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The developer behind sprinklz.io says his site became slow after he shared it on Hacker News, with server load remaining high even as logged-in human use was modest. Reviewing request logs, he attributed a large share of traffic to automated crawlers, including one service that repeatedly checked the site; he blocked that service and added rate limits and other infrastructure changes.
The developer of sprinklz.io says his website became persistently slow after he posted the feed-reader project to Hacker News, and that request logs showed automated crawlers contributing heavily to the load. He says he blocked one service that was checking the site repeatedly, added rate limits and made infrastructure changes, but did not publish traffic totals or an independently verified breakdown.
The developer, writing on sammystraus.com, said his Hacker News post received roughly 100 upvotes. He initially assumed the slowdown was the result of people visiting the site. But, he wrote, the performance problems continued and worsened several days after the post, while the application showed a relatively small number of active logged-in users alongside high server load.
To investigate, he added logging that counted requests by URL path and reviewed aggregate NGINX logs. He said most requests did not attempt to retrieve news articles or run the JavaScript needed to render the site, which is built as a single-page application. He also reported that nearly half of the traffic in the logs came from one user, which he identified as a service that monitors websites and summarizes changes for an AI newsletter.
The developer said he blocked that service after finding it queried his site many times per minute. He also observed requests from crawlers that identified themselves as Claude Bot, OpenAI Bot and Google’s search indexer, as well as vulnerability scanners probing paths associated with WordPress and phpinfo, despite his site not being a WordPress website. He added a robots.txt file, allowed search-related traffic, introduced rate limits and made other infrastructure changes.
When Crawlers Strain Small Websites
The account illustrates how automated requests can create a real operational burden for a small website, even when the visible audience appears manageable. Repeated polling and crawling can consume server capacity, slow pages for human visitors and make it harder for an independent developer to distinguish ordinary attention from automated demand.
It also highlights a limit of robots.txt: the developer used the file to discourage some crawlers, but it is a request to automated clients, not a technical barrier that every bot must follow. Rate limits and blocking can reduce pressure, though they require site operators to make choices about which services and users they want to allow. The report offers a specific operator’s experience, not a measurement of AI crawler traffic across the web.
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The Site and Its Hacker News Debut
Sprinklz.io is described by its developer as a customizable feed reader. Users can set their own adjustments, including deprioritizing topics such as AI or large language models, and can apply other custom rules. The developer said the service is free to use.
That functionality was the subject of the Hacker News post about a month before the account on his blog. He said the response was useful exposure for the product, but also preceded the performance problems. His post does not establish that the Hacker News audience itself caused the continuing load: the log review, as he described it, pointed to automated requests rather than a comparable volume of active human sessions.
“A majority of the requests did not even make an attempt to fetch news articles.”
— The developer of sprinklz.io, writing on sammystraus.com
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Traffic Counts and Bot Identity
The account does not include raw request counts, a precise measurement period, server capacity figures or a before-and-after performance benchmark. The statement that nearly half of traffic came from one user is the developer’s reading of aggregate logs; the post does not publish evidence that would allow an independent review of the attribution or the service’s exact request rate.
It is also unclear how much of the site’s slowdown came from the single monitoring service versus other crawlers, scanners, human visits or the application’s own capacity limits. The developer named several crawler categories but did not provide a complete traffic breakdown, say whether the crawlers were following robots.txt, or report whether blocking and rate limits resolved the slowdown.
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Further Performance Work Planned
The developer said he had made several infrastructure improvements over the weeks after identifying the traffic and expected them to produce substantial performance gains for users. He did not list the changes in the account or give a date for a detailed performance report. The next clear measure of progress would be updated operational data showing whether response times and server load improved after the changes.
For now, the reported response combines crawler controls with broader efforts to make the site handle more requests. Whether those measures will be enough for future spikes, and how the site will balance search indexing against unwanted automated access, remain open questions.
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Key Questions
What happened after the developer posted to Hacker News?
The developer said sprinklz.io became slow after the post received roughly 100 upvotes. The slowdown continued and worsened several days later, prompting him to inspect request logs.
What did the logs show?
He said most requests did not attempt to fetch news articles or run the JavaScript that renders the single-page app. He also reported that nearly half of the traffic came from one user, which he linked to a service that monitors websites for an AI newsletter.
Did the developer say all AI bots were responsible?
No. He described one service making frequent requests, several identifiable crawlers and vulnerability scanners. The post does not provide enough traffic data to determine each group’s share of the load.
What steps did he take?
He said he blocked the frequently querying service, added a robots.txt file, set rate limits and made infrastructure changes. He did not report a quantified before-and-after result.
Was the slowdown resolved?
The account says infrastructure work was under way and expected to improve performance, but it does not confirm that the slowdown was fully resolved or provide updated response-time measurements.
Source: hn
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