95 : sorted[Math .floor (sorted.length * 0.95 )] || 0 ,
p99 : sorted[Math .floor (sorted.length * 0.99 )] || 0 ,
};
}
}
Output
Right product selection per use case
Connection pooling reducing TCP overhead
Response cache avoiding duplicate scrapes
Concurrent scraping with backpressure control
Bulk API for large-scale jobs
Error Handling Issue Cause Solution Slow scrapes CAPTCHA solving overhead Expected for Web Unlocker; use cache Connection exhausted Too many concurrent Reduce p-queue concurrency Memory pressure Large cached pages Set maxSize on LRU cache Timeout storms All requests hitting slow site Add circuit breaker
Resources
Next Steps For cost optimization, see brightdata-cost-tuning.
