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Official Proxy-Seller channel. Product updates, maintenance notices, new locations, offers, and short setup tips. Residential, mobile, ISP, IPv4 & IPv6 since 2014 · 185,000+ customers · 220+ locations Support 24/7: @ProxySellerio_bot proxy-seller.com
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Дописи каналу
⚠️ Our residential proxies now pass UDP and QUIC (HTTP/3) over SOCKS5.
It matters if part of your traffic never uses TCP:
▪️ WebRTC and VoIP calls you test from another country
▪️ video ad delivery, which often runs over QUIC
▪️ sites and APIs that serve HTTP/3
▪️ game-server latency checks from player regions
UDP leaves from the same IP as your TCP traffic, with the same credentials, on every residential list. IPv4, ISP, and mobile are still TCP-only.
👉 Browsers can't route UDP through a proxy, so use Clash, sing-box, v2rayN, Shadowrocket, or Proxifier with type socks5 and UDP on.
Read how to set up UDP and QUIC in our Help Center 👇
https://help.proxy-seller.com/en/articles/17704821-udp-and-quic-http-3-support-on-residential-proxies
| 2 | ⚠️ New guide: how to size a large-scale scraping fleet with actual math instead of guesswork.
Concurrency ≈ requests per second × average response time.
From there:
▪️ 1M pages a day becomes 1.15M attempts once retries are counted
▪️ 15.97 RPS over a 20-hour window
▪️ 44.7 in-flight requests, or 64 workers at 70% utilization
▪️ 400 to 800 IPs in the pool, or ~1,150 if the target caps you at 50 requests per IP per hour
▪️ 288 GB of egress a day at 250 KB per attempt
🔎 The workers fit on one small node, so the proxy pool almost always becomes the ceiling before CPU or memory.
Read the full guide, with the capacity table and Python code: https://proxy-seller.com/blog/large-scale-web-scraping-guide-to-concurrency-math-and-scaling/ | 728 |
| 3 |  ⚠️ New: shared access for mobile proxies, now live alongside dedicated pools.
▪️ Real 5G/4G/LTE carrier IPs on major global networks
▪️ 99.5% success rate
▪️ Scheduled IP rotation, with on-demand switching available on dedicated
▪️ HTTP, HTTPS, SOCKS5
▪️ The IP is assigned to several users rather than held for you
▪️ Traffic isn’t capped by us, carrier FUP applies
🔎 Take dedicated instead when you need predictable throughput under sustained load.
Compare both access types and configure yours: https://proxy-seller.com/mobile-proxies/ | 1 359 |
| 4 | /goto | 1 |
| 5 | ⚠️ Since August 26, Google routes search result links through /goto redirects, which can break your SERP pipeline even when your proxies work fine. That address can't be decoded locally, and HEAD requests are blocked, so each link needs a full GET.
In an existing pipeline, that can show up as:
1️⃣ broken URL extraction
2️⃣ normalization failures
3️⃣ parser errors
Of course, you can budget for a higher request volume along with more IPs, but rotating the IP won't fix a parser assumption, and you pay for the retry either way.
🔎 The solution is to classify every response as a network, redirect, parser, or downstream failure before it's stored, then fix the layer that broke.
Our full guide to scalable SERP collection covers the architecture, including the response classifier + code snippets: https://proxy-seller.com/blog/best-rank-tracking-api-how-to-build-scalable-serp-solutions/ | 1 694 |
| 6 | ⚠️ Your browser can show the proxy IP while UDP traffic takes a completely different route.
WebRTC and HTTP/3 both use UDP. Chrome doesn't use SOCKS5's UDP relay, so configuring SOCKS5 in the browser doesn't route UDP the same way.
Three possible outcomes:
🟢 TCP fallback through the proxy: direct UDP blocked, application uses TCP
🔴 Bypassed: UDP exposes the real source IP
🟡 Suppressed: UDP never reaches the destination
Number three is the trap. Disabling WebRTC prevents a leak, but it doesn't prove UDP is proxied, and a browser with zero ICE candidates stands out on its own.
🔎 On Chrome with SOCKS5: set WebRTCIPHandlingPolicy to disable_non_proxied_udp, then disable HTTP/3 and QUIC. You're choosing TCP fallback deliberately, which is the right call.
None of it helps if the proxy itself isn't reachable with the right credentials. Free Proxy-Check here: https://proxy-seller.com/tools/proxy-checker/ | 2 001 |
| 7 |  🤔 Picking a proxy type: the short version
Two mismatches we see most often:
1️⃣ Datacenter on a protected target. Uptime may be stable, but the response rate is plummeting. You add IPs, nothing changes.
2️⃣ Residential on a public API. It works, but costs several times more than it needs to.
There's also a third mismatch, and it's hard to catch: some targets don't error at all. They return rankings and prices for the server's location rather than the market you're tracking. Nothing will show up in the logs and the decision comes down to use case and geo precision.
💡Use our comparison table to save you a debugging session.
👉 Pick the type your target needs: https://proxy-seller.com/ | 976 |
| 8 | 🎥 New tutorial: building a web scraper that doesn’t get blocked and holds up at scale using AdsPower × Proxy-Seller.
Sites always check two layers: your browser fingerprint and your IP. If you only fix one, the other gives you away. Also, what really bites you at scale is if your profiles share an IP or even a subnet, they get correlated and banned as a batch. A unique fingerprint won't save you.
So, our solution is:
• AdsPower for a separate, isolated browser identity per profile
• Proxy-Seller for a separate, clean IP per profile (static ISP or rotating residential)
• AdsPower Local API to run it all from code (Python + Selenium)
We ran it live on books.toscrape.com (a practice sandbox), then scaled to several profiles in parallel, each on its own IP.
📹Watch here 👇
https://youtu.be/vSpcbzQAGJg?si=EhMsLNTLAeNHU3EF
🎁Bonus: scripts are in the description. | 992 |
| 9 | On September 15, Cloudflare changes how it treats AI bot traffic by default. Here's what it means for your scraping setup.
Starting September 15, new Cloudflare domains block AI bots in the Agent and Training categories by default on ad-supported pages. These categories cover AI crawlers, bots collecting data for model training, or acting as autonomous agents. If you're running AI training crawlers or AI agents, this is a real, direct change.
General scraping and automation tools aren't part of this classification.
If you're using residential or ISP proxies for scraping, price monitoring, or account automation, this specific rule likely doesn't apply to your traffic directly. Standard bot detection, the kind that already evaluates IP reputation and request patterns, isn't newly introduced by this update. It has been getting stricter gradually over the past year regardless of this deadline: wider reputation databases, more detailed traffic fingerprinting.
What's changing longer term: Cloudflare's new verification method, Web Bot Auth, lets bots sign requests with a private key instead of relying on a user-agent string. It's still an early standard; adoption is limited so far. AWS and Google are adopting the same approach.
🔎 What's worth focusing on now:
1. Focus on IP quality, not pool size. Clean Residential and ISP IPs remain the stronger foundation for reliable data collection.
2. Match realistic request timing and browser behavior. This affects block rates more than a signature would right now.
3. Test your workflows against Cloudflare-protected sites before scaling volume, especially if you're already seeing blocks or CAPTCHAs.
4. Keep an eye on Web Bot Auth adoption.
Cloudflare's update doesn't replace the need for proxies. It adds one more layer to how modern anti-bot systems work, and it's a good moment to check your setup.
👉 Get residential proxies here: https://proxy-seller.com/residential-proxies/ | 1 557 |
| 10 | Data stopped being just a fuel for AI, it became the limiting factor.
Teams don’t struggle with model design anymore. They struggle with what happens before training even starts: inconsistent sources, incomplete samples, and pipelines that quietly degrade under scale.
In practice, the failure point is unstable data flow:
- success rates drop without clear system errors
- regional gaps create biased training sets
- retries and blocked requests inflate compute cost
- large pipelines break down at session and network level
At scale, even small instability in data collection turns into measurable drift in model performance and cost.
This is why data infrastructure is now part of the ML stack, not just an ingestion layer, but a control system for consistency, coverage, and traceability.
In 2026, the teams that win aren’t those collecting the most data, but those keeping it reliable under real production load.
👉 Watch the full video on our channel | 1 695 |
| 11 |  Web Scraping in 2026: Choosing Proxies That Work in Production
Scraping issues today don’t come from blocks, but from degraded or inconsistent responses that still return “success”.
The real challenge is keeping data stable and usable at scale.
What matters in practice:
— residential proxies handle high-friction targets best;
— ISP proxies offer a balance of stability and performance;
— datacenter proxies work for fast, low-protection endpoints;
— mobile proxies are used when other types fail;
— session control matters more than pool size;
— failures often appear as partial or altered data, not errors.
In 2026, scraping is less about access and more about response consistency under load.
👉 Read the full guide on our blog | 1 458 |
| 12 | Many enterprise scraping systems continue to prioritize throughput over data validity.Currently, the primary failure point has shifted from blocked requests to degraded responses that still return “successful” status codes.
This video examines the evolution of proxy data consumption in 2026 and explains why extracting data at a gigabyte scale no longer ensures usable results.
Key topics covered include:
- Data quality is defined by response integrity, not volume.
- Even successful requests may return filtered or incomplete data.
- Proxy infrastructure now plays a role in data validation, not only in data transport.
- Session consistency directly affects long-term data reliability.
- System failures often manifest as gradual degradation rather than complete blocking.
- Observability is essential for detecting when “valid” responses are no longer accurate.
The core shift in 2026 is that enterprises are moving from large-scale data collection to ensuring data validity under changing conditions.
Watch the full video on our YouTube channel | 1 406 |
| 13 |  Modern scraping is less about choosing a tool and more about managing reliability, scale, and anti-bot resilience.
In the analysis of “Best Web Scraping Tools to Get Ahead in 2026”, we explore how scraping evolved from simple HTML parsing to full-scale systems combining APIs, browser automation, and proxy networks.
Key areas covered:
- no-code tools vs APIs vs developer frameworks
- role of proxies and session stability in scraping success
- handling JavaScript-heavy sites with browser automation
- scaling data extraction with cloud platforms and orchestration
- production challenges: bans, layout changes, and cost efficiency
The core shift in 2026 is: success depends more on infrastructure quality than extraction logic.
👉 Read the full article: Best Web Scraping Tools to Get Ahead in 2026 | 1 395 |
| 14 | Websites don’t block requests randomly. Access decisions are based on structured risk scoring that evaluates multiple traffic signals before interaction begins.
In this video, we break down how modern protection systems classify traffic and how risk evaluation works.
What you’ll see in practice:
– what risk scoring is and how it classifies traffic using measurable signals
– key factors: IP origin, request frequency, session consistency, device characteristics
– how risk systems aggregate signals and apply thresholds (rate limits, challenges, access control)
– main signal categories used in traffic evaluation systems
– how mitigation works in layers: friction, targeted restriction, broader controls
– why robots.txt does not enforce access and how enforcement is implemented
Modern systems combine multiple signals into a structured classification model that evolves over time and determines how traffic is handled.
👉 Watch the full video on our YouTube channel | 1 351 |
| 15 |  CloudScraper is often treated as a quick fix for Cloudflare-protected sites, but in practice its effectiveness depends on session handling, request patterns, and proxy quality.
This guide explains how CloudScraper works with Cloudflare checks and why proxy configuration directly affects automation stability.
Inside the article, we cover:
- how CloudScraper handles JavaScript challenges, headers, cookies, and redirects
- proxy integration in Python and common setup patterns
- limitations around CAPTCHAs, Turnstile, and unsupported challenges
- common issues like 403 errors, SSL failures, and redirect loops
- when it makes sense to switch to Playwright or Puppeteer
The focus is on building stable, maintainable scraping workflows with realistic expectations of what CloudScraper can and cannot do.
👉 Read the full guide: Beginner’s Guide – How to Use CloudScraper Proxy Effectively | 1 171 |
| 16 | Automation is rarely blocked instantly at scale. Modern websites observe behavior over time, scoring requests through accumulated signals rather than single-rule decisions.
This video explains how automation is detected in 2026 and why most systems degrade instead of failing outright.
What you’ll see in practice:
- automation is evaluated through probabilistic, behavior-based detection rather than simple blocking rules;
- systems shifted from IP blocking to risk scoring and gradual access degradation;
- browser-level entropy signals (canvas, WebGL, timing, device traits) form a high-impact detection layer;
- detection relies on accumulated behavioral consistency across sessions, not single requests;
- HTTP 200 responses can still return degraded or altered data without errors;
- observability is needed at request and behavior level to interpret detection outcomes.
Automation typically passes initial checks but loses reliability over time as small behavioral deviations accumulate. Systems keep running while data quality and trust gradually degrade.
👉 Watch the full video on our YouTube channel | 1 353 |
| 17 |  Most teams exploring IPRoyal alternatives already have proxy setups and working data or automation workflows.
This comparison outlines how providers differ in pricing, geo targeting, stability, compliance, and workload fit.
What the guide covers:
- what IPRoyal is and its main use cases (SEO, scraping, ads, multi-account setups)
- key selection factors: pricing, targeting depth, stability, compliance
- comparison of Proxy-Seller, Bright Data, SOAX, Smartproxy (Decodo), and Oxylabs
- differences between self-serve proxy providers and enterprise data platforms
- how to evaluate providers using real workload testing
The article focuses on how proxy providers differ in structure and suitability based on operational requirements and team scale.
👉 Read the full article: Top IPRoyal Alternatives in 2026 | 1 413 |
| 18 | Web scraping pipelines often fail not at execution, but at system level when moved from testing to production under real scale and protection mechanisms.
This video explains why scraping should be treated as a distributed system and how failures emerge across the full data pipeline.
What you’ll see in practice:
- web scraping operates as a distributed system with requests, retries, parsing, ingestion, and analytics stages;
- production environments introduce concurrency, rate limits, retries, and adaptive antibot systems;
- testing environments differ from production due to low load, predictable responses, and limited protection layers;
- scale exposes structural issues such as race conditions, retry amplification, CPU/memory contention, and extraction drift;
- HTTP 200 responses may still return invalid or incomplete data without triggering errors;
- observability typically starts after ingestion, creating blind spots in request-level monitoring.
At scale, scraping systems degrade through accumulated inconsistencies rather than failing through explicit errors or outages, leading to reduced data quality without system-level breakdowns.
👉 Watch the full video on our YouTube channel | 1 542 |
| 19 |  Proxy providers in 2026 are selected based on workload requirements, infrastructure compatibility, and operational stability.
This guide explains how proxy infrastructure is used across SEO, advertising, automation, and data collection, and what factors are considered when choosing a provider.
What the guide:
– what proxies are and how they function as an IP layer
– proxy types and their use cases (residential, mobile, ISP, datacenter, IPv4/IPv6)
– how proxies support SEO, ad verification, QA, and automation workflows
– selection criteria: IP quality, geo targeting, session control, protocols
– operational factors: uptime, session stability, response consistency
– pricing models and comparison approaches
– overview of providers by use case and scale
The article outlines how proxy infrastructure is aligned with specific business tasks and system requirements.
👉 Read the full article: Top Proxy Providers in 2026 | 1 526 |
| 20 | Production scraping problems are rarely caused by bugs.
They’re caused by architecture.
A scraper can pass tests, return stable responses, and run without errors — while the usefulness of the collected data steadily declines under real load.
In this video, we look at why scraping systems break down in production environments and why treating them as simple scripts leads to hidden data loss.
We discuss:
- how modern websites turn scraping into a distributed system problem;
- why scaling traffic reveals design assumptions that don’t hold;
- how anti-bot mechanisms affect response quality, not just availability;
- why successful requests can still produce unusable data;
- and why post-ingestion monitoring misses the real failure points.
🎥 Watch the full video on our YouTube channel | 1 509 |
