Automate IP, VLAN & BGP Resource Allocation With Infrahub Resource Manager

Automate IP, VLAN & BGP Resource Allocation With Infrahub Resource Manager

Have you ever had two teams accidentally assign the same IP address? Or heard someone ask, “Can I get a VLAN? I’m not sure which one to use.” I’m also certain you have because manually managing infrastructure resources like IP addresses, IP prefixes, VLAN IDs, and BGP ASNs is still all too common in a lot of environments. Manual resource management is also time-consuming and painful, and often results in duplicate resource assignments, which means more work to clean things up later.

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The Infrahub Resource Manager is designed to eliminate those pains while speeding up your workflows. The Resource Manager automatically hands out resources from managed pools and ensures every allocation is tracked and unique.

Automate IP, VLAN & BGP Resource Allocation With Infrahub Resource Manager

In this guide, we’ll show you how the Infrahub Resource Manager works and give you three ways to build pools and allocate resources with it.


Common use cases for the Infrahub Resource Manager

The Resource Manager can be used in many areas of network design and automation. A common use case is data center expansion Continue reading

Automating threat analysis and response with Cloudy

Security professionals everywhere face a paradox: while more data provides the visibility needed to catch threats, it also makes it harder for humans to process it all and find what's important. When there’s a sudden spike in suspicious traffic, every second counts. But for many security teams — especially lean ones — it’s hard to quickly figure out what’s going on. Finding a root cause means diving into dashboards, filtering logs, and cross-referencing threat feeds. All the data tracking that has happened can be the very thing that slows you down — or worse yet, what buries the threat that you’re looking for. 

Today, we’re excited to announce that we’ve solved that problem. We’ve integrated Cloudy — Cloudflare’s first AI agent — with our security analytics functionality, and we’ve also built a new, conversational interface that Cloudflare users can use to ask questions, refine investigations, and get answers.  With these changes, Cloudy can now help Cloudflare users find the needle in the digital haystack, making security analysis faster and more accessible than ever before.  

Since Cloudly’s launch in March of this year, its adoption has been exciting to watch. Over 54,000 users have tried Cloudy for custom Continue reading

Cloudy Summarizations of Email Detections: Beta Announcement

Background

Organizations face continuous threats from phishing, business email compromise (BEC), and other advanced email attacks. Attackers adapt their tactics daily, forcing defenders to move just as quickly to keep inboxes safe.

Cloudflare’s visibility across a large portion of the Internet gives us an unparalleled view of malicious campaigns. We process billions of email threat signals every day, feeding them into multiple AI and machine learning models. This lets our detection team create and deploy new rules at high speed, blocking malicious and unwanted emails before they reach the inbox.

But rapid protection introduces a new challenge: making sure security teams understand exactly what we blocked — and why.

The Challenge

Cloudflare’s fast-moving detection pipeline is one of our greatest strengths — but it also creates a communication gap for customers. Every day, our detection analysts publish new rules to block phishing, BEC, and other unwanted messages. These rules often blend signals from multiple AI and machine learning models, each looking at different aspects of a message like its content, headers, links, attachments, and sender reputation.

While this layered approach catches threats early, SOC teams don’t always have insight into the specific combination of factors that triggered a Continue reading

Cloudflare is the best place to build realtime voice agents

The way we interact with AI is fundamentally changing. While text-based interfaces like ChatGPT have shown us what's possible, in terms of interaction, it’s only the beginning. Humans communicate not only by texting, but also talking — we show things, we interrupt and clarify in real-time. Voice AI brings these natural interaction patterns to our applications.

Today, we're excited to announce new capabilities that make it easier than ever to build real-time, voice-enabled AI applications on Cloudflare's global network. These new features create a complete platform for developers building the next generation of conversational AI experiences or can function as building blocks for more advanced AI agents running across platforms.

We're launching:

  • Cloudflare Realtime Agents - A runtime for orchestrating voice AI pipelines at the edge

  • Pipe raw WebRTC audio as PCM in Workers - You can now connect WebRTC audio directly to your AI models or existing complex media pipelines already built on 

  • Workers AI WebSocket support - Realtime AI inference with models like PipeCat's smart-turn-v2

  • Deepgram on Workers AI - Speech-to-text and text-to-speech running in over 330 cities worldwide

Why realtime AI matters now

Today, building voice AI applications is hard. You need to coordinate multiple services such Continue reading

Troubleshooting network connectivity and performance with Cloudflare AI

Monitoring a corporate network and troubleshooting any performance issues across that network is a hard problem, and it has become increasingly complex over time. Imagine that you’re maintaining a corporate network, and you get the dreaded IT ticket. An executive is having a performance issue with an application, and they want you to look into it. The ticket doesn’t have a lot of details. It simply says: “Our internal documentation is taking forever to load. PLS FIX NOW”.

In the early days of IT, a corporate network was built on-premises. It provided network connectivity between employees that worked in person and a variety of corporate applications that were hosted locally.

The shift to cloud environments, the rise of SaaS applications, and a “work from anywhere” model has made IT environments significantly more complex in the past few years. Today, it’s hard to know if a performance issue is the result of:

  • An employee’s device

  • Their home or corporate wifi

  • The corporate network

  • A cloud network hosting a SaaS app

  • An intermediary ISP

A performance ticket submitted by an employee might even be a combination of multiple performance issues all wrapped together into one nasty problem.

Cloudflare built Cloudflare One, Continue reading

The crawl-to-click gap: Cloudflare data on AI bots, training, and referrals

In 2025, Generative AI is reshaping how people and companies use the Internet. Search engines once drove traffic to content creators through links. Now, AI training crawlers — the engines behind commonly-used LLMs — are consuming vast amounts of web data, while sending far fewer users back. We covered this shift, along with related trends and Cloudflare features (like pay per crawl) in early July. Studies from Pew Research Center (1, 2) and Authoritas already point to AI overviews — Google’s new AI-generated summaries shown at the top of search results — contributing to sharp declines in news website traffic. For a news site, this means lots of bot hits, but far fewer real readers clicking through — which in turn means fewer people clicking on ads or chances to convert to subscriptions.

Cloudflare's data shows the same pattern. Crawling by search engines and AI services surged in the first half of 2025 — up 24% year-over-year in June — before slowing to just 4% year-over-year growth in July. How is the space evolving? Which crawling purposes are most common, and how is that changing? Spoiler: training-related crawling is leading the way. In this post, we track Continue reading

Running Palo Alto Firewalls on Proxmox

Running Palo Alto Firewalls on Proxmox

If you follow me or my blog, you may know that I moved my homelab to Proxmox. Even though I already have a physical Palo Alto firewall, I also needed to set up a Palo Alto VM. After some reading and research, and with the help of a great guide I found, I managed to get Palo Alto running on Proxmox. I thought it would be useful to write a post about it for anyone else trying to do the same.

At a high level, you need to download the Palo Alto QCOW image. I’m using PAN-OS 11.2.5 and downloaded the image called PA-VM-KVM-11.2.5.qcow2. You will also need multiple network interfaces on Proxmox. With Palo Alto, you need at least two to begin with, one for management and one for data.

When I say Proxmox interfaces or NICs, I mean the virtual network adapters that you can assign to your VM. These map to your physical or virtual bridges on the Proxmox host, and they let you connect the firewall VM to different parts of your network.

Running Palo Alto Firewalls on Proxmox
I have two linux bridges

The first step is to copy the Palo Alto QCOW image over to Continue reading

N4N037: IPsec Basics

It’s time to talk crypto. No, not the Bitcoin kind. Ethan and Holly introduce the basics of IPsec, the protocol that authenticates and encrypts traffic between endpoints. They discuss what it is, how it provides trustworthiness and secrecy to IP traffic, and common use cases. They review the different types of IPsec protocols and modes,... Read more »

A deeper look at AI crawlers: breaking down traffic by purpose and industry

Search platforms historically crawled web sites with the implicit promise that, as the sites showed up in the results for relevant searches, they would send traffic on to those sites — in turn leading to ad revenue for the publisher. This model worked fairly well for several decades, with a whole industry emerging around optimizing content for optimal placement in search results. It led to higher click-through rates, more eyeballs for publishers, and, ideally, more ad revenue. However, the emergence of AI platforms over the last several years, and the incorporation of AI "overviews" into classic search platforms, has turned the model on its head. When users turn to these AI platforms with queries that used to go to search engines, they often won't click through to the original source site once an answer is provided — and that assumes that a link to the source is provided at all! No clickthrough, no eyeballs, and no ad revenue. 

To provide a perspective on the scope of this problem, Radar launched crawl/refer ratios on July 1, based on traffic seen across our whole customer base. These ratios effectively compare the number of crawling requests for HTML pages from the crawler Continue reading