This guide helps you to install Pi-hole on your Raspberry Pi 3B running Debian 12, […]
The post Pi-hole on Raspberry Pi 3B with Debian first appeared on Brezular's Blog.
For most of the generative AI revolution thus far, the big original equipment manufacturers, or OEMs, have been sidelined as Nvidia and now AMD have done direct allocations of their GPU compute engines to hyperscalers, cloud builders, and other lighthouse customers. …
How Much Can Dell Profit From The AI Wave? was written by Timothy Prickett Morgan at The Next Platform.
For DevOps and platform teams working with containers and Kubernetes, reducing downtime and improving security posture is crucial. A clear understanding of network topology, service interactions, and workload dependencies is required in cloud-native applications. This is essential for securing and optimizing the Kubernetes deployment and minimizing response time in the event of failure.
Network observability can highlight gaps in network policies for applications that require network policy controls to reduce the risk of attack from unsecured egress access or lateral movement of threats within the Kubernetes cluster. However, visualizing workload communication, service dependencies, and active and inactive network security policies presents significant challenges due to the distributed and dynamic nature of Kubernetes workloads.
Kubernetes scales up and scales out pods and creates and destroys services depending on real-time business requirements, resulting in dynamic network connections for each workload instance. Network access policies defined for each workload further impact these connections.
In such a scenario, capturing an accurate and up-to-date representation of network traffic, service dependencies, and network policies is difficult. The default Kubernetes implementation provides limited network traffic visibility and policy information, making it challenging for teams to troubleshoot connectivity issues, improve Continue reading
Miscommunication between techies and business leaders are often caused by misunderstanding. Listen in as Eyvonne, Tom, and Russ discuss these misunderstandings and how we can address them.
In 2023, Cloudflare introduced a new load balancing solution, supporting Local Traffic Management (LTM). This gives organizations a way to balance HTTP(S) traffic between private or internal servers within a region-specific data center. Today, we are thrilled to be able to extend those same LTM capabilities to non-HTTP(S) traffic. This new feature is enabled by the integration of Cloudflare Spectrum, Cloudflare Tunnels, and Cloudflare load balancers and is available to enterprise customers. Our customers can now use Cloudflare load balancers for all TCP and UDP traffic destined for private IP addresses, eliminating the need for expensive on-premise load balancers.
In this blog post, we will be referring to load balancers at either layer 4 or layer 7. This is, of course, referring to layers of the OSI model but more specifically, the ingress path that is being used to reach the load balancer. Layer 7, also known as the Application Layer, is where the HTTP(S) protocol exists. Cloudflare is well known for our layer 7 capabilities, which are built around speeding up and protecting websites which run over HTTP(S). When we refer to layer 7 load balancers, we are referring to HTTP(S)-based services. Our layer Continue reading
Welcome to Technology Short Take #178! This one is notably shorter than many of the Technology Short Takes I publish; I’m still trying to fine-tune my collection of RSS feeds (such a useful technology that seems to have fallen out of favor), removing inactive feeds and looking for new feeds to replace them. Regardless, I have managed to collect a few links for your reading pleasure this weekend. Enjoy!
I mostly gave up on LLMs being any help (apart from generating copious amounts of bullshit), but I still thought that generating summaries might be an interesting use case. I was wrong.
As Gerben Wierda explains in his recent “When ChatGPT summarises, it actually does nothing of the kind” blog post, you have to understand a text if you want to generate a useful summary, and that’s not what LLMs do. They can generate a shorter version of the text, which might not focus on the significant bits.
While performing some testing with CiliumNetworkPolicies, I came across a behavior that was unintuitive and unexpected to me. The behavior centers around how an endpoint selector behaves in a CiliumNetworkPolicies when Kubernetes namespaces are involved. (If you didn’t understand a bit of what I just said, I’ll provide some additional explanation shortly—stay with me!) After chatting through the behavior with a few folks, I realized the behavior is essentially “correct” and expected. However, if I was confused by the behavior then there’s a good chance others might be confused by the behavior as well, so I thought a quick blog post might be a good idea. Keep reading to get more details on the interaction between endpoint selectors and Kubernetes namespaces in CiliumNetworkPolicies.
Before digging into the behavior, let me first provide some definitions or explanations of the various things involved here:
Cloudforce One is publishing the results of our investigation and real-time effort to detect, deny, degrade, disrupt, and delay threat activity by the Russia-aligned threat actor FlyingYeti during their latest phishing campaign targeting Ukraine. At the onset of Russia’s invasion of Ukraine on February 24, 2022, Ukraine introduced a moratorium on evictions and termination of utility services for unpaid debt. The moratorium ended in January 2024, resulting in significant debt liability and increased financial stress for Ukrainian citizens. The FlyingYeti campaign capitalized on anxiety over the potential loss of access to housing and utilities by enticing targets to open malicious files via debt-themed lures. If opened, the files would result in infection with the PowerShell malware known as COOKBOX, allowing FlyingYeti to support follow-on objectives, such as installation of additional payloads and control over the victim’s system.
Since April 26, 2024, Cloudforce One has taken measures to prevent FlyingYeti from launching their phishing campaign – a campaign involving the use of Cloudflare Workers and GitHub, as well as exploitation of the WinRAR vulnerability CVE-2023-38831. Our countermeasures included internal actions, such as detections and code takedowns, as well as external collaboration with third parties to remove the actor’s cloud-hosted malware. Continue reading
We’re excited to announce that BastionZero, a Zero Trust infrastructure access platform, has joined Cloudflare. This acquisition extends our Zero Trust Network Access (ZTNA) flows with native access management for infrastructure like servers, Kubernetes clusters, and databases.
Security teams often prioritize application and Internet access because these are the primary vectors through which users interact with corporate resources and external threats infiltrate networks. Applications are typically the most visible and accessible part of an organization's digital footprint, making them frequent targets for cyberattacks. Securing application access through methods like Single Sign-On (SSO) and Multi-Factor Authentication (MFA) can yield immediate and tangible improvements in user security.
However, infrastructure access is equally critical and many teams still rely on castle-and-moat style network controls and local resource permissions to protect infrastructure like servers, databases, Kubernetes clusters, and more. This is difficult and fraught with risk because the security controls are fragmented across hundreds or thousands of targets. Bad actors are increasingly focusing on targeting infrastructure resources as a way to take down huge swaths of applications at once or steal sensitive data. We are excited to extend Cloudflare One’s Zero Trust Network Access to natively protect infrastructure with user- and device-based policies Continue reading
The generative AI revolution is making strange bedfellows, as revolutions and emerging monopolies that capitalize on them, often do. …
Key Hyperscalers And Chip Makers Gang Up On Nvidia’s NVSwitch Interconnect was written by Timothy Prickett Morgan at The Next Platform.
Using the typical default router configurations, it can take minutes between a failure of an inter-AS link and the convergence of BGP routes. You can fine-tune that behavior with BGP timers and BFD (and still get pwned by Graceful Restart). While you can’t influence link failures, you could drain the traffic from a link before starting maintenance operations on it, and it would be a shame not to do that considering there’s a standard way to do that – the GRACEFUL_SHUTDOWN BGP community defined in RFC 8326. That’s what you’ll practice in the next BGP lab exercise.
By Matthew Jones, Chief Architect, Ansible Automation at Red Hat
Back in 2013, a small team of engineers worked for over a year to make the first commercial release of Ansible Tower (before we expanded and evolved to Ansible Automation Platform) and during that time we put down the foundation of an application that I’m immensely proud of.
We, the original architects of Tower, were trying to find the best way to create a system that would allow running Ansible at scale for hundreds of thousands of servers. We wanted there to be a way to not just manage those servers but store the results of that automation and provide auditability and traceability. It needed to make Ansible functional for large teams and it succeeded.
Today, we’re not just talking about hundreds of thousands. We’re thinking in the millions and tens of millions, we’re managing automation for some of the largest IT organizations in the world. And we’re not just managing servers. In the intervening years we’ve been automating containers, cloud platforms, network devices, storage, IoT devices and PLCs (among other things). One of the main challenges that we’re facing is that some of the architectural decisions we made Continue reading
One reason the OSI model isnメt all that useful anymore is because it assumes things about networks that are no longer true, such as the existence of a clear set of protocols neatly layered one atop another. We just donメt build networks this way any longer.
I recently had a need to get Barrier—an open source project aimed at enabling mouse/keyboard sharing across multiple computers, aka a “software KVM”—running between Arch Linux and Ubuntu 22.04. Unfortunately, the process for getting Barrier working isn’t as intuitive as it should be, so I’m posting this information in the hopes it will prove useful to others who find themselves in a similar situation. Below, I’ll share how I got Barrier working between an Arch Linux system and an Ubuntu system.
Although this post specifically mentions Arch Linux and Ubuntu, the process for getting Barrier running should be pretty similar (if not identical) for other Linux distributions and for macOS. I don’t have any Windows-based systems on which to test these instructions, but they should be adaptable to Windows as well. Note that there may be slight differences in the flags for the commands listed here when they are run on platforms other than Linux.
Both Arch and Ubuntu 22.04 have the latest release of Barrier, version 2.4.0, available in their repositories, so the installation is straightforward.
For Arch, just install with pacman
:
pacman -Ss barrier
There’s also a “barrier-headless” package in Continue reading