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Cloudflare Issues Reports

Latest outage, problems and issue reports in social media:

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  Jaideep Parashar (@jaideepparasha7) reported 3 minutes ago

  Another Layoff: Cloudflare lays off 1100 employees. They didn't cut the jobs because Cloudflare is struggling. This is true AI effect now, when companies are laying off without any issue.

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  moonboy (@Szypetike) reported 3 minutes ago

  @PaulGugAI Just use litellm it's a solved problem. The other side of the coin is either running your own open source models here nomad is positioned to benefit plus Nvidia or buy hosted model and here existing enterprise providers are going to benefit aws, azure, now cloudflare etc. plus Nvidia. However if 31b param models are the 80% workforce there's significant downward pressure on Nvidia et al in the medium and long term

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  Contract Level (@contractlevel) reported 10 minutes ago

  @ygorz01 @DefiLlama @chainlink Schmidt said in one of his talks with Sergey to not force decentralization where it doesn't necessarily make sense. If cloudflare (where relay is deployed) or defillama api is down, the only impact to the system is delayed rebalancing. Funds stay earning in active strategy.

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  Marcus Gill Greenwood (@inventur_es) reported 11 minutes ago

  @FinlaysonConnor I don’t think the issue was whether Webflow was bad at what it did, the fact is web design is now both trivial and virtually free with LLMs. Hosting is also free (via services like Cloudflare) or very cheap. I actually think the pivot was necessary. Same with Wix but at least they got ahead of it with Base44 acquisition

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  Tom Galland (@tom_galland) reported 11 minutes ago

  @woocassh Cloudflare domain billing bugs are a special kind of painful. Check your card statement and open a support ticket with the transaction ID - they're usually pretty good at sorting it out fast.

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  Siddharth (@ssiddharrth) reported 11 minutes ago

  Built my pincode/IFSC lookup API on Railway + PostgreSQL because that's what I knew. Realized recently: it's 340k rows of static data that never changes. Pure reads. No reason to pay for a always-on server in one region. Moved it to Cloudflare Workers + D1. Serves from the edge, fits in the free tier, faster for everyone. 🥳🥳🥳

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  arsey (@arseyHat_) reported 14 minutes ago

  @KiwiFarmsDotNet @Cloudflare CloudFlare needs to learn that when you bend over and become someone's *****, it's not a one-time thing. They coming back for more of their bussy. Bend over, CloudFlare. **** CloudFlare.

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  Devanshu (@DevanshuXi) reported 16 minutes ago

  People usually learn tries in the context of autocomplete and dictionary problems, but once you start working on real infra systems, you realize tries are everywhere underneath modern high-performance networking and search stacks. I was recently reading the @Cloudflare blog about the performance bottlenecks of Linux BPF LPM tries used in packet routing and firewall systems, and learned something important. At scale, “search” stops being an algorithms problem and becomes a memory systems problem. The interesting part about tries is that they trade comparison-heavy searching for deterministic state transitions over bits/symbols. Instead of repeatedly comparing full keys like balanced BSTs or hash collision chains, a trie incrementally consumes the key itself during traversal. That sounds theoretical until you realize this is exactly why networking stacks use longest-prefix-match tries for CIDR routing. Routers are effectively doing millions of searches/sec over prefixes where latency matters more than throughput averages, branch mispredictions hurt badly, deterministic lookup depth matters, and memory locality dominates everything One thing that becomes super obvious from the BPF trie implementation is how “Big-O” alone becomes almost useless for understanding performance. The Linux BPF LPM trie uses only 2 child pointers per node, which means densely populated prefixes effectively degenerate into many sequential binary branch decisions. In theory the asymptotics still look acceptable. In practice, the trie height explodes, pointer chasing increases, and lookup throughput collapses as the structure outgrows cache and starts hammering dTLBs. That’s the part most people miss about high-performance systems: a cache miss is often more expensive than the actual computation. Modern CPUs are absurdly fast at arithmetic. They’re slow at waiting for memory. Also I was solving a suffix-query problem recently where the straightforward Trie solution itself wasn’t enough. The interesting part became optimizing the traversal and memory layout rather than just “using a Trie.” The strategy was to build a highly optimized reversed Trie where every node stores the “best” candidate index for that suffix path. Instead of doing expensive comparisons during query time, I pushed almost all decision-making into insertion time. While inserting container strings in reverse order, every node keeps track of shortest matching string and if tied, earliest index. So during query traversal, the search becomes almost embarrassingly simple: walk backwards through the query, follow pointers until traversal breaks, and the current node already contains the precomputed optimal answer. No heap allocations during queries. No suffix comparisons during queries. No backtracking. No secondary scans. Just incremental state transitions through memory. The funny thing is the actual algorithmic idea is pretty small. Most of the engineering challenge became memory optimization. A naive pointer-heavy Trie immediately started hitting MLE because every node carried 26 pointers. So the optimization was moving toward index-based contiguous storage: replacing raw pointers with integer child indices storing nodes in a flat vector, reducing pointer chasing improving locality, cutting memory almost in half And honestly this is exactly the same class of problem that appears in production systems. In CP, tries feel like string DS problems. In real systems, tries are actually cache-behavior problems disguised as data structures. That’s why production systems rarely use textbook tries. Instead you start seeing: Patricia tries, radix tries, crit-bit trees, compressed tries, LC-tries, succinct tries finite state transducers, double-array tries. All basically solving the same underlying issue: “How do we preserve fast prefix search while minimizing memory movement?” Even path compression itself is basically a cache optimization disguised as a data structure trick. So, This is why systems engineering feels so different from competitive programming sometimes. In CP, we optimize operations. In real infra, we optimize movement through memory.

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  Aditya Miskin (@ad1tyamiskin) reported 18 minutes ago

  using @Cloudflare Think for the first time and holy ****!!! got the same feeling as using ai sdk when it first released. they cooked hard!!! 🫡 will be documenting my experience building an ai background agent system like ramp inspect 👀

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  h 🇺🇦🇵🇸 (@PrototypePWND) reported 19 minutes ago

  @RixThereal99054 I think I was I thought you heard it. Probably the cloudflare warp connection issues

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  Iqra (@AiWithIqra) reported 23 minutes ago

  The neighbor's final advice was the most actionable. He sat down and wrote out a list of 6 things every internet customer should do: 1. Turn off the public Xfinity hotspot (or your ISP's equivalent Spectrum, Optimum, and Cox all do this too) 2. Manually set your Wi-Fi channel instead of "Auto" 3. Disable QoS / Smart Network "optimization" features 4. Change your DNS to Cloudflare (1.1.1.1) or Google (8.8.8.8) 5. Buy your own modem and router, stop renting from the ISP 6. Test your speed with fast. com or speedtest. net using a non-ISP server, never trust your ISP's own speed test Total cost: $150-300 in equipment, paid back within a year. Total time: One afternoon of setup. Total impact: Often 2-5x improvement in real-world speeds. The customer went from paying $90/month for "fast" internet that crawled to paying $60/month for the same internet that finally worked.

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  Julian Goldie SEO (@JulianGoldieSEO) reported 24 minutes ago

  The Mythos-1 numbers are wild. And they explain why Anthropic is being careful. In 30 days, Claude Mythos preview reportedly found: → 23,019 vulnerabilities. → 6,022 high or critical issues. → 90% true-positive verification. → 2,000 bugs in Cloudflare systems. → 271 Firefox vulnerabilities patched. → $1.5M wire fraud blocked in real time. The problem? AI can now find issues faster than humans can fix them. That’s why Claude Security matters. Find the bug. Write the patch. Let humans review.

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  Satoshi Nakamoto, Andrew Rulnick (@MickeySteamboat) reported 24 minutes ago

  Kind of annoyed to learn I was right about @Cloudflare blocking my IP addresses. Really ******... Has caused a lot of problems over the past six months. I didn't have time to investigate it deeply until today to confirm. It's a bad look for a business to single out their next competitor @CloudflareHelp @CloudflareDev

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  basedcapital (@thebasedcapital) reported 26 minutes ago

  @catalinmpit locked down a hetzner box the same way, tailscale + cloudflare saved me from a brute force attempt.

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  Outbound Autonomy (@outbndautonomy) reported 26 minutes ago

  🚫 Ahrefs — Audit failed entirely. Protected by Cloudflare. The bot can't even reach the homepage. 🚫 Moz — Same problem. Cloudflare challenge blocked the scan. Irony: Two SEO tool companies blocking automated site analysis — the very thing their customers need. 🤡