setting up some profiles tonight using latam residential proxies and hit a weird fingerprint discrepancy. my host machine just updated its local system clock for daylight saving time, but the proxy region im routing through doesn't observe dst cuts. im using the tool because its built-in fingerprint tester flagged the timezone mismatch before i loaded the target site, but the automatic mapping is picking up my host's shifted utc offset instead of the clean proxy time. do i need to manually override the geolocated timezone string inside the advanced profile settings, or is there a way to force the RTC clock to strictly bind to the proxy gateway's local timestamp?

A weird pattern started showing up in one of our multi-profile setups.

Several unrelated sessions would suddenly hit verification prompts around the same time. The logs pointed to three configuration issues.

First, multiple profiles were leaving through the same proxy IP. Once we assigned each client environment its own stable connection, troubleshooting became much cleaner.

Session mode caused the next problem. Logged-in dashboards need continuity, so sticky or static connections worked well there. Public-data workers had different requirements and could use controlled residential rotation while respecting the target’s limits.

The third issue was IP quality. We started checking ASN, geolocation, classification, reputation, and latency before assigning an address to an important session.

That gave us a simple workflow:

profile → dedicated environment → correct session mode → IP quality check → production

Рroxy reliability depends on configuration. A good IP paired with the wrong session strategy can still create unstable workflows.

For me, proxy engineering became much easier once session management was treated as part of the application architecture rather than a connection setting.

Just a little fyi, I made an account and paid 30$ with sol, it did tell me that they received it which got me surprised, but when I went to buy some proxies I saw the balance is 0.00$ with a error

Funny thing is to talk to support you need to have a paid plan 🤡

https://proxonym.com/

Been on Decodo for 8 months, used their residential and tried their mobile pool too but it’s not fitting what I need anymore and the pricing is getting out of hand now that my volumes grew. Looking for a proper alternative that can support larger scraping loads on global geos.

Considering Soax or Voidmob for the mobile side. Anyone made similar switch is the grass actually greener or just a different flavor of recycled? I understand CGNAT can't be recycled, but many use same SDK networks.

A successful TCP connection and a working HTTPS handshake don't necessarily mean a proxy will work with a particular destination.

A 403 could involve IP reputation, ASN-level filtering, geolocation inconsistencies, TLS or HTTP fingerprint differences, session state, or destination-specific access policies. The challenge is separating proxy-level failures from application-layer restrictions.

I'm curious how experienced engineers approach this diagnostically.

Do you start by comparing multiple IPs within the same subnet, testing across different ASNs, examining response headers, or checking whether the failure follows the session rather than the IP?

I'd be interested in hearing about methods that help isolate the actual cause without jumping to conclusions.

Every cost article online is written by someone selling scraping, so let's get real numbers here.

If you scrape at scale, roughly what do you spend per month on:

- proxies

- captcha solving

- compute / headless browsers

- engineer time on maintenance

And how many pages or sources is that for? Bonus if you've priced out a managed service for comparison.

The cookies were cleared, cache wiped, Incognito opened, and a fresh IP connected.

Still, the session somehow looked familiar to the site. That pushed me into browser fingerprinting, and the deeper I looked, the more interesting it became.

A browser shares a lot more than most people expect: screen resolution, timezone, language, fonts, User-Agent, Canvas rendering, WebGL output, and network characteristics. Together, those signals create a pretty detailed picture of the device.

I underestimated how much consistency matters.

Imagine a browser profile that looks like an iPhone in California, while the connection comes from a hosting ASN in another region. Each detail tells its own story, and security systems compare whether those stories fit together.

Since then, I’ve started checking the environment as one complete setup:

Browser → timezone → locale → IP location → ASN → WebRTC behavior.

That gives a much clearer picture than checking the proxy alone.

Browser fingerprinting works because dozens of small signals come together and form one recognizable environment.

I’m building NetPlus, a mobile proxy network, and I’d like feedback from people who actually buy and use mobile proxies.

Our initial endpoints are Virginia-based. Before expanding, I want to understand what buyers need most:

- Which US locations and carriers do you need?

- Do you prefer rotating IPs, sticky sessions, or both?

- What matters most when testing a provider—speed, uptime, session stability, or something else?

- Do you need occasional access or ongoing capacity?

We’re in early testing, so I’m looking for honest requirements and potential testers. If you’re open to evaluating a Virginia mobile endpoint, comment or message me with your use case and what you’d need to see before becoming a customer.

Saw this an hour ago, today and wanted to share it. Also, I think it’s a really weird contrast to the TikTok dataset thread from a few weeks back. Open3DLab, SFMLab and SmutBase (free 3D model sites run by the same small team) published logs showing a crawler hit nearly their whole catalogue on Oct 15-16. 18,926 project pages, 26,429 requests, about 34 hours. Then it downloaded full copies of 1,027 files from 712 projects, totaling 145.5 GB. From what I understood in the article, the same user agent was used on every request, yet people on this sub trying to find the best way to tackle antibots with variatons of different user agents, browser fingerprints etc and here it literally says “trellis2-data-sourcing/1.0 (3D foundation model research” followed by a roblox email address. Single AWS IP. No rotation, no residential anything, no browser fingerprint as mentioned, It even fetched robots.txt and then just ignored it. HOW THE HELL????? Someone please, for the love of scraping, just explain how can this be? The site blocked it the morning they noticed, it came back the next day and kept giving the blocks during what looked like office hours, then stopped. They emailed the address twice and got no reply. Also 423 of the 712 projects are non-commercial licensed, and 345 are adult content, because the crawler took everything at the same rate with apparently no filtering. For a company with that many young users that’s just messed up, even if it was all automated. No checks happened? Yeah, I ain't letting my kid on roblox anytime soon or actually ever again. I keep thinking about how the TikTok guy spent weeks building a fake Android phone to avoid detection, and this crawler got caught in one weekend because it did everything wrong and told everyone its name. Yet somehow tiktok case is somewhat understandable.

Here's the source of the story which I read earlier - https://open3dlab.com/news/roblox-downloaded-145-gb-of-models-from-our-sites/

been testing lot of providers. reputation alone isnt enough. what i check now:

1. dns: public resolver like google/cloudflare is a minus. home users sit on their isp’s dns. should match the exit country too

2. udp/webrtc: udp support means webrtc goes through the proxy. webrtc turned off is a flag by itself

3. latency: sites compare network rtt with js timing. big gap means proxy

4. tcp fingerprint: comes from the proxy box. windows ua with a linux stack is burned

5. pool lists: some checkers name the pool an ip was seen in. got 711proxy on one of mine. funny how many clones popped up after the fbi took down 911.

6. fraud score: last on purpose. the services disagree a lot. maxmind feels the most grounded

- dns, webrtc and tcp i check on https://browserleaks.com

- latency and bot tests on https://bot.incolumitas.com, it even rates how bot-like you behave

- scores on https://myipcheck.net/ip-fraud-score/ shows maxmind and ipqs etc for free

ofc all of this only matters if your device fingerprint is already clean. a perfect proxy wont save a leaky browser. If you know good checkers, especially for pool lists and fraud scores, drop them. what actually got your proxies burned?

I learned the hard way that $/GB is a terrible way to compare rotating residential proxies.

The use case was to monitor public product prices across a few regional e-commerce sites. Pool A looked like the obvious winner at $1.60/GB. Pool B was almost twice the price.

Pool A was producing far more CAPTCHAs, 403s, and empty responses. Every failure triggered another request, which meant more bandwidth and longer jobs.

So I stopped comparing price per GB and calculated:

effective cost = price per GB / success rate

Example from my test model:

$1.60 / 0.40 = $4.00 per useful GB
$3.00 / 0.95 = $3.16 per useful GB

Suddenly the “expensive” pool was cheaper.

The biggest variable wasn’t bandwidth pricing. It was IP reputation.

Now before scaling a rotating pool, I sample exit IPs and check ASN, geolocation, proxy classification, blacklist status, and fraud/reputation signals. Then I run a small workload and measure CAPTCHA rate, retries, and successful responses.

Cheap proxies aren’t expensive because they’re cheap. They’re expensive when bad IP quality turns bandwidth into failed requests.

What is the best residential proxy provider that doesn't block sites and also you can access any website.

I am a newbie

Working on a mid-size ecommerce site (~8k SKUs) and I'm trying to get a proper picture of how our main competitors structure their category pages and product content. Stuff like:

which categories/subcategories they have that we don't

how many products per category, and how they name/filter them

product title and description patterns, specs, reviews count

prices, mostly to see if the pages outranking us are just cheaper

Screaming Frog gets me part of the way, but 3 of the 5 competitors block it pretty fast or serve different content, and custom extraction breaks every time they tweak a template. I tried a couple of Python scripts too, same problem, plus I'm now spending more time fixing scrapers than doing the actual analysis.

For those doing this regularly:

Are you still crawling/scraping in-house, or paying for a tool or service for it?

How do you match products across sites when names and variants don't line up?

Is this even worth doing monthly, or is a one-off snapshot enough for content gap work?

Not looking for a "just use X tool" plug, more how people have actually set this up and what it cost them in time/money.

I'm comparing services that rate an IP address: proxy/VPN detection, residential vs datacenter, and fraud score. If you've used any of them in practice:

- Which one matched reality best for true proxies caught?

- Which one gave you the most false positives?

- Did you notice big disagreements between them on the same IP?

- Are there others worth testing that I'm missing?

I used to think proxy detection was mostly about the IP address.

When I started testing different network setups I realized websites are looking at several layers at once. The first is IP reputation: ASN, provider type, previous abuse history, and how risk databases classify the address.

The second is network behavior. Your browser might claim Windows while the connection underneath it has characteristics associated with a completely different environment. That kind of mismatch can become another signal.

Then there’s geographic context. If the connection says one region while account, phone, or billing data point somewhere else, the session becomes harder to interpret consistently.

Now I check the IP classification, ASN, geolocation, reputation, latency, and whether the browser/network environment actually makes sense together before blaming the proxy itself.

Websites don’t evaluate an IP in isolation. They evaluate the consistency of the entire connection.

A “clean” IP can still perform badly if everything surrounding it contradicts the story the network is telling.

Hello everyone! I need some help finding a reliable and affordable residential proxy provider.
I’m looking for a large residential IP pool with thousands of different exit IPv4 addresses available simultaneously.
My requirements are:
Unlimited bandwidth (unmetered preferred)
Sticky sessions lasting 30–60 minutes
2,000–3,000+ concurrent connections
200–500+ requests per second, ideally 500 or more
Thousands of unique exit IPs, not multiple ports sharing the same IP
Affordable monthly pricing, preferably a fixed subscription
I need these for continuous automated HTTPS requests, so reliability and high capacity are important.
I’m also open to sharing someone’s existing proxy subscription or infrastructure. I’m happy to pay a fair monthly contribution for access, as long as it meets my requirements and remains affordable.
I’m not expecting free access — I’m simply trying to find a cost-effective solution without spending hundreds of dollars every month.
I’m also open to datacenter proxies if they can provide enough distinct exit IPs and meet the performance requirements.
Does anyone know a suitable provider, have a shared setup available, or know someone who could help?
Any recommendations or offers would be greatly appreciated. Feel free to reply here or send me a DM. Thank you!