Cloudflare One has grown a lot over the years. What started with securing traffic at the network now spans the endpoint and SaaS applications – because that’s where work happens.
But as the market has evolved, the core mission has become clear: data security is enterprise security.
Here’s why. We don’t enforce controls just to enforce controls. We do it because the downstream outcomes are costly: malware, credential theft, session hijacking, and eventually the thing that matters most: sensitive data leaving the organization. What looks like a simple access policy can be the first link in a chain that ends in incident response, customer impact, and reputational damage.
So when you take a step back, most security programs – even the ones that look different on paper – are trying to answer the same questions:
Where is sensitive data?
Who can access it?
What paths exist for it to move somewhere it shouldn’t?
That’s the backbone of our data security vision in Cloudflare One: a single model that follows data across the places it moves, not a pile of siloed controls. That means:
Protection in transit (across Internet + SaaS access)
Visibility and control at rest (inside SaaS)
Enforcement Continue reading
It’s 2026, and it’s time for a new cellular telephone hype cycle: 6G! Doug Dawson from CCG joins Russ and Tom to talk about why 5G is really 4.5G, the proposed changes for 6G, and the challenges higher frequency ranges and bandwidths face in the real world.
It’s definitely worth following Doug’s daily post about the telecom and wireless worlds over at Pots and Pans.
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Akvorado, a network flow collector, relies on Traefik, a reverse HTTP proxy, to expose HTTP endpoints for services implemented in a Docker Compose setup. Docker labels attached to each service define the routing rules. Traefik picks them up automatically when a container starts. Instead of maintaining a static configuration file to collect Prometheus metrics, we can apply the same approach with Grafana Alloy, making its configuration simpler.
Traefik listens for events on the Docker socket. Each service advertises its configuration through labels. For example, here is the Loki service in Akvorado:
services: loki: # … expose: - 3100/tcp labels: - traefik.enable=true - traefik.http.routers.loki.rule=PathPrefix(`/loki`)
Once the container is healthy, Traefik creates a router forwarding requests
matching /loki to its first exposed port. Colocating Traefik configuration
with the service definition is attractive. How do we achieve the same for
Prometheus metrics?
Grafana Alloy, a metrics collector that can scrape Prometheus endpoints,
includes a discovery.docker component. Just like Traefik,
it connects to the Docker Continue reading
Last Updated: 2026-03-05 When I see spreadsheets like this I want to cry and tear my hair out. What if I want to select a subset? (Hide the other rows, seriously?). What does the color coding mean???? A Visceral Response It took me a while to understand why seeing something like this made my skin READ MORE
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You’ve likely seen this support ticket countless times: a user’s Internet connection that worked just fine a moment ago for Slack and DNS lookups is suddenly hung the moment they attempt a large file upload, join a video call, or initiate an SSH session. The culprit isn't usually a bandwidth shortage or service outage issue, it is the "PMTUD Black Hole" — a frustration that occurs when packets are too large for a specific network path, but the network fails to communicate that limit back to the sender. This situation often happens when you’re locked into using networks you do not manage or vendors with maximum transmission unit (MTU) restrictions, and you have no means to address the problem.
Today, we are moving past these legacy networking constraints. By implementing Path MTU Discovery (PMTUD), the Cloudflare One Client has shifted from a passive observer to an active participant in path discovery.
Dynamic Path MTU Discovery allows the client to intelligently and dynamically adjust to the optimal packet size for most network paths using MTUs above 1281 bytes. This ensures that a user’s connection remains stable, whether they are on a high-speed corporate backbone or a restrictive cellular network.
Yesterday, I had a short presentation on netlab use cases during the NetBCN event. It covered a dozen examples, from rapid prototyping to testing network automation software and arguing with vendor TAC. I added the “use cases” part of the presentation to the standard netlab presentation; you can view the results on ipSpace.net (no account or registration required).
When you need to use a proxy to keep your zero trust environment secure, it often comes with a cost: poor performance for your users. Soon after deploying a client proxy, security teams are generally slammed with support tickets from users frustrated with sluggish browser speed, slow file transfers, and video calls glitching at just the wrong moment. After a while, you start to chalk it up to the proxy — potentially blinding yourself to other issues affecting performance.
We knew it didn’t have to be this way. We knew users could go faster, without sacrificing security, if we completely re-built our approach to proxy mode. So we did.
In the early days of developing the device client for our SASE platform, Cloudflare One, we prioritized universal compatibility. When an admin enabled proxy mode, the Client acted as a local SOCKS5 or HTTP proxy. However, because our underlying tunnel architecture was built on WireGuard, a Layer 3 (L3) protocol, we faced a technical hurdle: how to get application-layer (L4) TCP traffic into an L3 tunnel. Moving from L4 to L3 was especially difficult because our desktop Client works across multiple platforms (Windows, macOS, Linux) so we couldn’t use Continue reading
The public Internet relies on a fundamental principle of predictable routing: a single IP address points to a logically unique destination. Even in an Anycast architecture like Cloudflare’s, where one IP is announced from hundreds of locations, every instance of that IP represents the same service. The routing table always knows exactly where a packet is intended to go.
This principle holds up because global addressing authorities assign IP space to organizations to prevent duplication or conflict. When everyone adheres to a single, authoritative registry, a routing table functions as a source of absolute truth.
On the public Internet, an IP address is like a unique, globally registered national identity card. In private networks, an IP is just a name like “John Smith”, which is perfectly fine until you have three of them in the same room trying to talk to the same person.
As we expand Cloudflare One to become the connectivity cloud for enterprise backbones, we’ve entered the messy reality of private IP address space. There are good reasons why duplication arises, and enterprises need solutions to handle these conflicts.
Today, we are introducing Automatic Return Routing (ARR) in Closed Beta. ARR is an optional tool for Continue reading
When I first started learning Kubernetes, I had the idea that observing the network traffic between a client system using kubectl and the Kubernetes API Server would be a useful thing to do. The source of the idea is unclear; I am unsure why I thought this would be useful as a learning tool. Regardless, I continued on with learning Kubernetes and never really pursued this idea—until this week. I found it can be a useful troubleshooting technique, but I will leave it up to you to determine if it is a useful learning technique. In this post, I will show you how to observe kubectl traffic using mitmproxy.
This technique is inspired by/informed by Ahmet Alp Balkan’s similarly-named blog post from 2019. Unfortunately, I found the instructions there to be incomplete (most likely just due to the passage of time and continued evolution of the tools involved).
I used the following tools and environments in my testing:
apt.kubectl version 1.33.3 was used to communicate to a self-managed cluster Continue readingAI Powered Intelligence, Unified Traffic Observability and Scalable Infrastructure Management
As anyone managing one or more Kubernetes clusters knows by now, scaling can introduce an exponentially growing number of problems. The sheer volume of metrics, logs and other data can become an obstacle, rather than an asset, to effective troubleshooting and overall cluster management. Fragmented tools and manual troubleshooting processes introduce operational complexity leading to the inevitable security gaps and extended downtime. As the number of clusters grows it becomes more important than ever to find ways of reducing the observability noise, decluttering the monitoring stack and eliminating the bottlenecks that get in the way of keeping your clusters stable and secure.
The Winter 2026 release of Calico Enterprise and Calico Cloud addresses the pain points of scaling clusters with three key enhancements:
AI Assistant for Calico: Efficiently navigate disparate data sources to quickly get answers through natural language, or proactively identify problems before they arise.
Traditional Web Application Firewalls typically require extensive, manual tuning of their rules before they can safely block malicious traffic. When a new application is deployed, security teams usually begin in a logging-only mode, sifting through logs to gradually assess which rules are safe for blocking mode. This process is designed to minimize false positives without affecting legitimate traffic. It’s manual, slow and error-prone.
Teams are forced into a trade-off: visibility in log mode, or protection in block mode. When a rule blocks a request, evaluation stops, and you lose visibility into how other signatures would have assessed it — valuable insight that could have helped you tune and strengthen your defenses.
Today, we’re solving this by introducing the next evolution of our managed rules: Attack Signature Detection.
When enabled, this detection inspects every request for malicious payloads and attaches rich detection metadata before any action is taken. You get complete visibility into every signature match, without sacrificing protection or performance. Onboarding becomes simple: traffic is analyzed, data accumulates, and you see exactly which signatures fire and why. You can then build precise mitigation policies based on past traffic, reducing the risk of false positives.
But we’re going one step further. Continue reading
One of our favorite ask-me-anything questions for company meetings or panels at security conferences is the classic: “What keeps you up at night?”
For a CISO, that question is maybe a bit of a nightmare in itself. It does not have one single answer; it has dozens. It’s the constant tension between enabling a globally distributed workforce to do their best work, and ensuring that "best work" does not inadvertently open the door to a catastrophic breach.
We often talk about the "zero trust journey," but the reality is that the journey is almost certainly paved with friction. If security is too cumbersome, users find creative (and dangerous) ways around it. If it’s seamless at the cost of effectiveness, it might not be secure enough to stop a determined adversary.
Today, we are excited to announce two new tools in Cloudflare’s SASE toolbox designed to modernize remote access by eliminating the "dark corners" of your network security without adding friction to the user experience: mandatory authentication and Cloudflare’s own multi-factor authentication (MFA).
When you deploy the Cloudflare One Client, you gain incredible visibility and control. You can apply Continue reading