Category: Worth Reading

In case you ever wondered how old the “keep network simple and do complex stuff at the endpoints” approach is, read the End-to-End Arguments in System Design article from 1981.

For whatever reason (hint: profits), networking vendors keep ignoring those arguments, turning the network into a kitchen sink of complexity.

Fun tidbit: the article describes a variant of relying on layer-2 checksums will corrupt your data. Some things never change.

Want to know some details behind the CloudFlare SD-WAN implementation? You might find them in From IP packets to HTTP: the many faces of our Oxy framework.

I don’t know enough about Linux networking to figure out whether one could use those details to build something similar, but CloudFlare blog posts keep begin much better than Google’s Look How Awesome We Are recruitment drives.

Avery Pennarun published a lovely rambling on magic, science, engineering and a pinch of AI. You might enjoy reading it¹ with your Sunday morning coffee 😎.

Jeff McLaughlin wrote a nice blog post on the death of CLI (and why it has been greatly exaggerated):

The GUI-based layout tool [for iOS app development] is going away in favor of UI-as-code! The black screen always comes back!

As I’ve been saying for ages: people optimizing their productivity use CLI.

I have blog post ideas sitting in my to-write queue for over a decade. One of them is why would you need a VRF (and associated router) between virtual servers and a firewall?

Andrea Dainese answered at least part of that question in his Off-Path firewall with Traffic Engineering blog post. Enjoy!

Another interesting take on ChatGPT in networking, this time by Tom Hollingsworth in The Dangers of Knowing Everything:

In a way, ChatGPT is like a salesperson. No matter what you ask it the answer is always yes, even if it has to make something up to answer the question.

To paraphrase an old joke: It’s not that ChatGPT is lying. It’s just that what it knows isn’t necessarily true. See also: the difference between bullshit and lies.

Just in case you wondered why we have eight bits per byte: after Julia Evans investigated this mystery, Steven Bellovin published an excellent overview of the early years of bytes and words.

Another take on “what are large language models and what can we expect from them,” this time by Bruce Davie: Putting Large Language Models in Context:

My approach, at least for now, is to treat these LLM-based systems as very large, efficient collections of matchboxes–and keep working in my chosen field of networking.

Jeff McLaughlin published an excellent blog post perfectly describing what we’ve been experiencing for decades: the war on expertise.

On one hand, the “business owners” force us to build complex stuff because they think they know better, on the other they blame people who know how to do it for the complex stuff that happens as the result of their requirements:

I am saying that we need to stop blaming complexity on those who manage to understand it.

One of the best descriptions of what ChatGPT does and what it cannot do I found so far comes from an ancient and military historian. The what is ChatGPT and what is an essay parts are a must-read, the preparing to be disrupted conclusion is pure gold:

I do think there are classrooms that will be disrupted by ChatGPT, but those are classrooms where something is already broken.

I can’t help but think of the never-ending brouhaha about exam brain dumps.