IPIPGO Dynamic IP Pool Technology: A Practical Solution for IP Blocking in AI Large Model Training

The Death Trap of AI Training Data Collection: the Truth About IP Block Rates 97%

When an AI company was training a big legal model, 182 IPs were blocked by Westlaw for 3 consecutive days, resulting in 300,000 pieces of critical data being scrapped. Traditional server room IP'sRegularity request feature(e.g. synchronized timestamps, fixed interval access) will be instantly recognized by the anti-crawling system. And with ipipgo's dynamic IP pool of residential IPs, each request comes from a real home network, which naturally has aHuman-operated randomness, which has been measured to reduce the blocking rate to below 3%.

Three Core Weapons of Dynamic IP Pooling

Five Steps to Build an Anti-Blocking Capture System

Step 1: Smart Route Configuration
Setting up the ipipgo consolegradient switching strategy::
- Automatic IP change for every 50 successful requests
- Immediate switching on encountering 403/429 error codes
- Reduced switching frequency from 2-6 a.m. (to simulate a real routine)

Step 2: Traffic anthropomorphic transformation
Enabled in the request header:
- Dynamically generated User-Agent (retaining the old browser version of 10%)
- Randomizing Accept-Language Parameters
- Add harmless cookies (via ipipgo'sCookie Pool Module(automatically acquired)

Step 3: Spatio-temporal decentralization strategy
Assign geographic IPs by target site characteristics:
- Academic paper site: prioritizing the use of European and American residential IPs
- Social media data: mixing dynamic IPs in Southeast Asia
- Open government data: targeting national static IPs
Available in the ipipgo backendgeofenceAutomatic matching of optimal IP zones

Step 4: Adaptive Rate Control
Do not use a fixed time interval, configuration is recommended:
- 120±30 seconds between requests during working hours (9-18 p.m.)
- Nighttime hours (0-8 p.m.) interval extended to 300 ± 60 seconds
- 20% random delay added all day on weekends

Step 5: Distributed Acquisition Architecture
Split the crawler node into:
- Reconnaissance node: detecting anti-crawl rules with ipipgo dynamic IP (taking up 10% resources)
- Primary node: static IPs continuously acquiring data (accounting for 60% resources)
- Backup node: dynamic IP to cope with unexpected blocking (30% resources)

A must-see guide for AI engineers to avoid the pitfalls

Q: Why do I still get blocked with a dynamic IP?
A: Check for three common mistakes:
1. Failure to clear browser fingerprints (with ipipgo)Fingerprint isolation system)
2. Abnormal IP geographic jumps (switching more than 3 countries in 1 hour)
3. Failure to simulate real user movement (sudden jumps from detail pages to deep catalogs)

Q: How do I handle CAPTCHA?
A: AdoptionHuman intervention strategies::
1. automatic switching of ipipgo residential IP when triggering CAPTCHA
2. Mark the IP to cool for 24 hours
3. Transfer the problem URL to a virtual environment with GUI for manual processing

Q: What should I do if the dynamic IP affects the collection speed?
A: Turn it on in the ipipgo backendHigh-speed channel mode::
- Automatic selection of quality IPs with latency <100ms
- Pre-established 20% backup connection pools
- Intelligent reuse of IPs that have not triggered an alarm (reused up to 3 times)

ipipgo's dedicated solution for AI training

We have provided dynamic IP solutions to 12 AI unicorns and our core strengths include:

1. Millions of IP reserves: 200,000+ new available residential IPs added daily, support filtering by ASN number
2. Intelligent Routing System: Automatically avoids IP segments that have been recently tagged by the target website.
3. Protocol masquerading techniques: Fake Crawler Traffic as Chrome Behavior

Apply NowAI Enterprise Exclusive PackageAvailability:
- Get a free copy of the Big Model Data Collection Compliance White Paper
- Customized IP Geographic Distribution Heat Map
- Priority access to enterprise-class API gateway (supports 300 concurrent calls per second)
Customers have already realized 30 consecutive days without blocking records, data collection efficiency increased by 17 times, the fastest 1 working day to complete the whole set of system deployment.