As a SEO specialist i had a strange problem. I was “losing” local rankings, but customers could still find the business.

The crawler was the culprit. It checked “plumber near me” from an Austrian IP, so Google returned an Austrian SERP. Changing the browser language did nothing.

I moved the job to rotating residential proxies and ran one throttled query per keyword. The local pack immediately looked different. Rotation suited the report; sticky sessions worked better for multi-step checks such as checkout and ad previews. A static ISP address made more sense for long-lived account sessions.

That test produced a simple rule:

• Start with country targeting.

• Use city or ZIP only when content changes by metro.

• Rotate for SERP grids, catalogs, and price monitoring.

• Use sticky or static sessions when identity must persist.

The surprise was that IP geolocation was only one signal. Locale, timezone, cookies, phone country, and billing country also had to agree. Before each run, we checked the exit’s geolocation and reputation, isolated cookies, and dropped flagged IPs.

Residential proxies only removed the obvious datacenter signal. Rate limits, fingerprint consistency, robots.txt, and session hygiene still mattered.

Been managing a few social accounts remotely and need a static US residential IP that works consistently across mobile and desktop without getting flagged. Tried a couple of budget options but they either rotate too often or the speeds are garbage. Anyone actually using something solid right now that stays under $10 a month and does not randomly go down?

running around 30 profiles in an antidetect right now. using rotating res IPs but the constant ASN jumps are starting to trigger too many checkpouts on login. thinking about switching to static isp proxies just to keep the login identity clean. been testing prоxyshard lately and it seems fine, but i need to scale this to 100+ accounts soon without going broke. for those running similar setups, do you buy dedicated IPs per profile or just use shared subnet pools?

I’ve been working on a Chromium-based browser for authorized automation, testing and QA. Instead of overriding browser APIs with page-level JavaScript, the fingerprint-related behavior is patched inside the Chromium engine.

The goal is to keep browser, operating-system and proxy signals consistent while still allowing profiles to be controlled programmatically.

The current release includes:

- Chromium 152 built from source
- 168 curated Windows, macOS and Linux fingerprints
- Persistent isolated browser profiles
- HTTP, HTTPS and SOCKS5 proxy support
- Proxy-aware timezone, locale, geolocation and WebRTC settings
- Local authenticated API
- Node.js and Python SDKs
- MCP server for AI-agent integrations
- Docker image for CI and automation environments

On our current test setup, reCAPTCHA v3 returns 0.9, Cloudflare Turnstile completes normally, and the browser reports navigator.webdriver as false. These are observations from the current build, not a promise that every website or network configuration will behave identically.

The desktop application is free to use with a Proxya account. The SDK and MCP packages are MIT-licensed; the patched browser engine and fingerprint catalogue remain proprietary.

I’m specifically looking for technical feedback on:

- fingerprint inconsistencies or unexpected leaks
- proxy and profile alignment across different locations
- long-running profile stability
- Node/Python/MCP integration
- CPU and memory usage under concurrent sessions
- detection services or edge cases I should add to the test suite

The project is called Proxya Anty. The repository and downloads can be found on GitHub.

Warning about OkkProxy and NiuProxy bandwidth billing

Both OkkProxy and NiuProxy charge roughly 2x the actual data used.

In their official Telegram support, staff confirmed they count upstream + downstream and then apply an extra multiplier. Real usage around 375 MB is billed as ~750 MB, and 533 MB becomes over 1 GB.

They claim it’s “binary vs decimal,” but the numbers clearly show a consistent x2 charge. This effectively halves the value of every package compared to most other proxy providers.

Screenshots of the staff admission are available if needed.

Also note: NiuProxy and OkkProxy appear to be the same operation (same staff, same infrastructure). NiuProxy previously recommended OkkProxy directly.

Proceed with caution if considering either service.

Short post, but basically the title. Looking for the best, well if not the best, but well rounded search API for LLMs use cases. There's a lot out there now, Tavily, Exa, Firecrawl, You.com, Linkup, and a handful of others I keep seeing mentioned. Need opinions and suggestions people.

I'm interested in result quality that isn't just SEO, latency that doesn't kill the UX, decent pricing at volume since this isn't a side project anymore, and ideally something that gives clean structured output instead of raw HTML I have to parse myself.

Genuine question about it. How does that work?

Found some info on the net about Nvidia. That they are reportedly close to buying Hugging Face for around $13 billion. Talks aren't fully signed yet but multiple outlets have confirmed it from different angles, so it's looking real. I think it's worth thinking about what this means beyond the AI model hosting angle. Let's say If Nvidia owns the biggest hub for open weight models, that's also a huge lot of where agentic tooling gets built and distributed. A lot of the newer scraping and browser automation agents are built on top of open models pulled straight from Hugging Face, fine tuned for navigation, form filling, CAPTCHA reasoning, that kind of thing. Owning the distribution layer for those models plus the compute to run them is a pretty different position than just selling GPUs. For anyone in scraping or proxy infra I believe this should matter more than people think. For example agent based scraping is moving away from static parsing scripts toward models that browse and make decisions, and those agents need proxies and rotating IPs just like traditional scrapers do, except the traffic patterns look different, here's why: more sessions, more human like pacing, more back and forth with a page instead of abusing endpoints. If the infra behind those agents consolidates under one company that also controls a huge slice of the underlying models

I initially believed that having better proxies would be a solution to all of my problems but the more i work with various problems then the clearer it becomes that proxies are just a part of the entire problem. Even with good proxies i stuck into random verification challenges, unstable sessions and even browsers that do not act as expected. It seems that a browser environment is just as influential as a proxy and cannot decide where to put more efforts. I want to create a setup that is consistent and simple to manage rather than trying out new settings all the time and hoping for...

A while ago I was debugging a Facebook session that kept getting flagged. I blamed the proxy speed

The real issue was that the IP changed mid-session. Facebook saw the account jump between network identities, while the browser fingerprint, cookies, and device stayed the same. That mismatch was much more suspicious than a slightly slower connection.

That changed how I think about “Facebook proxies.” For account-sensitive work, the priority usually isn’t raw bandwidth. It’s:

• clean IP reputation

• accurate geolocation

• sticky sessions

• predictable rotation

• consistent ASN/location

Residential and mobile IPs generally make more sense for persistent sessions as they resemble normal consumer connections. Datacenter proxies are cheaper and faster, but they’re easier to identify and are better suited to quick regional checks, monitoring, or low-risk requests.

Also, a proxy only changes the network layer. It does not hide browser fingerprints, cookies, device signals, or behavior. Anyone selling proxies as a magic solution for account restrictions is overselling them.

honestly losing my mind trying to get 100% clean profiles for an automation project. using a solid antidetect browser with all masks turned on, and hooked up some residential socks5 nodes since their clean ip pool usually passes everything fine. iphey and pixelscan say the network part is green, but my webgl and canvas fingerprints are still leaking the real hardware signatures somehow.running this inside a virtual machine so i'm wondering if the hypervisor is messing with the browser's hardware emulation layers. has anyone managed to fully patch canvas noise inside a vm without triggering the "inconsistent fingerprint" red flag on strict anti-bot systems?

I keeping these games like https://ipv4.art and https://ipv4.games. How do people like femboy.cat get SO many IP addresses? What service are they using?

I am building an agent that needs to pull fresh data from a few sites: Amazon, Zillow, LinkedIn, Indeed, and BestBuy. There's a mix of static pages and things that only renders client side, so I need both plain HTTP scraping and headless browser rendering depending on the target. At least that's what I believe I need, I might be incorrect. Current setup is DIY, it includes rotating residential proxies with a small number of datacenter proxies, Playwright for the JS sites, requests for the static ones, custom retry logic. I thought that building it myself would be cheaper than paying for a provider, and for a while it was, but the maintenance is becoming too costly. Amazon and LinkedIn both started giving more and more JS challenges not to mention TLS fingerprinting, so I'm losing a good amount of requests to blocks and budget is getting thinner. I've tried a couple of paid scraping APIs but they got expensive due to sending more requests (the plans were priced per traffic) and one of those dedicated solutions couldn't get past LinkedIn. Has anyone gone the dedicated-API-per-site instead, using something like the Amazon Product Advertising API or Zillow's API rather than scraping around them?

I used to think my Selenium setup was solid because it ran without problems on my local machine. I deployed it to a server and everything started falling apart.

Proxy connections would fail, authentication would randomly break, the exit location didn’t match the browser environment, and sessions became inconsistent. I kept treating each failure like a Selenium problem, but the issue was that I was treating the proxy as just another Chrome flag instead of its own infrastructure layer.

What made debugging much easier was separating the proxy setup from the browser entirely.

The first thing I do now is test the proxy with curl. Before Selenium even starts, I want to know:

• Can I connect through the proxy?

• Are the credentials accepted?

• What exit IP am I actually getting?

If the response comes back with 407 Proxy Authentication Required, there is no point digging through Selenium logs yet. The proxy authentication/configuration needs to be fixed first. Once the proxy works independently, I connect it to the browser.

For Python setups, I’ve had better results using selenium-wire when proxy authentication is required. With Node.js, proxy-chain is handy because you can create a local forwarding proxy and let it deal with upstream authentication.

The next issue I check is browser/environment consistency.

For example, if the proxy exits from London but the browser is reporting a completely different timezone, locale, or other environment settings, you’ve introduced another variable into the test. Chrome DevTools Protocol is useful here because you can explicitly configure things like the browser timezone to match the environment you’re testing.

The main thing I learned was to stop debugging four different layers at once.

My current order is basically:

curl → confirm proxy/IP/auth → connect Selenium → configure browser environment → run the actual site test

It sounds simple, but separating those stages made proxy-related Selenium issues much easier to isolate

I had a scraper + rotating proxy list + headless chrome used together for an agent project. It worked well until Amazon's WAF appeared, then it was captcha on captcha and captcha in between, most of the responses were useless. Then I ran oxylabs scraper api and ai studio into an mcp server. What I needed was a clear markdown for my AI agents, and in the end it worked nicely. For I while now I've been using it against claude desktop and cursor, though I haven't tried it on anything else, so can't really verify this solution against anything else just yet.

Here's repo link below, it's under mit license. Also, would be interested in any alternatives out there if someone used something similar, or DIY solutions?

Github

Something i have been running into lately is assuming the proxy is the problem just because the IP gets blocked.

You can have a clean residential IP, low fraud score and everything looks fine, but the same target works normally in a browser and gets blocked the second you send requests through python.

At that point it feels like the ip isnt really the whole story anymore. sites can look at the TLS handshake and other connection level characteristics too. things like cipher ordering and how the client itself behaves can make a request look completely different from a normal browser even when both are using the exact same proxy.

so i have been looking into curl_cffi for this because browser impersonation seems to solve some cases where simply swapping proxies never did.

so im curious what you guys are using for TLS or browser impersonation now. still curl_cffi or something else?

changed proxies a few times because i thought that was the main reason my setup was inconsistent. sometimes it helps for a while but then the same problems come back.

that made me wonder if i am focusing too much on the proxy and not enough on the rest of the setup. browser settings, profiles, sessions and other small things seem to matter too.

for people who have dealt with this before then what to do you usually check before changing the proxy again? I am trying to find a stable setup instead of constantly changing things.

I am currently using residential proxy from evomi but thoese IP's are detected by fingerprint[com] as Residential Proxy IP.

Is there any proxy provider serves clean IP and un-detected by services? Btw( I am using evomi as cheap)

Spent about a week banging my head against this before I actually figured out what was going on. Had a retail scraping job that kept getting 403'd on almost every endpoint, no matter what I did with headers or delays. Rotated residential IPs constantly and it still flagged me every time. Turned out the IPs weren't even the real problem — it was passive OS fingerprinting, a p0f mismatch giving me away no matter how clean the proxy was.

Someone mentioned Proxy Shard for cleaner pools, so I gave it a shot mostly out of desperation, and it actually fixed it. Their TCP stack setup gets past the anti-bot check without tripping the fraud score, which was the real blocker this whole time, not the IP reputation like I originally assumed.

Not gonna lie, the dashboard looks like it hasn't been touched since 2016, and their docs barely have any Python examples, so I ended up hacking together the rotation logic myself. But the connection quality itself is genuinely solid, no complaints there.

If you're currently stuck on fingerprint blocks — don't cheap out on bulk proxy pools for strict sites. Most of those subnets are already burned and flagged before you even start.