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You start tuning the obvious knobs. Rotation intervals get shorter. Concurrency limits get nudged upward. Exit pools are regrouped, split, merged, and split again. On dashboards, something always improves. Latency drops. Throughput rises. Request volume looks healthier. And yet, a few days later, something important breaks. Logins fail more often. Accounts that used to survive…

At first, everything works. Residential proxies handle sensitive flows, datacenter proxies chew through bulk tasks, and the system scales simply by adding more IPs. When problems appear, the fix feels obvious: rotate faster, buy a larger pool, or switch providers. Then one day, adding more proxies stops helping. Success rates plateau. Some workflows become fragile….

Everything looks normal at a glance. Requests are flowing, proxy latency is stable, and no single IP pool appears exhausted. Yet results keep deteriorating in ways that are hard to pin down. Certain actions fail far more often than others. Some accounts decay quickly, while others survive under nearly identical automation logic. Adding more IPs…

You open your proxy dashboard: latency is fine, success rate looks good, reputation checks say your exits are “clean”.But on the platform side it’s a different story: – Logins that used to pass quietly now trigger captchas.– Accounts with months of history suddenly get “unusual activity” warnings.– Some accounts stay healthy, others die fast under…

You set up a “serious” proxy stack: residential IPs for accounts, datacenter pools for scraping, some rotation logic on top.Yet in real use you still see the same problems: – Commerce accounts randomly hit verification even though you barely touch them.– Price and inventory monitors run fine for a while, then a whole block of…

You start with a neat setup: one proxy provider, a rotation script, a handful of workers.Small tests fly, logs look clean, and everything appears “production ready”. Then real traffic hits: – Latency spikes and drops with no obvious pattern.– Some accounts suddenly drown in captchas while others stay fine.– Scaling workers from 5 to 20…

You wire up a new proxy pool, tests all pass, and a small batch of accounts runs smoothly.Once real traffic hits, a different story appears: – Latency goes up and down without a clear reason.– Certain accounts start hitting captchas and soft blocks in waves.– Scrapers slow to a crawl whenever you raise volume. You…

Your scripts run, responses look “OK”, proxies show as “online and healthy”.But in real usage: – Accounts slowly collect more captchas and soft flags.– Some regions feel much slower and less stable than others.– As soon as you push volume, weird errors appear, then vanish again. No big outage, no clear provider error — just…

You buy more proxies, wire up “smart rotation”, and spread traffic across a big shared pool.On paper you’re safer: more IPs, wider regions, fewer hits per exit. In reality: – New accounts still get flagged in batches.– Old accounts suddenly see a wave of captchas.– When one task misbehaves, whole regions start feeling unstable. The…

You add more proxies, but failures keep clustering in the same places. One workflow becomes unreliable, another stays fine. Latency graphs look healthy, yet success rates on important actions quietly slide. The most confusing part is that nothing appears consistently broken until a burst of traffic arrives and the whole system starts tripping over itself….