The Raspberry Pi 3 Model B may be an older board, but it remains a […]
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https://codingpackets.com/blog/yt-dlp-quick-reference
https://codingpackets.com/blog/libvirt-tips-and-tricks
It’s time again for Tom, Eyvonne, and Russ to talk about current articles they’ve run across in their day-to-day reading. This time we talk about WiFi in the home, how often users think a global problem is really local, and why providers have a hard time supporting individual homes and businesses. The second topic is one no one really cares about … apathy. What causes apathy? How can we combat it? Join us for this episode of the Hedge … if you can bring yourself to care!
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Kubernetes adoption is growing, and managing secure and efficient network communication is becoming increasingly complex. With this growth, organizations need to enforce network policies with greater precision and care. However, implementing these policies without disrupting operations can be challenging.
That’s where Calico Whisker comes in. It helps teams implement network policies that follow the principle of least privilege, ensuring workloads communicate only as intended. Since most organizations introduce network policies after applications are already running, safe and incremental rollout is essential.
To support this, Calico Whisker offers staged network policies, which allow teams to preview a policy’s effect in a live environment before enforcing it. Alongside this, policy traces in Calico Whisker provide deep visibility into how both enforced and pending policies impact traffic. This makes it easier to understand policy behaviour, validate intent, and troubleshoot issues in real time. In this post, we’ll walk through real-world policy trace outputs and show how they help teams confidently deploy and refine network policies in production Kubernetes clusters.
It’s important to reiterate the network policy behaviour in Kubernetes, as understanding this foundation is key to effectively interpreting policy traces and ensuring the right traffic flow decisions are Continue reading
sflow sampling-rate 10000 sflow polling-interval 20 sflow header-bytes 128 sflow direction both sflow drop-monitoring enable sflow enable GigabitEthernet0/8/0 sflow enable GigabitEthernet0/9/0 sflow enable GigabitEthernet0/a/0The above VPP configuration commands enable sFlow monitoring of the VPP dataplane, randomly sampling packets, periodically polling counters, and capturing dropped packets and reason codes. The measurements are send via Linux netlink messages to an instance of the open source Host sFlow agent (hsflowd) which combines the measurements and streams standard sFlow telemetry to a remote collector.
sflow {
collector { ip=192.0.2.1 udpport=6343 }
psample { group=1 egress=on }
dropmon { start=on limit=50 }
vpp { }
}The /etc/hsflowd.conf file above enables the modules needed to receive netlink messages from VPP and send the resulting sFlow telemetry to a collector at 192.0.2.1. See vpp-sflow for detailed instructions.
docker run -p 6343:6343/udp sflow/sflowtoolRun sflowtool on the sFlow collector host to verify verify that the data is being received and Continue reading
After launching the BGP labs in 2023 and IS-IS labs in 2024, it was time to start another project that was quietly sitting on the back burner for ages: open-source (and free) VXLAN/EVPN labs.
The first lab exercise is already online and expects you to extend a single VLAN segment across an IP underlay network using VXLAN encapsulation with static ingress replication.

The IT world is on fire right now with solutions to every major problem we’ve ever had. Wouldn’t you know it that the solution appears to be something that people are very intent on selling to you? Where have I heard that before? You wouldn’t know it looking at the landscape of IT right now but AI has iterated more times than you can think over the last couple of years. While people are still carrying on about LLMs and writing homework essays the market has moved on to agentic solutions that act like employees doing things all over the place.
The result is people are more excited about the potential for AI than ever. Well, that is if you’re someone that has problems that need to be solved. If you’re someone doing something creative, like making art or music or poetry you’re worried about what AI is going to do to your profession. That divide is what I’ve been thinking about for a while. I don’t think it should come as a shock to anyone but I’ve figured out why AI is hot for every executive out there.
AI appeals to people that have someone doing work for them.
Pat Allen wrote an interesting guide for managers of networking teams dealing with the onslaught of AI (HT: PacketPushers newsletter).
The leitmotif: use AI to generate a rough solution, then review and improve it. That makes perfect sense and works as long as we don’t forget we can’t trust AI, assuming you save time doing it this way.
Securing what comes into your Kubernetes cluster often gets top billing. But what leaves your cluster, outbound or egress traffic, can be just as risky. A single compromised pod can exfiltrate data, connect to malicious servers, or propagate threats across your network. Without proper egress controls, workloads can reach untrusted destinations, creating serious security and compliance risks. This guide breaks down five practical steps to strengthen Kubernetes egress security, helping teams protect data, enforce policies, and maintain visibility across clusters.
Why Egress Controls Matter
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To help teams tackle this challenge, we’ve put together a Kubernetes Egress Security Checklist, based on best practices from real-world Continue reading
Found this incredible gem1 hidden in the Usage Guidelines for the OSPFv3 router-id configuration command part of the Cisco IOS IPv6 reference guide.
The whole paragraph seems hallucinated2, but that couldn’t be because the page was supposedly last updated in 2019, and LLMs weren’t good enough to write well-structured nonsense at that time:
OSPFv3 is backward-compatible with OSPF version 2.
No, it is not.