Which platform's API/scraping restrictions have burned you the most?
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Building an API that pulls data across 13 social platforms, and the thing that's eaten the most engineering time isn't the scraping itself, it's how differently every platform breaks. Rate limits that change without notice, auth flows that expire silently, structured data one week and a wall of JS the next.
Curious what's bitten other builders here. Which platform has been the worst to depend on, and what did you end up doing about it?
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@lukem121 which platform acts fine until it hits production?
@lukem121 Which platform makes you check the logs first every morning?
@lukem121 Ever had a bug that made the whole team laugh later?
@lukem121 Has a silent update ever ruined your weekend?
@lukem121 Which platform changed the rules on you the most?
@lukem121 Which API has actually been a pleasant surprise?
For us, it's usually not one platform but the constant undocumented changes that cause the biggest headaches. Something works perfectly for weeks, then a small frontend update or stricter rate limits suddenly break the workflow. We've found that building good monitoring and fallback logic saves more time than trying to make a scraper "perfect."
Curious....out of the 13 platforms you're supporting, which one has been the most unpredictable lately?
Different domain — I do this on the e-commerce side, not social — but the failure taxonomy is identical, and the one that's burned me most isn't rate limits or a clean 403. It's the silent shadow-block: the endpoint returns 200 with subtly stale or degraded data instead of erroring. A 403 you can detect and escalate; a 200 with poisoned data quietly corrupts your dataset for days before anyone notices.
+1 to Laiba on monitoring — but the check that actually catches this is a schema/shape contract on the response body, not HTTP status. Status lies; the payload doesn't. If a field that's populated 99% of the time suddenly goes null across a whole batch, that's your real alarm.
On the "structured one week, wall of JS the next" whiplash: I go straight for whatever JSON the page already ships (JSON-LD, the internal API the frontend calls) rather than parsing rendered HTML — markup churns, the data contract behind it is stickier. And once you hit a real JS sensor (Akamai _abck, Kasada), stop — no server-side trick beats an L3 block.
Running distribution for a consumer app across three platforms taught me the spread. Bluesky's AT Protocol does everything through the public API, likes, reposts, search, notifications, it just works. Threads technically posts and replies but every useful read sits behind another OAuth scope you have to re-consent your way into. Instagram is the worst, there is simply no API for engaging anyone else's content, a human in a browser or nothing. I stopped fighting it: automate discovery everywhere, act by hand where the platform demands a human.
LinkedIn and X are usually the hardest because the rules, rate limits, and enforcement patterns can change quickly, and the business risk is higher when customers depend on that data operationally. The best mitigation I have seen is being very clear about data freshness, source reliability, and failure states. For customers, predictable degradation is much better than a black-box API that silently breaks.