With AMD having attaining more than 40 percent revenue share and more than 27 percent shipment share in the X86 server CPU market in the first half of 2025, that means two things. …
Intel’s “Clearwater Forest” Xeon 7 E-Core CPU Will Be A Beast was written by Timothy Prickett Morgan at The Next Platform.
Large Language Models (LLMs) are rapidly evolving from impressive information retrieval tools into active, intelligent agents. The key to unlocking this transformation is the Model Context Protocol (MCP), an open-source standard that allows LLMs to securely connect to and interact with any application — from Slack to Canva, to your own internal databases.
This is a massive leap forward. With MCP, an LLM client like Gemini, Claude, or ChatGPT can answer more than just "tell me about Slack." You can ask it: "What were the most critical engineering P0s in Jira from last week, and what is the current sentiment in the #engineering-support Slack channel regarding them? Then propose updates and bug fixes to merge."
This is the power of MCP: turning models into teammates.
But this great power comes with proportional risk. Connecting LLMs to your most critical applications creates a new, complex, and largely unprotected attack surface. Today, we change that. We’re excited to announce Cloudflare MCP Server Portals are now available in Open Beta. MCP Server Portals are a new capability that enable you to centralize, secure, and observe every MCP connection in your organization. Continue reading
The availability of SaaS and Gen AI applications is transforming how businesses operate, boosting collaboration and productivity across teams. However, with increased productivity comes increased risk, as employees turn to unapproved SaaS and Gen AI applications, often dumping sensitive data into them for quick productivity wins.
The prevalence of “Shadow IT” and “Shadow AI” creates multiple problems for security, IT, GRC and legal teams. For example:
Gen AI applications may train their models on user inputs, which could expose proprietary corporate information to third parties, competitors, or even through clever attacks like prompt injection.
Applications may retain user data for long periods, share data with third parties, have lax security practices, suffer a data breach, or even go bankrupt, leaving sensitive data exposed to the highest bidder.
Gen AI applications may produce outputs that are biased, unsafe or incorrect, leading to compliance violations or bad business decisions.
In spite of these problems, blanket bans of Gen AI don't work. They stifle innovation and push employee usage underground. Instead, organizations need smarter controls.
Security, IT, legal and GRC teams therefore face a difficult challenge: how can you appropriately assess each third-party application, without Continue reading
Starting today, all users of Cloudflare One, our secure access service edge (SASE) platform, can use our API-based Cloud Access Security Broker (CASB) to assess the security posture of their generative AI (GenAI) tools: specifically, OpenAI’s ChatGPT, Claude by Anthropic, and Google’s Gemini. Organizations can connect their GenAI accounts and within minutes, start detecting misconfigurations, Data Loss Prevention (DLP) matches, data exposure and sharing, compliance risks, and more — all without having to install cumbersome software onto user devices.
As Generative AI adoption has exploded in the enterprise, IT and Security teams need to hustle to keep themselves abreast of newly emerging security and compliance challenges that come alongside these powerful tools. In this rapidly changing landscape, IT and Security teams need tools that help enable AI adoption while still protecting the security and privacy of their enterprise networks and data.
Cloudflare’s API CASB and inline CASB work together to help organizations safely adopt AI tools. The API CASB integrations provide out-of-band visibility into data at rest and security posture inside popular AI tools like ChatGPT, Claude, and Gemini. At the same time, Cloudflare Gateway provides in-line prompt controls and Shadow AI identification. It applies policies and Continue reading
Security teams are racing to secure a new attack surface: AI-powered applications. From chatbots to search assistants, LLMs are already shaping customer experience, but they also open the door to new risks. A single malicious prompt can exfiltrate sensitive data, poison a model, or inject toxic content into customer-facing interactions, undermining user trust. Without guardrails, even the best-trained model can be turned against the business.
Today, as part of AI Week, we’re expanding our AI security offerings by introducing unsafe content moderation, now integrated directly into Cloudflare Firewall for AI. Built with Llama, this new feature allows customers to leverage their existing Firewall for AI engine for unified detection, analytics, and topic enforcement, providing real-time protection for Large Language Models (LLMs) at the network level. Now with just a few clicks, security and application teams can detect and block harmful prompts or topics at the edge — eliminating the need to modify application code or infrastructure. This feature is immediately available to current Firewall for AI users. Those not yet onboarded can contact their account team to participate in the beta program.
Cloudflare's Firewall for AI protects user-facing LLM applications from abuse and Continue reading
As Generative AI revolutionizes businesses everywhere, security and IT leaders find themselves in a tough spot. Executives are mandating speedy adoption of Generative AI tools to drive efficiency and stay abreast of competitors. Meanwhile, IT and Security teams must rapidly develop an AI Security Strategy, even before the organization really understands exactly how it plans to adopt and deploy Generative AI.
IT and Security teams are no strangers to “building the airplane while it is in flight”. But this moment comes with new and complex security challenges. There is an explosion in new AI capabilities adopted by employees across all business functions — both sanctioned and unsanctioned. AI Agents are ingesting authentication credentials and autonomously interacting with sensitive corporate resources. Sensitive data is being shared with AI tools, even as security and compliance frameworks struggle to keep up.
While it demands strategic thinking from Security and IT leaders, the problem of governing the use of AI internally is far from insurmountable. SASE (Secure Access Service Edge) is a popular cloud-based network architecture that combines networking and security functions into a single, integrated service that provides employees with secure and efficient access to the Internet and to corporate resources, regardless Continue reading
A netlab user wanted to explore a multi-site design where every site runs an independent EVPN fabric, and the inter-site link is either a layer-2 or a layer-3 interconnect (DCI). Let’s start with the easiest scenario: a layer-3 DCI with a separate (virtual) link for every tenant (in the MPLS/VPN world, we’d call that Inter-AS Option A)
As Kubernetes adoption scales across enterprise architectures, platform architects face mounting pressure to implement consistent security guardrails across distributed, multi-cluster environments while maintaining operational velocity. Modern infrastructure demands a security architecture that can adapt without introducing complexity or performance penalties. Traditional approaches force architects to cobble together separate solutions for ingress protection, network policies, and application-layer security, creating operational friction and increasing attack surface.
Today, we’re announcing significant enhancements to Calico that eliminate this architectural complexity. This release introduces native Web Application Firewall (WAF) capabilities integrated directly into Calico’s Ingress Gateway, enabling platform architects to deploy a single technology stack for both ingress management and HTTP-layer threat protection. Combined with enhanced Role-Based Access Controls (RBAC) controls, and centralized observability across heterogeneous workloads, platform architects can now design and implement comprehensive security all within a unified platform.
The new features in this release can be grouped under two main categories:
Just because the center of gravity for GenAI compute and other kinds of machine learning and data analytics has shifted from the CPU to the XPU accelerator – generally a GPU these days, but not universally – does not mean that the choice of the CPU for the system hosting those XPUs doesn’t matter. …
NeuReality Wants Its NR2 To Be Your Arm CPU For AI was written by Timothy Prickett Morgan at The Next Platform.
The digital landscape of corporate environments has always been a battleground between efficiency and security. For years, this played out in the form of "Shadow IT" — employees using unsanctioned laptops or cloud services to get their jobs done faster. Security teams became masters at hunting these rogue systems, setting up firewalls and policies to bring order to the chaos.
But the new frontier is different, and arguably far more subtle and dangerous.
Imagine a team of engineers, deep into the development of a groundbreaking new product. They're on a tight deadline, and a junior engineer, trying to optimize his workflow, pastes a snippet of a proprietary algorithm into a popular public AI chatbot, asking it to refactor the code for better performance. The tool quickly returns the revised code, and the engineer, pleased with the result, checks it in. What they don't realize is that their query, and the snippet of code, is now part of the AI service’s training data, or perhaps logged and stored by the provider. Without anyone noticing, a critical piece of the company's intellectual property has just been sent outside the organization's control, a silent and unmonitored data leak.
This isn't a Continue reading
If you’re here on the Cloudflare blog, chances are you already understand AI pretty well. But step outside our circle, and you’ll find a surprising number of people who still don’t know what it really is — or why it matters.
We wanted to come up with a way to make AI intuitive, something you can actually see and touch to get what’s going on. Hands on, not just hand-wavy.
The idea we landed on is simple: nothing comes into the world fully formed. Like us, and like the Internet, AI didn’t show up fully formed. So we asked ourselves: what if we told the story of AI as it learns and grows?
Episode by episode, we’d give it new capabilities, explain how those capabilities work, and explore how they change the way AI interacts with the world. Giving it a voice. Letting it see. Helping it learn. And maybe even letting it imagine the future.
So we made AI Avenue, a show where I (Craig) explore the fun, human, and sometimes surprising sides of AI… with a little help from my co-host Yorick, a robot hand with a knack for comic timing and the occasional eye-roll. Together, we travel, Continue reading
The revolution is already inside your organization, and it's happening at the speed of a keystroke. Every day, employees turn to generative artificial intelligence (GenAI) for help with everything from drafting emails to debugging code. And while using GenAI boosts productivity—a win for the organization—this also creates a significant data security risk: employees may potentially share sensitive information with a third party.
Regardless of this risk, the data is clear: employees already treat these AI tools like a trusted colleague. In fact, one study found that nearly half of all employees surveyed admitted to entering confidential company information into publicly available GenAI tools. Unfortunately, the risk for human error doesn’t stop there. Earlier this year, a new feature in a leading LLM meant to make conversations shareable had a serious unintended consequence: it led to thousands of private chats — including work-related ones — being indexed by Google and other search engines. In both cases, neither example was done with malice. Instead, they were miscalculations on how these tools would be used, and it certainly did not help that organizations did not have the right tools to protect their data.
While the instinct for many may be to deploy Continue reading
A networking engineer (let’s call him Joe1) sent me an interesting challenge: they built a data center network with Cisco switches, and the switches flood LLDP packets between servers.
That would be interesting by itself (the whole network would appear as a single hub), but they’re also using DCBX (which is riding in LLDP TLVs), and the DCBX parameters are negotiated between servers (not between servers and adjacent switches), sometimes resulting in NIC resets2.
We are witnessing in real time as AI fundamentally changes how people work across every industry. Customer support agents can respond to ten times the tickets. Software engineers are reviewers of AI generated code instead of spending hours pounding out boiler plate code. Salespeople can get back to focusing on building relationships instead of tedious follow up and administration.
This technology feels magical, and Cloudflare is committed to helping companies build world class AI-driven experiences for their employees and customers.
There is a but, however. Any time a brand new technology with such widespread appeal emerges, the technology often outpaces the tools in place to govern, secure and control the technology. We're already starting to see stories of vibe coded apps leaking all their users' details. LLM chats that were intended to only be shared between colleagues, are actually out on the web, being indexed by search engines for all the world to see. AI Agents are being given the keys to the application kingdom, enabling them to work autonomously across an organization — but without proper tracking and control. And then there’s the risk of a well-meaning employee uploading confidential company or customer data into an LLM, which Continue reading
Recently, I was doing some reading on MPLS and wanted to build a lab for it. For my use case, I needed five routers connected and running OSPF between them before I could even start configuring MPLS. So before doing any MPLS work, I have to spend a lot of time setting up the lab and prerequisites like configuring IP addresses on interfaces and setting up OSPF. This is tedious, and this is exactly where Netlab can help you get up to speed.
Netlab is an open source tool that makes it easy to build and share network labs. Instead of manually dragging devices in a GUI or typing the same base configs over and over, you describe your lab in a simple YAML file. Netlab then takes care of creating the topology, assigning IP addresses, configuring routing protocols, and even pushing custom configs. Netlab works with containerlab (or vagrant) so you can spin up realistic network topologies in minutes and reproduce them anywhere automagically.
As Network Engineers, we often set up labs to help us learn and practice. Most of us use tools like EVE-NG, GNS3, or Cisco CML, where you go into Continue reading
It has been clear for some time that Japan wants to have a certain amount of economic and technical independence when it comes to cloud computing in the Land of the Rising Sun. …
Nvidia Tapped To Accelerate RIKEN’s FugakuNext Supercomputer was written by Timothy Prickett Morgan at The Next Platform.
For over two decades, we've built real-time communication on the Internet using a patchwork of specialized tools. RTMP gave us ingest. HLS and DASH gave us scale. WebRTC gave us interactivity. Each solved a specific problem for its time, and together they power the global streaming ecosystem we rely on today.
But using them together in 2025 feels like building a modern application with tools from different eras. The seams are starting to show—in complexity, in latency, and in the flexibility needed for the next generation of applications, from sub-second live auctions to massive interactive events. We're often forced to make painful trade-offs between latency, scale, and operational complexity.
Today Cloudflare is launching the first Media over QUIC (MoQ) relay network, running on every Cloudflare server in datacenters in 330+ cities. MoQ is an open protocol being developed at the IETF by engineers from across the industry—not a proprietary Cloudflare technology. MoQ combines the low-latency interactivity of WebRTC, the scalability of HLS/DASH, and the simplicity of a single architecture, all built on a modern transport layer. We're joining Meta, Google, Cisco, and others in building implementations that work seamlessly together, creating a shared foundation for the next generation of real-time Continue reading
From time to time, I like to dive into the archive and find a show that’s worth repeating. Forthwith, Derrick Winkworth and automation.
Network automation efforts tend to focus on building and maintaining configurations–but is this the right place to be putting our automation efforts? Derick Winkworth joins Tom Ammon and Russ White at the Hedge for a conversation about what engineers really do, and what this means for automation.
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When I was cleaning the “set BGP MED” integration test, I decided that once a BGP prefix is in the BGP table of the BGP peer, there’s no need for a further wait before checking its MED value. After all:
That approach failed miserably with ArubaCX; it was time to investigate the details.