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Cloudflare Issues Reports

Latest outage, problems and issue reports in social media:

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  Steven Liss (@This_Liss) reported 3 minutes ago

  @joe_zappa @fsinton @BishPlsOk Brands are doing anything they can to influence how they show up in AI. There's already a market for off-site GEO and astroturfing. AI companies have a choice: increasingly get blocked by publishers, pay publishers (lol never), or rely on their existing retrieval system to inherently filter for relevance while allowing publishers a business model that enriches search results and keeps publishers in business. Perplexity's now an enterprise B2B company, so removing any possibility of ads is more aligned with their use-case. They're also more likely to get blocked outright by publishers, since the amount of display ad revenue at stake from Perplexity referred traffic is vanishingly small. Realistically, I see Anthropic following suit until publishers become much more aggressive about blocking noncompliant bot traffic (which Cloudflare is helping accelerate or the legal costs of unauthorized retrieval increase (NY state's Stealth Crawler Prohibition Act).

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  güs (@nukefags) reported 5 minutes ago

  @NEVER_G0ON Soybooru and ze Jarti haven’t used cloudflare in like 3 years. Null and d0ll swapped it over to a custom DDoS retarding service when the domain was switched to .st

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  Devin Kurant (@DevinKofsky) reported 6 minutes ago

  @janxpm @Namecheap I spent 2 hours this morning thinking it was my fault and configuring cloudflare, only to discover the real issue. Clients think I broke there sites.

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  perdrix (@perdrix_fl) reported 6 minutes ago

  @glenngabe Another HUGE item for AdSense publishers is that @Cloudflare blocks Google’s access to ads.txt by default… I learned that one the hard way and it would be such an easy fix for Cloudflare to make.

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  Hemant (@HKsoldev) reported 6 minutes ago

  Why this never breaks: After the first lookup your computer saves that answer locally. Next time you visit GitHub? It skips ALL those steps. That's called TTL (Time To Live) a timer on every DNS record. 8 trillion DNS queries happen every day globally. Most never even reach a root server because of this cache. 40-year-old technology. Still running the entire internet. 🤯 @Cloudflare (1.1.1.1 DNS) @googledns (8.8.8.8)

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  Alex Greenland (@ajrgd) reported 8 minutes ago

  cloudflare could never

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  Artyom Shimanski (@a_shimanski) reported 13 minutes ago

  @gitcommit90 @Cloudflare most people just never check what's already included

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  Justin Schroeder (@jpschroeder) reported 14 minutes ago

  @dschewchenko Good luck with that. The loop is our fault. Not having limits is 100% a cloudflare problem.

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  Artyom Shimanski (@a_shimanski) reported 14 minutes ago

  @XJosephCox @Cloudflare yeah, hard caps would fix half the horror stories

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  favoritbookshop🚢 (@favoritbookshop) reported 14 minutes ago

  For years, the crypto industry has searched for a mainstream use case for stablecoins. The answer may be arriving from an unexpected direction: not humans, but machines. Cloudflare is pushing toward an agentic Internet where software can request and pay for digital resources automatically. Its Monetization Gateway is designed to let websites, APIs, datasets and MCP tools charge users in stablecoins through x402, an open protocol built around the long-unused HTTP "402 Payment Required" status. This matters because AI agents operate very differently from humans. A human might make a few payments per day. An autonomous agent could make thousands of API calls, purchase datasets, access compute, retrieve information and interact with other services — potentially around the clock. Traditional payment rails were not designed for this. Why stablecoins fit the machine economy AI agents don't need a bank account in the traditional sense. They need: - programmable spending rules; - fast settlement; - global access; - low transaction costs; - machine-readable payment instructions; - the ability to transact without a human approving every purchase. That is exactly the problem stablecoins can address. Cloudflare describes x402 as a mechanism where an agent requests a resource, receives a machine-readable "402 Payment Required" response containing payment terms, pays, and retries the request with proof of payment. The payment itself becomes the credential. That is a radically different model from: Sign up → create account → enter card → receive API key → get billed later. Instead: Request → pay → receive. For machines, that distinction is huge. The infrastructure is already forming Cloudflare isn't moving alone. MetaMask has introduced Agent Wallet, giving AI agents dedicated wallets with user-defined policies and a security pipeline that includes transaction simulation, threat scanning and MEV protection. Transactions outside predefined policies can require human approval, while eligible safe transactions receive up to $10,000 per month in Transaction Protection coverage. This is an important evolution. The agent receives a budget, follows predefined rules, pays for resources and potentially earns revenue — without requiring a human to manually sign every transaction. The bigger shift: from blockchain economy to application economy This is where the thesis becomes interesting for crypto investors. The next major value capture may not happen at the blockchain layer alone. It may happen at the application and infrastructure layer — where users and agents actually consume services. Cloudflare's own vision is explicit: agents could eventually become primary buyers on the Internet, purchasing datasets, API calls, tools and compute automatically. If that happens at scale, stablecoins stop being merely an alternative payment method. They become machine-native money. What traders should watch The investment thesis is broader than simply buying “AI tokens.” Watch the infrastructure connecting four layers: AI agents → wallets → stablecoins → payment protocols The winners could include: - stablecoin issuers; - payment protocols; - agent-wallet infrastructure; - blockchain networks optimized for cheap settlement; - API and data marketplaces; - DeFi protocols that agents can interact with programmatically. The most interesting question is therefore not: “Will AI use crypto?” It is: “How much economic activity will autonomous software generate — and which crypto rails will capture that activity?” We're still early. But the direction is becoming increasingly clear: the next generation of crypto users may not have a face, a phone or even a human behind the transaction. They may be agents. And when millions of machines start buying from millions of other machines, someone will need money that machines can actually use. Stablecoins may have just found their killer customer.

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  Aleksejs Zuravlovs (@aleksztrading) reported 20 minutes ago

  @shownotover Oh.. you are from Pakistan! I had some good programmers from there many years ago. Damn, that's backwards, it should be the opposite, like in Steam - you get charged *less* from poorer countries, which makes sense. In that case, re-review everything. Do you need Contabo or can you push everything to Cloudflare? (it's free for quite a lot of traffic, but better ask Grok to verify the limits) Do you really need Grok at $30? I would get ChatGPT Codex at $20 + Open Code Go at $10 - much stronger stack, I think.

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  Dwinity (@dwinity_eco) reported 20 minutes ago

  @signalapp @Cloudflare the math was never the weak part. the key directory was. every e2e messenger asks you to trust a server handing out keys, and apple shipped contact key verification in ios 17.2 for exactly that. verification you have to remember to do is verification nobody does.

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  Yamparala Rahul (@yamparalarahul1) reported 21 minutes ago

  @vercel & @vercel_dev why you pause all the projects of user if free trier usage is going beyond, why not help me (users) optimise? This make me and others probably shift to @Cloudflare

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  Amanda Lauren Machen (@AmandaLauren7W) reported 21 minutes ago

  @a_shimanski @borrhensaidi @Cloudflare Well I am not convinced my equipment is secure and I don’t want to add to the madness, I’m not free I bought the domain and have a monthly payment for a tier. Have given no one access to! Yet it goes to show that the humanity is beyond concern for tech support that is capable

• 
  TheValueist (@TheValueist) reported 23 minutes ago

  ELECTRONICS MANUFACTURING SERVICES THE MORE-THAN-10X MANUFACTURING RAMP IS A DIRECT POSITIVE FOR FLEX AND SANMINA (READ-THROUGH 8) AFFECTED COMPANIES: Flex Ltd. (FLEX: Singapore); Sanmina Corp. (SANM: US). DIRECTIONAL IMPACT AND MAGNITUDE: Positive and medium, with upside to the magnitude if Cerebras’ 2027 revenue and production objectives are achieved. Cerebras explicitly identified Flex and Sanmina as manufacturing partners and stated that manufacturing capacity is already approximately 4x the H1 2025 level. The company expects capacity to increase by more than 10x during 2026 and has already contracted facilities capable of supporting another 3x-4x expansion in 2027. This is one of the clearest direct supplier read-throughs from the call. Flex and Sanmina should benefit from factory preparation, system assembly, rack integration, testing, supply-chain management, quality control, repair, and potentially ongoing lifecycle services. Cerebras systems are high-value, technically complex products, which can support greater manufacturing-services content than conventional low-complexity electronics. The scale of the planned expansion also creates an operating-leverage opportunity for the manufacturing partners. Initial factory setup, process qualification, tooling, labor training, and yield improvement require upfront costs. Higher production volumes can improve asset utilization and spread fixed manufacturing costs across a larger output base. The principal uncertainty is allocation. Cerebras did not disclose how manufacturing volume, capital requirements, or economics are divided between Flex and Sanmina. No assumption should be made that the 10x capacity expansion is shared equally. The near-term catalyst is the 2026 factory ramp and the launch of CS4. The 2027 catalyst is the additional 3x-4x contracted manufacturing expansion required to support Cerebras’ objective of more than tripling core revenue. The longer-duration implication is positive for the broader outsourced-compute manufacturing model. AI infrastructure is expanding beyond semiconductor fabrication into increasingly complex systems, racks, power delivery, and integration, creating a larger role for high-end electronics manufacturing services. AI CLOUDS AND NEO-CLOUD ECONOMICS VERTICAL INTEGRATION CREATES A LONG-DURATION COST THREAT TO MERCHANT GPU CLOUDS, DESPITE SUPPORTIVE NEAR-TERM CAPACITY SCARCITY (READ-THROUGH 9) AFFECTED COMPANIES: CoreWeave Inc. (CRWV: US); Nebius Group N.V. (NBIS: Netherlands); Applied Digital Corp. (APLD: US); IREN Ltd. (IREN: Australia). DIRECTIONAL IMPACT AND MAGNITUDE: Positive and medium in the near term because severe compute scarcity supports utilization and rental pricing; negative and medium-to-high over the longer term because vertically integrated accelerator-cloud providers can operate at structurally lower capital cost. Cerebras disclosed that demand exceeded immediately available owned capacity to such an extent that the company temporarily rented back some of its systems from customers. The arrangement reduced core gross margin by approximately 500 bps in Q2. This is strong evidence that premium inference capacity remains scarce and that customers are willing to support economic arrangements that bring capacity online sooner. That scarcity is a near-term positive for CoreWeave, Nebius, Applied Digital, IREN, and other owners or developers of AI infrastructure. High demand should support strong utilization, financing availability, customer prepayments, and attractive contract terms. The Cerebras call therefore does not indicate an immediate collapse in merchant AI cloud economics. The longer-term read-through is more challenging. Cerebras stated that it has lower net capital expenditure per megawatt than most AI cloud providers because it deploys its own systems at internal bill-of-material cost rather than purchasing accelerators at a third-party vendor’s gross margin. Its largest customer also reimburses a meaningful portion of data center fit-out costs. If Cerebras can combine lower hardware acquisition cost, customer-funded infrastructure, premium pricing for fast tokens, and higher throughput per watt, it could price below merchant GPU clouds while still earning attractive margins. Merchant GPU clouds generally purchase hardware from NVIDIA or other third parties, absorb HBM and system-vendor economics, and then recover those costs through cloud pricing. A vertically integrated competitor captures the hardware margin internally and can optimize the entire stack around its own workload. This is the same structural advantage that hyperscalers seek through custom silicon. Disaggregation creates an offsetting opportunity. Cerebras argued that pairing its decode systems with already-installed GPUs could materially improve the productivity and useful life of older hardware. If merchant clouds adopt such configurations, they could re-monetize existing GPU fleets and reduce near-term obsolescence. However, Cerebras acknowledged that it has not yet implemented the approach with NVIDIA GPUs, making this an option rather than a validated offset. The near-term catalyst is continued evidence of high utilization and compute scarcity. The longer-term catalyst is Cerebras’ transition from rented systems to owned capacity, which management expects to begin improving gross margin materially in Q4 2026. A successful owned-capacity ramp would provide evidence that vertically integrated inference clouds can achieve structurally superior economics. The most important comparative metrics will be revenue per megawatt, gross profit per megawatt, capital expenditure per token, utilization, and lease-adjusted free cash flow. CYBERSECURITY LOW-LATENCY LLM INSPECTION COULD CREATE A NEW INLINE SECURITY CATEGORY AND A DIFFERENTIATED ADVANTAGE FOR CROWDSTRIKE (READ-THROUGH 10) AFFECTED COMPANIES: CrowdStrike Holdings Inc. (CRWD: US); Palo Alto Networks Inc. (PANW: US); Zscaler Inc. (ZS: US); Cloudflare Inc. (NET: US). DIRECTIONAL IMPACT AND MAGNITUDE: Positive and medium strategically for CrowdStrike; negative and low-to-medium competitively for Palo Alto Networks, Zscaler, and Cloudflare if they cannot offer comparable low-latency AI inspection. Near-term financial impact is low because no deployment scale or revenue contribution was disclosed. Cerebras announced a new agreement with CrowdStrike and described the use case as an application “that only exists if AI is fast.” Management argued that sufficiently fast inference allows an LLM-based security system to sit inline with enterprise traffic and inspect activity without creating a perceptible delay or disruption. The significance is that latency determines whether generative AI can be used as an active control-plane technology rather than an offline analytical tool. Traditional AI security use cases often analyze events after collection, prioritize alerts, or assist investigators. Inline LLM inference could interpret traffic, user actions, code, content, and context before allowing an interaction to proceed. For CrowdStrike, this could expand the addressable market from endpoint detection and post-event analysis toward real-time inspection and policy enforcement. It could support premium modules, higher platform attachment, improved detection efficacy, and greater strategic relevance within enterprise security architectures. The application also aligns with CrowdStrike’s broad platform strategy because low-latency model inference could be integrated across endpoint, identity, cloud, and data-protection workflows. The competitive implication is that Palo Alto Networks, Zscaler, and Cloudflare may need comparable low-latency inference capabilities to prevent feature differentiation from shifting toward CrowdStrike. The requirement could raise research and development spending and inference cost of revenue. Vendors unable to deliver model-driven inspection without adding latency could be disadvantaged in security-sensitive network paths. The principal limitation is that the call did not disclose whether the CrowdStrike relationship is in development, limited deployment, or broad production. It also did not provide contract value, customer adoption, or product-launch timing. The near-term stock impact should therefore remain modest. The longer-duration opportunity is substantial if inline AI security becomes standard. Every inspected request or session could generate recurring inference demand, creating a high-frequency workload with far greater compute intensity than periodic security analytics. This would be positive not only for CrowdStrike but also for the broader inference infrastructure ecosystem. APPLICATION SOFTWARE AND ENTERPRISE AI FAST INFERENCE IS BECOMING A PRODUCT-LEVEL DIFFERENTIATOR IN CODING AND AGENTIC WORKFLOWS, BUT IT ALSO MOVES AI COSTS INTO SOFTWARE GROSS MARGINS (READ-THROUGH 11) AFFECTED COMPANIES: Figma Inc. (FIG: US); Block Inc. (XYZ: US); GSK plc (GSK: UK). DIRECTIONAL IMPACT AND MAGNITUDE: Strategically positive and medium for product engagement, automation, and competitive differentiation; neutral-to-negative for near-term software gross margins unless customers successfully monetize the additional inference expense. Cerebras stated that it signed 6 Q2 transactions exceeding $30 million. New customer agreements included Figma, Cognition, Lovable, Block, AlphaSense, GSK, and CrowdStrike. Management described coding as a market in which customers are particularly unwilling to tolerate slow output and argued that the value of speed compounds as agentic systems evolve toward multi-step and multi-agent workflows. The read-through is that latency is becoming an application feature rather than an invisible infrastructure metric. In a single-response chatbot, a modest delay may be tolerable. In coding, design, research, automation, or multi-agent workflows, every model interaction can create a sequential dependency. A delay repeated across dozens or hundreds of tool calls can materially extend task-completion time. For Figma, faster inference can improve interactive design generation, iteration, and developer workflows. For Block, it can improve internal automation, coding productivity, customer support, risk operations, or commerce-related agents. For GSK, it can accelerate research, analytical, and enterprise-agent workflows. The specific production applications and financial contribution were not disclosed, so the impact should be viewed as strategic rather than forecastable. The positive transmission mechanism is higher user engagement, faster task completion, greater product utility, and potentially improved conversion or pricing power. The negative transmission mechanism is higher inference cost. Premium low-latency tokens can become a recurring cost of revenue rather than a temporary research expense. Software companies must therefore monetize faster AI through higher prices, greater retention, lower labor expense, or increased transaction volume. The broader software implication is that AI gross-margin exposure will vary materially by workload architecture. Companies operating asynchronous or batch applications may optimize primarily for cost. Companies operating interactive coding, design, security, and agentic products may rationally pay a premium for latency. This creates a segmented inference market rather than a single commoditized token market. The near-term catalyst is disclosure of product launches or usage growth tied to the Cerebras agreements. The longer-duration shift is the movement of inference performance into customer-facing software differentiation. Vendors that integrate speed into product design and monetization should be better positioned than vendors treating model access as an interchangeable commodity. SOURCE MATERIAL