A quick public service announcement for anyone implementing BGP-LU or deploying it in a multivendor environment.
Originally, BGP was designed to advertise IP prefixes. Then [RFC2283] (obsoleted by [RFC4760]) defined Multiprotocol …
In late November 2024, Anthropic announced a new way to interact with AI, called Model Context Protocol (MCP). Today, we’re excited to show you how to use MCP in combination with Cloudflare to extend the capabilities of Claude to build applications, generate images and more. You’ll learn how to build an MCP server on Cloudflare to make any service accessible through an AI assistant like Claude with just a few lines of code using Cloudflare Workers.
MCP is an open standard that provides a universal way for LLMs to interact with services and applications. As the introduction on the MCP website puts it,
“Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.”
From an architectural perspective, MCP is comprised of several components:
MCP hosts: Programs or tools (like Claude) where AI models operate and interact with different services
MCP clients: Client within an AI assistant that initiates requests and communicates with MCP servers to Continue reading
OpenAI announced support for WebRTC in their Realtime API on December 17, 2024. Combining their Realtime API with Cloudflare Calls allows you to build experiences that weren’t possible just a few days earlier.
Previously, interactions with audio and video AIs were largely single-player: only one person could be interacting with the AI unless you were in the same physical room. Now, applications built using Cloudflare Calls and OpenAI’s Realtime API can now support multiple users across the globe simultaneously seeing and interacting with a voice or video AI.
Here’s what this means in practice: you can now invite ChatGPT to your next video meeting:
We built this into our Orange Meets demo app to serve as an inspiration for what is possible, but the opportunities are much broader.
In the not-too-distant future, every company could have a 'corporate AI' they invite to their internal meetings that is secure, private and has access to their company data. Imagine this sort of real-time audio and video interactions with your company’s AI:
"Hey ChatGPT, do we have any open Jira tickets about this?"
"Hey Company AI, who are the competitors in the space doing Continue reading
When I went of in search of warmer climates in Australia I moored up at the Aylesbury Canal Society on the Grand Union’s Aylesbury arm. As fortune dictated the weekend before I got back a lock on the arm collapsed meaning I was going to be stuck there for sometime so decided to be productive and try and finish off the interior of the boat.
Hello my friend,
So far we have covered almost all possible data types in Python and Go (Golang), at least the ones we are going to use ourselves for network automation. One of these data types, which we have introduced in the previous blog post, that is object/class or struct, has without overestimations enormous importance as it opens for us doors into object oriented programming. As doors are opened, let’s enter them.
Meaning, apart of spending time your family and friends, cooking, eating and dancing, you also study network automation with our trainings!
We offer the following training programs in network automation for you:
During these trainings you will learn the following topics:
Phishing remains one of the most dangerous and persistent cyber threats for individuals and organizations. Modern attacks use a growing arsenal of deceptive techniques that bypass traditional secure email gateways (SEGs) and email authentication measures, targeting organizations, employees, and vendors. From business email compromise (BEC) to QR phishing and account takeovers, these threats are designed to exploit weaknesses across multiple communication channels, including email, Slack, Teams, SMS, and cloud drives.
Phishing remains the most popular attack vector for bad actors looking to gain unauthorized access or extract fraudulent payment, and it is estimated that 90% of all attacks start with a phishing email. However, as companies have shifted to using a multitude of apps to support communication and collaboration, attackers too have evolved their approach. Attackers now engage employees across a combination of channels in an attempt to build trust and pivot targeted users to less-secure apps and devices. Cloudflare is uniquely positioned to address this trend thanks to our integrated Zero Trust services, extensive visibility from protecting approximately 20% of all websites, and signals derived from processing billions of email messages a year.
Cloudflare recognizes that combating phishing requires an integrated approach and a more complete view Continue reading
In Kubernetes, pods often need to securely communicate with external resources, such as internet services or APIs. Traditional Kubernetes network policies use IP addresses to identify these external resources. However, managing policies with IP addresses can be challenging because IPs often change, especially when dealing with dynamic websites or APIs.
Calico Enterprise addresses this challenge by extending Kubernetes network policies to support Fully Qualified Domain Names (FQDNs). This allows users to define policies using domain names instead of IP addresses, making it easier to manage and secure egress traffic. By dynamically mapping domain names to IPs, Calico ensures that policies remain up-to-date, enabling seamless and secure connectivity to external resources.
While this approach is conceptually simple, practical implementation is tricky. DNS mappings are dynamic: domain names often resolve to different IPs with each query, and wildcard support (e.g., *.example.com
) adds complexity. To address this, Calico monitors DNS traffic to create and manage domain-to-IP mappings dynamically, translating high-level DNS-based rules into efficient low-level constructs like iptables
, nftables
, or eBPF.
The DNS policy implementation significantly impacts performance and reliability. Currently, Calico offers three different modes to operate the DNS Continue reading
This is the second blog post in a series exploring how Kubernetes, despite its inherent complexity, provides features that simplify security efforts.
Kubernetes presents an interesting paradox: while it is complex, it simplifies many aspects of deploying and managing containerized applications, including configuration security. Once you navigate its learning curve, Kubernetes unlocks powerful capabilities and tool support that make managing configuration security significantly easier.
In this blog post, we’ll dive into how Kubernetes enhances configuration security and outline its key advantages.
Despite its complexity, Kubernetes offers a range of features that simplify configuration security. These include enhanced visibility, streamlined access to log data, robust RBAC (Role-Based Access Control) capabilities, security policy as code, a layered network policy model, and more. Many of these capabilities also improve the efficiency and effectiveness of mitigation and remediation workflows for configuration security. Below, we highlight key features that should be considered when developing a configuration security strategy.
Maintaining a complete inventory of workloads can be challenging in non-Kubernetes environments. However, Kubernetes provides complete visibility into every containerized workload running in the system. This eliminates concerns about shadow systems or overlooked resources that could Continue reading
Cloudflare Radar celebrated its fourth birthday in September 2024. As we’ve expanded Radar’s scope over the last four years, the value that it provides as a resource for the global Internet has grown over time, and with Radar data and graphs often appearing in publications and social media around the world, we knew that we needed to make it available in languages beyond English.
Localization is important because most Internet users do not speak English as a first language. According to W3Techs, English usage on the Internet has dropped 8.3 points (57.7% to 49.4%) since January 2023, whereas usage of other languages like Spanish, German, Japanese, Italian, Portuguese and Dutch is steadily increasing. Furthermore, a CSA Research study determined that 65% of Internet users prefer content in their language.
To successfully (and painlessly) localize any product, it must be internationalized first. Internationalization is the process of making a product ready to be translated and adapted into multiple languages and cultures, and it sets the foundation to enable your product to be localized later on at a much faster pace (and at a lower cost, both in time and budget). Below, we review how Cloudflare’s Radar Continue reading
Another year is almost gone, and it’s time for my traditional “I will disappear until mid-January” retreat (also, don’t expect me to read my email until I’m back).
I hope you’ll also be able to disconnect from the crazy pace of the networking world, forget the “AI will make networking engineers obsolete” shenanigans (hint: SDN did not), and focus on your loved ones. I would also like to wish you all the best in 2025!
I will probably get bored sometime in late December, so expect a few new netlab features in early January.
So far, this book has introduced two neural network architectures. The first one, the Feed-Forward Neural Network (FNN), works well for simple tasks, such as recognizing handwritten digits in small-sized images. The second one, the Convolutional Neural Network (CNN), is designed for processing larger images. CNNs can identify objects in images even when the location or orientation of the object changes.
This chapter introduces the Recurrent Neural Network (RNN). Unlike FNNs and CNNs, an RNN’s inputs include not only the current data but also all the inputs it has processed previously. In other words, an RNN preserves and uses historical data. This is achieved by feeding the output of the previous time step back into the hidden layer along with the current input vector.
Although RNNs can be used for predicting sequential data of variable lengths, such as sales figures or a patient’s historical health records, this chapter focuses on how RNNs can perform character-based text autocompletion. The upcoming chapters will explore word-based text prediction.
For training the RNN model, we typically use text datasets like IMDB Reviews or the Wikipedia Text Corpus. However, in this chapter, we simplify the process by using a tailored dataset containing Continue reading