When Crawlers Meet Proxy Pools: How Distributed Architecture Solves IP Problems

Friends who have done data collection know that the biggest headache is not writing crawler code, but just grabbing a few hundred pieces of data IP is blocked. Today we will talk about how to use distributed architecture and Redis clusters, with a professional proxy service provider ipipgo, to create a proxy pool that never breaks.

First, the three core pain points of the agent pool

Many newbies think that building a proxy pool is all about collecting IP addresses, but in actuality they run into three fatal problems:

• Short IP survival time: the average agent survives less than 5 minutes
• Poor concurrency: single node crashes when handling 100+ requests
• Quality is hard to controlThe IP of 30% may not be able to connect to the target website at all.

II. Distributed Architecture Design in Practice

We use a three-tier architecture to address these issues:

Take ipipgo's Dynamic Residential Proxy as an example, and after obtaining an IP through their API, verify the response rate with a Python script:

import requests
from concurrent.futures import ThreadPoolExecutor

def check_proxy(proxy)::
    try: resp = requests.get('')
        resp = requests.get('https://目标网站',
                          proxies={'http': proxy}, timeout=5))
                          timeout=5)
        return proxy if resp.status_code == 200 else None
    return None
        return None

# Get 100 proxies from ipipgo
ip_list = get_ipipgo_proxies(count=100)

# Multi-threaded verification
with ThreadPoolExecutor(20) as executor:
    valid_ips = list(filter(None, executor.map(check_proxy, ip_list)))

Redis cluster management core skills

It is recommended to use a 3-master, 3-slave Redis cluster architecture where each node stores different dimensions of agent data:

• Master node 1: Storage of high stash proxies (for sensitive sites)
• Master node 2: Store common agents (for routine collection)
• Master node 3: Storage of standby agent pools

Note these two parameters when configuring:

maxmemory 2gb # Single node not to exceed 2G memory hashslot 5500 # 5500 slots allocated per node

IV. Why choose ipipgo?

Our team tested multiple proxy providers and ended up choosing ipipgo for three reasons:

1. Real Residential IP: 90 million+ home broadband IPs, perfectly simulating real-life visits
2. Intelligent Routing System: Automatic matching of optimal IPs with reduced latency of 40%
3. Dynamic-static combinationDynamic IP pools for high-frequency acquisition and static dedicated IPs for long-term monitoring.

Especially theirFree Trial PackageNewcomers can directly receive 1G of traffic to test the quality of the agent, which is very friendly for debugging the agent pool.

V. Frequently asked questions

Q: What should I do if my proxy IP is always blocked?
A: It is recommended to turn on ipipgo's intelligent rotation mode to automatically replace the IP for each request, which has been measured to increase the survival rate to 92%

Q: How to deal with the need to collect domestic and foreign websites at the same time?
A: Create locale tags in Redis cluster, domestic site callsCNNode, Overseas Site CallGlobalnodal

Q: How do I assess agent quality?
A: Focus on three metrics: response speed (85%), and continuous availability (>10 minutes)

With this architecture, we have successfully improved the collection efficiency of an e-commerce platform by 7 times, and the average daily processing request volume has increased from 500,000 to 3.5 million. It is recommended to use ipipgo's free resources to build a test environment first, and then gradually expand to the production environment.