Podcasts about zsh

Si llevas años usando Bash, Zsh o Fish y piensas que los pipes de Unix son lo más parecido a la perfección, este episodio te va a hacer tambalear los cimientos. Porque existe un shell que no pasa texto entre comandos: pasa estructuras de datos. Tablas, listas, registros, fechas, tamaños de archivo con tipo real. Y encima habla con Ollama sin que tengas que escribir ni una línea de Python.Ese shell es Nushell. Está escrito en Rust, tiene más de 40.000 estrellas en GitHub, y su filosofía es sencilla: los pipes deberían transportar datos con tipo, no texto que luego parseas con awk, sed o jq.En este episodio te cuento mi experiencia pasando de Fish a Nushell con ejemplos reales. Cuando escribes ls no obtienes texto: obtienes una tabla con columnas tipadas. Puedes hacer ls | where size > 1mb | sort-by size sin recurrir a awk ni números mágicos. El shell entiende qué es un filesize, qué es una fecha, qué es un número.Y luego está open, que entiende el formato por la extensión: JSON, YAML, TOML, CSV, SQLite... todo se convierte en datos estructurados. Abres un SQLite y ejecutas consultas con query db. Y todo combinable: http get a una API, filtrar con where y guardar con save — en un solo pipeline, sin archivos temporales.La guinda es la integración con IA. Como Nushell entiende JSON y Ollama habla JSON, se entienden a la perfección. Te enseño un pipeline que lista procesos, filtra los que consumen más de 100MB de RAM, se los manda a un modelo local, y mata el que más memoria usa. Todo en una línea. También te hablo de ai.nu, un módulo que envuelve Ollama, OpenAI y DeepSeek, con function calling desde el shell.También hago una comparativa: Bash, Zsh, Fish y Nushell cara a cara. Bash funciona en cualquier sitio pero el manejo de datos es arcaico. Zsh es Bash con esteroides pero los pipes siguen siendo texto. Fish es moderno pero no entiende de tipos. Nu es el único con estructuras de datos de verdad. PowerShell fue el primero en pasar objetos, pero Nu es lo que PowerShell debería haber sido.Capítulos del episodio:0:00 — Introducción: de Bash a Fish, la evolución de las shells2:30 — El problema del texto plano: por qué Nushell es diferente5:00 — La trifecta: ls, where y select, SQL en tu terminal7:30 — Tipos reales: la shell entiende fechas, tamaños y números10:00 — Open: abrir JSON, CSV, YAML y SQLite sin herramientas externas13:00 — Procesamiento avanzado: $in, save, append y par-each15:30 — HTTP GET: APIs de GitHub y meteorología desde la shell18:00 — Comparativa de shells: Bash vs ZSH vs Fish vs Nushell21:00 — Nushell e IA: integración nativa con Ollama sin Python24:00 — Instalación, casos de uso y conclusiones finalesMás información y enlaces en las notas del episodio

Hoy dejamos a un lado por un momento los modelos de lenguaje y la inteligencia artificial para volver a los clásicos de este pódcast: la optimización y el disfrute de nuestra terminal de Linux. He decidido intercalar estos temas para no aburrir a nadie. Sé que la inteligencia artificial es fascinante, pero de vez en cuando viene muy bien un respiro técnico para centrarnos en lo que siempre nos ha apasionado: exprimir al máximo nuestro sistema operativo favorito. Por eso, hoy te traigo lo que yo llamo el tridente de la terminal, un trío de herramientas que, cuando se integran y empiezan a trabajar juntas, cambian por completo tu flujo de trabajo. Te aseguro que, una vez que las pruebas, ya no hay vuelta atrás.El buscador difuso interactivo: FZFLa primera pieza de nuestro tridente es FZF (Fuzzy Finder). Imagina que tienes una lista gigante de archivos o de comandos y quieres encontrar algo específico. En lugar de escribir el término de búsqueda exacto, FZF te permite realizar una búsqueda difusa. Si buscas, por ejemplo, la palabra firefox, te bastará con teclear ffx. El programa entenderá de inmediato lo que estás intentando buscar y te filtrará los resultados en tiempo real.Ripgrep (rg): Búsquedas en milisegundosLa segunda herramienta que forma nuestro tridente es Ripgrep, conocida en la terminal simplemente como rg. Si vienes usando el comando grep de toda la vida, Ripgrep va a ser una revelación para ti. Está programada en Rust y su velocidad de búsqueda dentro de archivos es, sencillamente, abrumadora.Bat: El clásico cat rediseñado con superpoderesLa tercera punta del tridente es Bat (en algunos sistemas Debian y Ubuntu lo encontrarás como batcat). Todos hemos usado el comando cat para imprimir el contenido de un archivo en la terminal. Bat viene a sustituirlo ofreciendo una visualización muy superior.Cómo armar el tridente: La fusión definitivaLo verdaderamente potente de estas herramientas no es solo usarlas por separado, sino conectarlas. Combinando Ripgrep con FZF y Bat, consigues un sistema de búsqueda en vivo increíble. Puedes hacer que Ripgrep busque un término en todos tus documentos, pasarle esa lista a FZF para que te permita filtrar de forma interactiva y, mientras te mueves por los resultados, abrir una pequeña ventana en el lateral donde Bat te previsualice en tiempo real el contenido del archivo con la sintaxis coloreada.En el episodio te explico cómo definir estas funciones en tu archivo de configuración (Bash, Zsh o Fish). De este modo, puedes construirte utilidades personalizadas con solo unas pocas líneas de código: desde un explorador de commits de Git muy visual hasta tu propio gestor de notas Markdown, rápido y sin distracciones, eliminando la necesidad de recurrir a pesados programas con interfaz gráfica.Capítulos de este episodioAquí tienes la estructura del episodio para que puedas moverte cómodamente por el contenido:00:00:00 Introducción y el tridente de la terminal00:01:22 FZF: El buscador difuso interactivo00:03:00 Atajos de teclado esenciales para FZF00:08:16 El autocompletado mágico de FZF00:09:09 Ripgrep (rg): Búsquedas a la velocidad de la luz00:12:47 Combinando Ripgrep y FZF00:14:26 Bat: El comando "cat" con superpoderes00:18:07 Armando el tridente: Cómo combinar las tres herramientas00:19:48 Casos prácticos: Explorar commits, matar procesos y gestionar notas00:21:49 El ecosistema completo de 5 herramientas00:23:19 Integración con IA, despedida y conclusionesMás información y enlaces en las notas del episodio

**Palabras clave**: MacBook Pro M5 Max, scripts ZSH, dock, Bluetooth, desmontaje de discos, procesamiento de audio, transcripción local, modelos LLM, Q-WEN 3B, heretic models, automatización, panel de herramientas, iCloud, Homebrew - **MacBook Pro M5 Max con 128 GB de RAM** es el hardware base. - **Scripts ZSH para control del dock y dispositivos**, con limitaciones de macOS. - **Procesamiento de audio offline** desde grabación hasta publicación en blog. - **Q-WEN 3B (8 bits)** ofrece mejor calidad que la versión de 4 bits. - **“Heretic models”** representan una tendencia hacia IA más directa y autónoma. - **Panel en iCloud** como interfaz centralizada para acceder a herramientas.

Show DescriptionWe've got Robby Russell, maintainer of Oh My Zsh, on the show to talk about why Chris has it installed, what makes a good Zsh plugin, Oh My Zsh plugins Robby recommends, what it's like working in Rails in 2026, dealing with project dependancies, and how Rails apps make use of frameworks? Listen on WebsiteWatch on YouTubeGuestsRobby RussellGuest's Main URL • Guest's SocialCEO and Partner at Planet Argon Links Oh My Zsh - a delightful & open source framework for Zsh Robby Russell - CEO, Partner Planet Argon On Rails Podcast Maintainable Software Podcast ohmyzsh/plugins/autojump shadcn/ui SponsorsSanityThe back-end built for AI content operations. Power web, mobile, and agentic applications at scale. Start building with an extended 60-day trial.

Possible exploit variant for CVE-2024-9042 (Kubernetes OS Command Injection) We observed HTTP requests with our honeypot that may be indicative of a new version of an exploit against an older vulnerability. Help us figure out what is going on. https://isc.sans.edu/diary/Possible%20exploit%20variant%20for%20CVE-2024-9042%20%28Kubernetes%20OS%20Command%20Injection%29/32554 React2Shell: Technical Deep-Dive & In-the-Wild Exploitation of CVE-2025-55182 Wiz has a writeup with more background on the React2Shell vulnerability and current attacks https://www.wiz.io/blog/nextjs-cve-2025-55182-react2shell-deep-dive Notepad++ Update Hijacking Notepad++ s vulnerable update process was exploited https://notepad-plus-plus.org/news/v889-released/ New macOS PackageKit Privilege Escalation A PoC was released for a new privilege escalation vulnerability in macOS. Currently, there is no patch. https://khronokernel.com/macos/2024/06/03/CVE-2024-27822.html

Willkommen zurück zu einer neuen Schnapszahlfolge. Sandra und Daniel sprechen über Podcasts, die sie gerne hören. Family IT-Support, Notizen, ZSH und Linux dürfen auch nicht fehlen.

¡Transforma tu Terminal Linux en una Máquina de Productividad! Domina fish shell con este Tutorial Práctico¿Te preguntas cómo los expertos en Linux logran trabajar tan rápido en la terminal? ¿Estás cansado de escribir los mismos comandos largos una y otra vez? Si la respuesta es sí, este episodio de Atareao con Linux es para ti. En él, vamos a desvelar uno de los secretos mejor guardados para la automatización y la eficiencia: el uso de fish shell. A diferencia de otras shells como Bash o Zsh, fish se diseñó desde cero pensando en la usabilidad y la productividad, y hoy te voy a enseñar por qué sus abreviaciones y funciones son una auténtica revolución para tu flujo de trabajo.Este no es solo un tutorial teórico. Te guiaré paso a paso para que puedas implementar estas herramientas en tu sistema Linux de inmediato. Te mostraré cómo dejar de depender de los alias tradicionales y aprovechar el poder de las abreviaciones (abbr) que se expanden en tiempo real, dándote un control sin precedentes antes de ejecutar un comando. Esto te permitirá evitar errores comunes y, sobre todo, ganar velocidad.Pero fish no se queda ahí. También te enseñaré a crear funciones personalizadas para automatizar tareas más complejas, scripts que puedes ejecutar con una simple palabra, sin importar si necesitas gestionar tus servicios con Docker, optimizar la copia de archivos con Syncthing, o simplemente simplificar tareas cotidianas de administración del sistema. Cada segundo que ahorras en la terminal se traduce en más tiempo para innovar y crear.¿Qué te llevas de este episodio de Atareao con Linux?Aprende la diferencia clave entre abbr y alias, y por qué las abreviaciones de fish te harán más productivo al instante.Descubre cómo crear y gestionar tus propios atajos de teclado para cualquier comando, desde operaciones de Git hasta el despliegue de contenedores.Dominas el arte de las funciones en fish para automatizar scripts y lógicas complejas de forma sencilla.Obtén consejos prácticos sobre cómo organizar tu configuración en ~/.config/fish/ para mantener un entorno de trabajo limpio y eficiente.Entiende la filosofía de fish y por qué es una de las mejores shells de código abierto para cualquier entusiasta de GNU/Linux.Este episodio está pensado para cualquier persona que quiera mejorar su productividad en la línea de comandos, ya seas un desarrollador de software que usa Neovim o Rust, un sysadmin que gestiona servidores, o un usuario que simplemente quiere sacar el máximo provecho a su escritorio GNOME. Si te gusta la programación, el scripting, el software libre y la automatización, te garantizo que este contenido resonará contigo.No dejes pasar esta oportunidad de darle un impulso a tu carrera y a tus proyectos personales. La terminal es tu herramienta más poderosa; aprende a usarla como un verdadero profesional.¡Sigue el podcast Atareao con Linux para no perderte ningún truco! Cada semana, te traemos soluciones prácticas y tutoriales detallados para que domines Linux de una vez por todas. Si este episodio te ha parecido útil, deja una valoración positiva para que más personas puedan descubrir este conocimiento.Más información y enlaces en las notas del episodio

¡Transforma tu Terminal Linux en una Máquina de Productividad! Domina fish shell con este Tutorial Práctico¿Te preguntas cómo los expertos en Linux logran trabajar tan rápido en la terminal? ¿Estás cansado de escribir los mismos comandos largos una y otra vez? Si la respuesta es sí, este episodio de Atareao con Linux es para ti. En él, vamos a desvelar uno de los secretos mejor guardados para la automatización y la eficiencia: el uso de fish shell. A diferencia de otras shells como Bash o Zsh, fish se diseñó desde cero pensando en la usabilidad y la productividad, y hoy te voy a enseñar por qué sus abreviaciones y funciones son una auténtica revolución para tu flujo de trabajo.Este no es solo un tutorial teórico. Te guiaré paso a paso para que puedas implementar estas herramientas en tu sistema Linux de inmediato. Te mostraré cómo dejar de depender de los alias tradicionales y aprovechar el poder de las abreviaciones (abbr) que se expanden en tiempo real, dándote un control sin precedentes antes de ejecutar un comando. Esto te permitirá evitar errores comunes y, sobre todo, ganar velocidad.Pero fish no se queda ahí. También te enseñaré a crear funciones personalizadas para automatizar tareas más complejas, scripts que puedes ejecutar con una simple palabra, sin importar si necesitas gestionar tus servicios con Docker, optimizar la copia de archivos con Syncthing, o simplemente simplificar tareas cotidianas de administración del sistema. Cada segundo que ahorras en la terminal se traduce en más tiempo para innovar y crear.¿Qué te llevas de este episodio de Atareao con Linux?Aprende la diferencia clave entre abbr y alias, y por qué las abreviaciones de fish te harán más productivo al instante.Descubre cómo crear y gestionar tus propios atajos de teclado para cualquier comando, desde operaciones de Git hasta el despliegue de contenedores.Dominas el arte de las funciones en fish para automatizar scripts y lógicas complejas de forma sencilla.Obtén consejos prácticos sobre cómo organizar tu configuración en ~/.config/fish/ para mantener un entorno de trabajo limpio y eficiente.Entiende la filosofía de fish y por qué es una de las mejores shells de código abierto para cualquier entusiasta de GNU/Linux.Este episodio está pensado para cualquier persona que quiera mejorar su productividad en la línea de comandos, ya seas un desarrollador de software que usa Neovim o Rust, un sysadmin que gestiona servidores, o un usuario que simplemente quiere sacar el máximo provecho a su escritorio GNOME. Si te gusta la programación, el scripting, el software libre y la automatización, te garantizo que este contenido resonará contigo.No dejes pasar esta oportunidad de darle un impulso a tu carrera y a tus proyectos personales. La terminal es tu herramienta más poderosa; aprende a usarla como un verdadero profesional.¡Sigue el podcast Atareao con Linux para no perderte ningún truco! Cada semana, te traemos soluciones prácticas y tutoriales detallados para que domines Linux de una vez por todas. Si este episodio te ha parecido útil, deja una valoración positiva para que más personas puedan descubrir este conocimiento.Más información y enlaces en las notas del episodio

Die Drei sind mal wieder vom Weg abgekommen und haben dabei doch noch Themen wie den Libre Workspace, das Treffen von Bill und Linus, ZSH, EU DNS Server und AI in Linux.Bei Jean hat es zur Aufnahme geregnet, falls ihr euch wundert warum da so viele Hintergrundgeräusche sind.

Disclaimer: We recorded this episode ~1.5 months ago, timing for the FastHTML release. It then got bottlenecked by Llama3.1, Winds of AI Winter, and SAM2 episodes, so we're a little late. Since then FastHTML was released, swyx is building an app in it for AINews, and Anthropic has also released their prompt caching API. Remember when Dylan Patel of SemiAnalysis coined the GPU Rich vs GPU Poor war? (if not, see our pod with him). The idea was that if you're GPU poor you shouldn't waste your time trying to solve GPU rich problems (i.e. pre-training large models) and are better off working on fine-tuning, optimized inference, etc. Jeremy Howard (see our “End of Finetuning” episode to catchup on his background) and Eric Ries founded Answer.AI to do exactly that: “Practical AI R&D”, which is very in-line with the GPU poor needs. For example, one of their first releases was a system based on FSDP + QLoRA that let anyone train a 70B model on two NVIDIA 4090s. Since then, they have come out with a long list of super useful projects (in no particular order, and non-exhaustive):* FSDP QDoRA: this is just as memory efficient and scalable as FSDP/QLoRA, and critically is also as accurate for continued pre-training as full weight training.* Cold Compress: a KV cache compression toolkit that lets you scale sequence length without impacting speed.* colbert-small: state of the art retriever at only 33M params* JaColBERTv2.5: a new state-of-the-art retrievers on all Japanese benchmarks.* gpu.cpp: portable GPU compute for C++ with WebGPU.* Claudette: a better Anthropic API SDK. They also recently released FastHTML, a new way to create modern interactive web apps. Jeremy recently released a 1 hour “Getting started” tutorial on YouTube; while this isn't AI related per se, but it's close to home for any AI Engineer who are looking to iterate quickly on new products: In this episode we broke down 1) how they recruit 2) how they organize what to research 3) and how the community comes together. At the end, Jeremy gave us a sneak peek at something new that he's working on that he calls dialogue engineering: So I've created a new approach. It's not called prompt engineering. I'm creating a system for doing dialogue engineering. It's currently called AI magic. I'm doing most of my work in this system and it's making me much more productive than I was before I used it.He explains it a bit more ~44:53 in the pod, but we'll just have to wait for the public release to figure out exactly what he means.Timestamps* [00:00:00] Intro by Suno AI* [00:03:02] Continuous Pre-Training is Here* [00:06:07] Schedule-Free Optimizers and Learning Rate Schedules* [00:07:08] Governance and Structural Issues within OpenAI and Other AI Labs* [00:13:01] How Answer.ai works* [00:23:40] How to Recruit Productive Researchers* [00:27:45] Building a new BERT* [00:31:57] FSDP, QLoRA, and QDoRA: Innovations in Fine-Tuning Large Models* [00:36:36] Research and Development on Model Inference Optimization* [00:39:49] FastHTML for Web Application Development* [00:46:53] AI Magic & Dialogue Engineering* [00:52:19] AI wishlist & predictionsShow Notes* Jeremy Howard* Previously on Latent Space: The End of Finetuning, NeurIPS Startups* Answer.ai* Fast.ai* FastHTML* answerai-colbert-small-v1* gpu.cpp* Eric Ries* Aaron DeFazio* Yi Tai* Less Wright* Benjamin Warner* Benjamin Clavié* Jono Whitaker* Austin Huang* Eric Gilliam* Tim Dettmers* Colin Raffel* Sebastian Raschka* Carson Gross* Simon Willison* Sepp Hochreiter* Llama3.1 episode* Snowflake Arctic* Ranger Optimizer* Gemma.cpp* HTMX* UL2* BERT* DeBERTa* Efficient finetuning of Llama 3 with FSDP QDoRA* xLSTMTranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO-in-Residence at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol AI.Swyx [00:00:14]: And today we're back with Jeremy Howard, I think your third appearance on Latent Space. Welcome.Jeremy [00:00:19]: Wait, third? Second?Swyx [00:00:21]: Well, I grabbed you at NeurIPS.Jeremy [00:00:23]: I see.Swyx [00:00:24]: Very fun, standing outside street episode.Jeremy [00:00:27]: I never heard that, by the way. You've got to send me a link. I've got to hear what it sounded like.Swyx [00:00:30]: Yeah. Yeah, it's a NeurIPS podcast.Alessio [00:00:32]: I think the two episodes are six hours, so there's plenty to listen, we'll make sure to send it over.Swyx [00:00:37]: Yeah, we're trying this thing where at the major ML conferences, we, you know, do a little audio tour of, give people a sense of what it's like. But the last time you were on, you declared the end of fine tuning. I hope that I sort of editorialized the title a little bit, and I know you were slightly uncomfortable with it, but you just own it anyway. I think you're very good at the hot takes. And we were just discussing in our pre-show that it's really happening, that the continued pre-training is really happening.Jeremy [00:01:02]: Yeah, absolutely. I think people are starting to understand that treating the three ULM FIT steps of like pre-training, you know, and then the kind of like what people now call instruction tuning, and then, I don't know if we've got a general term for this, DPO, RLHFE step, you know, or the task training, they're not actually as separate as we originally suggested they were in our paper, and when you treat it more as a continuum, and that you make sure that you have, you know, more of kind of the original data set incorporated into the later stages, and that, you know, we've also seen with LLAMA3, this idea that those later stages can be done for a lot longer. These are all of the things I was kind of trying to describe there. It wasn't the end of fine tuning, but more that we should treat it as a continuum, and we should have much higher expectations of how much you can do with an already trained model. You can really add a lot of behavior to it, you can change its behavior, you can do a lot. So a lot of our research has been around trying to figure out how to modify the model by a larger amount rather than starting from random weights, because I get very offended at the idea of starting from random weights.Swyx [00:02:14]: Yeah, I saw that in ICLR in Vienna, there was an outstanding paper about starting transformers from data-driven piers. I don't know if you saw that one, they called it sort of never trained from scratch, and I think it was kind of rebelling against like the sort of random initialization.Jeremy [00:02:28]: Yeah, I've, you know, that's been our kind of continuous message since we started Fast AI, is if you're training for random weights, you better have a really good reason, you know, because it seems so unlikely to me that nobody has ever trained on data that has any similarity whatsoever to the general class of data you're working with, and that's the only situation in which I think starting from random weights makes sense.Swyx [00:02:51]: The other trends since our last pod that I would point people to is I'm seeing a rise in multi-phase pre-training. So Snowflake released a large model called Snowflake Arctic, where they detailed three phases of training where they had like a different mixture of like, there was like 75% web in the first instance, and then they reduced the percentage of the web text by 10% each time and increased the amount of code in each phase. And I feel like multi-phase is being called out in papers more. I feel like it's always been a thing, like changing data mix is not something new, but calling it a distinct phase is new, and I wonder if there's something that you're seeingJeremy [00:03:32]: on your end. Well, so they're getting there, right? So the point at which they're doing proper continued pre-training is the point at which that becomes a continuum rather than a phase. So the only difference with what I was describing last time is to say like, oh, there's a function or whatever, which is happening every batch. It's not a huge difference. You know, I always used to get offended when people had learning rates that like jumped. And so one of the things I started doing early on in Fast.ai was to say to people like, no, you should actually have your learning rate schedule should be a function, not a list of numbers. So now I'm trying to give the same idea about training mix.Swyx [00:04:07]: There's been pretty public work from Meta on schedule-free optimizers. I don't know if you've been following Aaron DeFazio and what he's doing, just because you mentioned learning rate schedules, you know, what if you didn't have a schedule?Jeremy [00:04:18]: I don't care very much, honestly. I don't think that schedule-free optimizer is that exciting. It's fine. We've had non-scheduled optimizers for ages, like Less Wright, who's now at Meta, who was part of the Fast.ai community there, created something called the Ranger optimizer. I actually like having more hyperparameters. You know, as soon as you say schedule-free, then like, well, now I don't get to choose. And there isn't really a mathematically correct way of, like, I actually try to schedule more parameters rather than less. So like, I like scheduling my epsilon in my atom, for example. I schedule all the things. But then the other thing we always did with the Fast.ai library was make it so you don't have to set any schedules. So Fast.ai always supported, like, you didn't even have to pass a learning rate. Like, it would always just try to have good defaults and do the right thing. But to me, I like to have more parameters I can play with if I want to, but you don't have to.Alessio [00:05:08]: And then the more less technical side, I guess, of your issue, I guess, with the market was some of the large research labs taking all this innovation kind of behind closed doors and whether or not that's good, which it isn't. And now we could maybe make it more available to people. And then a month after we released the episode, there was the whole Sam Altman drama and like all the OpenAI governance issues. And maybe people started to think more, okay, what happens if some of these kind of labs, you know, start to break from within, so to speak? And the alignment of the humans is probably going to fall before the alignment of the models. So I'm curious, like, if you have any new thoughts and maybe we can also tie in some of the way that we've been building Answer as like a public benefit corp and some of those aspects.Jeremy [00:05:51]: Sure. So, yeah, I mean, it was kind of uncomfortable because two days before Altman got fired, I did a small public video interview in which I said, I'm quite sure that OpenAI's current governance structure can't continue and that it was definitely going to fall apart. And then it fell apart two days later and a bunch of people were like, what did you know, Jeremy?Alessio [00:06:13]: What did Jeremy see?Jeremy [00:06:15]: I didn't see anything. It's just obviously true. Yeah. So my friend Eric Ries and I spoke a lot before that about, you know, Eric's, I think probably most people would agree, the top expert in the world on startup and AI governance. And you know, we could both clearly see that this didn't make sense to have like a so-called non-profit where then there are people working at a company, a commercial company that's owned by or controlled nominally by the non-profit, where the people in the company are being given the equivalent of stock options, like everybody there was working there with expecting to make money largely from their equity. So the idea that then a board could exercise control by saying like, oh, we're worried about safety issues and so we're going to do something that decreases the profit of the company, when every stakeholder in the company, their remuneration pretty much is tied to their profit, it obviously couldn't work. So I mean, that was a huge oversight there by someone. I guess part of the problem is that the kind of people who work at non-profits and in this case the board, you know, who are kind of academics and, you know, people who are kind of true believers. I think it's hard for them to realize that 99.999% of the world is driven very heavily by money, especially huge amounts of money. So yeah, Eric and I had been talking for a long time before that about what could be done differently, because also companies are sociopathic by design and so the alignment problem as it relates to companies has not been solved. Like, companies become huge, they devour their founders, they devour their communities and they do things where even the CEOs, you know, often of big companies tell me like, I wish our company didn't do that thing. You know, I know that if I didn't do it, then I would just get fired and the board would put in somebody else and the board knows if they don't do it, then their shareholders can sue them because they're not maximizing profitability or whatever. So what Eric's spent a lot of time doing is trying to think about how do we make companies less sociopathic, you know, how to, or more, you know, maybe a better way to think of it is like, how do we make it so that the founders of companies can ensure that their companies continue to actually do the things they want them to do? You know, when we started a company, hey, we very explicitly decided we got to start a company, not a academic lab, not a nonprofit, you know, we created a Delaware Seacorp, you know, the most company kind of company. But when we did so, we told everybody, you know, including our first investors, which was you Alessio. They sound great. We are going to run this company on the basis of maximizing long-term value. And in fact, so when we did our second round, which was an angel round, we had everybody invest through a long-term SPV, which we set up where everybody had to agree to vote in line with long-term value principles. So like never enough just to say to people, okay, we're trying to create long-term value here for society as well as for ourselves and everybody's like, oh, yeah, yeah, I totally agree with that. But when it comes to like, okay, well, here's a specific decision we have to make, which will not maximize short-term value, people suddenly change their mind. So you know, it has to be written into the legal documents of everybody so that no question that that's the way the company has to be managed. So then you mentioned the PBC aspect, Public Benefit Corporation, which I never quite understood previously. And turns out it's incredibly simple, like it took, you know, like one paragraph added to our corporate documents to become a PBC. It was cheap, it was easy, but it's got this huge benefit, which is if you're not a public benefit corporation, then somebody can come along and offer to buy you with a stated description of like turning your company into the thing you most hate, right? And if they offer you more than the market value of your company and you don't accept it, then you are not necessarily meeting the kind of your fiduciary responsibilities. So the way like Eric always described it to me is like, if Philip Morris came along and said that you've got great technology for marketing cigarettes to children, so we're going to pivot your company to do that entirely, and we're going to pay you 50% more than the market value, you're going to have to say yes. If you have a PBC, then you are more than welcome to say no, if that offer is not in line with your stated public benefit. So our stated public benefit is to maximize the benefit to society through using AI. So given that more children smoking doesn't do that, then we can say like, no, we're not selling to you.Alessio [00:11:01]: I was looking back at some of our emails. You sent me an email on November 13th about talking and then on the 14th, I sent you an email working together to free AI was the subject line. And then that was kind of the start of the C round. And then two days later, someone got fired. So you know, you were having these thoughts even before we had like a public example of like why some of the current structures didn't work. So yeah, you were very ahead of the curve, so to speak. You know, people can read your awesome introduction blog and answer and the idea of having a R&D lab versus our lab and then a D lab somewhere else. I think to me, the most interesting thing has been hiring and some of the awesome people that you've been bringing on that maybe don't fit the central casting of Silicon Valley, so to speak. Like sometimes I got it like playing baseball cards, you know, people are like, oh, what teams was this person on, where did they work versus focusing on ability. So I would love for you to give a shout out to some of the awesome folks that you have on the team.Jeremy [00:11:58]: So, you know, there's like a graphic going around describing like the people at XAI, you know, Elon Musk thing. And like they are all connected to like multiple of Stanford, Meta, DeepMind, OpenAI, Berkeley, Oxford. Look, these are all great institutions and they have good people. And I'm definitely not at all against that, but damn, there's so many other people. And one of the things I found really interesting is almost any time I see something which I think like this is really high quality work and it's something I don't think would have been built if that person hadn't built the thing right now, I nearly always reach out to them and ask to chat. And I tend to dig in to find out like, okay, you know, why did you do that thing? Everybody else has done this other thing, your thing's much better, but it's not what other people are working on. And like 80% of the time, I find out the person has a really unusual background. So like often they'll have like, either they like came from poverty and didn't get an opportunity to go to a good school or had dyslexia and, you know, got kicked out of school in year 11, or they had a health issue that meant they couldn't go to university or something happened in their past and they ended up out of the mainstream. And then they kind of succeeded anyway. Those are the people that throughout my career, I've tended to kind of accidentally hire more of, but it's not exactly accidentally. It's like when I see somebody who's done, two people who have done extremely well, one of them did extremely well in exactly the normal way from the background entirely pointing in that direction and they achieved all the hurdles to get there. And like, okay, that's quite impressive, you know, but another person who did just as well, despite lots of constraints and doing things in really unusual ways and came up with different approaches. That's normally the person I'm likely to find useful to work with because they're often like risk-takers, they're often creative, they're often extremely tenacious, they're often very open-minded. So that's the kind of folks I tend to find myself hiring. So now at Answer.ai, it's a group of people that are strong enough that nearly every one of them has independently come to me in the past few weeks and told me that they have imposter syndrome and they're not convinced that they're good enough to be here. And I kind of heard it at the point where I was like, okay, I don't think it's possible that all of you are so far behind your peers that you shouldn't get to be here. But I think part of the problem is as an R&D lab, the great developers look at the great researchers and they're like, wow, these big-brained, crazy research people with all their math and s**t, they're too cool for me, oh my God. And then the researchers look at the developers and they're like, oh, they're killing it, making all this stuff with all these people using it and talking on Twitter about how great it is. I think they're both a bit intimidated by each other, you know. And so I have to kind of remind them like, okay, there are lots of things in this world where you suck compared to lots of other people in this company, but also vice versa, you know, for all things. And the reason you came here is because you wanted to learn about those other things from those other people and have an opportunity to like bring them all together into a single unit. You know, it's not reasonable to expect you're going to be better at everything than everybody else. I guess the other part of it is for nearly all of the people in the company, to be honest, they have nearly always been better than everybody else at nearly everything they're doing nearly everywhere they've been. So it's kind of weird to be in this situation now where it's like, gee, I can clearly see that I suck at this thing that I'm meant to be able to do compared to these other people where I'm like the worst in the company at this thing for some things. So I think that's a healthy place to be, you know, as long as you keep reminding each other about that's actually why we're here. And like, it's all a bit of an experiment, like we don't have any managers. We don't have any hierarchy from that point of view. So for example, I'm not a manager, which means I don't get to tell people what to do or how to do it or when to do it. Yeah, it's been a bit of an experiment to see how that would work out. And it's been great. So for instance, Ben Clavier, who you might have come across, he's the author of Ragatouille, he's the author of Rerankers, super strong information retrieval guy. And a few weeks ago, you know, this additional channel appeared on Discord, on our private Discord called Bert24. And these people started appearing, as in our collab sections, we have a collab section for like collaborating with outsiders. And these people started appearing, there are all these names that I recognize, like Bert24, and they're all talking about like the next generation of Bert. And I start following along, it's like, okay, Ben decided that I think, quite rightly, we need a new Bert. Because everybody, like so many people are still using Bert, and it's still the best at so many things, but it actually doesn't take advantage of lots of best practices. And so he just went out and found basically everybody who's created better Berts in the last four or five years, brought them all together, suddenly there's this huge collaboration going on. So yeah, I didn't tell him to do that. He didn't ask my permission to do that. And then, like, Benjamin Warner dived in, and he's like, oh, I created a whole transformers from scratch implementation designed to be maximally hackable. He originally did it largely as a teaching exercise to show other people, but he was like, I could, you know, use that to create a really hackable BERT implementation. In fact, he didn't say that. He said, I just did do that, you know, and I created a repo, and then everybody's like starts using it. They're like, oh my god, this is amazing. I can now implement all these other BERT things. And it's not just answer AI guys there, you know, there's lots of folks, you know, who have like contributed new data set mixes and blah, blah, blah. So, I mean, I can help in the same way that other people can help. So like, then Ben Clavier reached out to me at one point and said, can you help me, like, what have you learned over time about how to manage intimidatingly capable and large groups of people who you're nominally meant to be leading? And so, you know, I like to try to help, but I don't direct. Another great example was Kerem, who, after our FSTP QLORA work, decided quite correctly that it didn't really make sense to use LoRa in today's world. You want to use the normalized version, which is called Dora. Like two or three weeks after we did FSTP QLORA, he just popped up and said, okay, I've just converted the whole thing to Dora, and I've also created these VLLM extensions, and I've got all these benchmarks, and, you know, now I've got training of quantized models with adapters that are as fast as LoRa, and as actually better than, weirdly, fine tuning. Just like, okay, that's great, you know. And yeah, so the things we've done to try to help make these things happen as well is we don't have any required meetings, you know, but we do have a meeting for each pair of major time zones that everybody's invited to, and, you know, people see their colleagues doing stuff that looks really cool and say, like, oh, how can I help, you know, or how can I learn or whatever. So another example is Austin, who, you know, amazing background. He ran AI at Fidelity, he ran AI at Pfizer, he ran browsing and retrieval for Google's DeepMind stuff, created Jemma.cpp, and he's been working on a new system to make it easier to do web GPU programming, because, again, he quite correctly identified, yeah, so I said to him, like, okay, I want to learn about that. Not an area that I have much expertise in, so, you know, he's going to show me what he's working on and teach me a bit about it, and hopefully I can help contribute. I think one of the key things that's happened in all of these is everybody understands what Eric Gilliam, who wrote the second blog post in our series, the R&D historian, describes as a large yard with narrow fences. Everybody has total flexibility to do what they want. We all understand kind of roughly why we're here, you know, we agree with the premises around, like, everything's too expensive, everything's too complicated, people are building too many vanity foundation models rather than taking better advantage of fine-tuning, like, there's this kind of general, like, sense of we're all on the same wavelength about, you know, all the ways in which current research is fucked up, and, you know, all the ways in which we're worried about centralization. We all care a lot about not just research for the point of citations, but research that actually wouldn't have happened otherwise, and actually is going to lead to real-world outcomes. And so, yeah, with this kind of, like, shared vision, people understand, like, you know, so when I say, like, oh, well, you know, tell me, Ben, about BERT 24, what's that about? And he's like, you know, like, oh, well, you know, you can see from an accessibility point of view, or you can see from a kind of a actual practical impact point of view, there's far too much focus on decoder-only models, and, you know, like, BERT's used in all of these different places and industry, and so I can see, like, in terms of our basic principles, what we're trying to achieve, this seems like something important. And so I think that's, like, a really helpful that we have that kind of shared perspective, you know?Alessio [00:21:14]: Yeah. And before we maybe talk about some of the specific research, when you're, like, reaching out to people, interviewing them, what are some of the traits, like, how do these things come out, you know, usually? Is it working on side projects that you, you know, you're already familiar with? Is there anything, like, in the interview process that, like, helps you screen for people that are less pragmatic and more research-driven versus some of these folks that are just gonna do it, you know? They're not waiting for, like, the perfect process.Jeremy [00:21:40]: Everybody who comes through the recruiting is interviewed by everybody in the company. You know, our goal is 12 people, so it's not an unreasonable amount. So the other thing to say is everybody so far who's come into the recruiting pipeline, everybody bar one, has been hired. So which is to say our original curation has been good. And that's actually pretty easy, because nearly everybody who's come in through the recruiting pipeline are people I know pretty well. So Jono Whitaker and I, you know, he worked on the stable diffusion course we did. He's outrageously creative and talented, and he's super, like, enthusiastic tinkerer, just likes making things. Benjamin was one of the strongest parts of the fast.ai community, which is now the alumni. It's, like, hundreds of thousands of people. And you know, again, like, they're not people who a normal interview process would pick up, right? So Benjamin doesn't have any qualifications in math or computer science. Jono was living in Zimbabwe, you know, he was working on, like, helping some African startups, you know, but not FAANG kind of credentials. But yeah, I mean, when you actually see people doing real work and they stand out above, you know, we've got lots of Stanford graduates and open AI people and whatever in our alumni community as well. You know, when you stand out above all of those people anyway, obviously you've got something going for you. You know, Austin, him and I worked together on the masks study we did in the proceeding at the National Academy of Science. You know, we had worked together, and again, that was a group of, like, basically the 18 or 19 top experts in the world on public health and epidemiology and research design and so forth. And Austin, you know, one of the strongest people in that collaboration. So yeah, you know, like, I've been lucky enough to have had opportunities to work with some people who are great and, you know, I'm a very open-minded person, so I kind of am always happy to try working with pretty much anybody and some people stand out. You know, there have been some exceptions, people I haven't previously known, like Ben Clavier, actually, I didn't know before. But you know, with him, you just read his code, and I'm like, oh, that's really well-written code. And like, it's not written exactly the same way as everybody else's code, and it's not written to do exactly the same thing as everybody else's code. So yeah, and then when I chatted to him, it's just like, I don't know, I felt like we'd known each other for years, like we just were on the same wavelength, but I could pretty much tell that was going to happen just by reading his code. I think you express a lot in the code you choose to write and how you choose to write it, I guess. You know, or another example, a guy named Vic, who was previously the CEO of DataQuest, and like, in that case, you know, he's created a really successful startup. He won the first, basically, Kaggle NLP competition, which was automatic essay grading. He's got the current state-of-the-art OCR system, Surya. Again, he's just a guy who obviously just builds stuff, you know, he doesn't ask for permission, he doesn't need any, like, external resources. Actually, Karim's another great example of this, I mean, I already knew Karim very well because he was my best ever master's student, but it wasn't a surprise to me then when he then went off to create the world's state-of-the-art language model in Turkish on his own, in his spare time, with no budget, from scratch. This is not fine-tuning or whatever, he, like, went back to Common Crawl and did everything. Yeah, it's kind of, I don't know what I'd describe that process as, but it's not at all based on credentials.Swyx [00:25:17]: Assemble based on talent, yeah. We wanted to dive in a little bit more on, you know, turning from the people side of things into the technical bets that you're making. Just a little bit more on Bert. I was actually, we just did an interview with Yi Tay from Reka, I don't know if you're familiar with his work, but also another encoder-decoder bet, and one of his arguments was actually people kind of over-index on the decoder-only GPT-3 type paradigm. I wonder if you have thoughts there that is maybe non-consensus as well. Yeah, no, absolutely.Jeremy [00:25:45]: So I think it's a great example. So one of the people we're collaborating with a little bit with BERT24 is Colin Raffle, who is the guy behind, yeah, most of that stuff, you know, between that and UL2, there's a lot of really interesting work. And so one of the things I've been encouraging the BERT group to do, Colin has as well, is to consider using a T5 pre-trained encoder backbone as a thing you fine-tune, which I think would be really cool. You know, Colin was also saying actually just use encoder-decoder as your Bert, you know, why don't you like use that as a baseline, which I also think is a good idea. Yeah, look.Swyx [00:26:25]: What technical arguments are people under-weighting?Jeremy [00:26:27]: I mean, Colin would be able to describe this much better than I can, but I'll give my slightly non-expert attempt. Look, I mean, think about like diffusion models, right? Like in stable diffusion, like we use things like UNet. You have this kind of downward path and then in the upward path you have the cross connections, which it's not a tension, but it's like a similar idea, right? You're inputting the original encoding path into your decoding path. It's critical to make it work, right? Because otherwise in the decoding part, the model has to do so much kind of from scratch. So like if you're doing translation, like that's a classic kind of encoder-decoder example. If it's decoder only, you never get the opportunity to find the right, you know, feature engineering, the right feature encoding for the original sentence. And it kind of means then on every token that you generate, you have to recreate the whole thing, you know? So if you have an encoder, it's basically saying like, okay, this is your opportunity model to create a really useful feature representation for your input information. So I think there's really strong arguments for encoder-decoder models anywhere that there is this kind of like context or source thing. And then why encoder only? Well, because so much of the time what we actually care about is a classification, you know? It's like an output. It's like generating an arbitrary length sequence of tokens. So anytime you're not generating an arbitrary length sequence of tokens, decoder models don't seem to make much sense. Now the interesting thing is, you see on like Kaggle competitions, that decoder models still are at least competitive with things like Deberta v3. They have to be way bigger to be competitive with things like Deberta v3. And the only reason they are competitive is because people have put a lot more time and money and effort into training the decoder only ones, you know? There isn't a recent Deberta. There isn't a recent Bert. Yeah, it's a whole part of the world that people have slept on a little bit. And this is just what happens. This is how trends happen rather than like, to me, everybody should be like, oh, let's look at the thing that has shown signs of being useful in the past, but nobody really followed up with properly. That's the more interesting path, you know, where people tend to be like, oh, I need to get citations. So what's everybody else doing? Can I make it 0.1% better, you know, or 0.1% faster? That's what everybody tends to do. Yeah. So I think it's like, Itay's work commercially now is interesting because here's like a whole, here's a whole model that's been trained in a different way. So there's probably a whole lot of tasks it's probably better at than GPT and Gemini and Claude. So that should be a good commercial opportunity for them if they can figure out what those tasks are.Swyx [00:29:07]: Well, if rumors are to be believed, and he didn't comment on this, but, you know, Snowflake may figure out the commercialization for them. So we'll see.Jeremy [00:29:14]: Good.Alessio [00:29:16]: Let's talk about FSDP, Qlora, Qdora, and all of that awesome stuff. One of the things we talked about last time, some of these models are meant to run on systems that nobody can really own, no single person. And then you were like, well, what if you could fine tune a 70B model on like a 4090? And I was like, no, that sounds great, Jeremy, but like, can we actually do it? And then obviously you all figured it out. Can you maybe tell us some of the worst stories behind that, like the idea behind FSDP, which is kind of taking sharded data, parallel computation, and then Qlora, which is do not touch all the weights, just go quantize some of the model, and then within the quantized model only do certain layers instead of doing everything.Jeremy [00:29:57]: Well, do the adapters. Yeah.Alessio [00:29:59]: Yeah. Yeah. Do the adapters. Yeah. I will leave the floor to you. I think before you published it, nobody thought this was like a short term thing that we're just going to have. And now it's like, oh, obviously you can do it, but it's not that easy.Jeremy [00:30:12]: Yeah. I mean, to be honest, it was extremely unpleasant work to do. It's like not at all enjoyable. I kind of did version 0.1 of it myself before we had launched the company, or at least the kind of like the pieces. They're all pieces that are difficult to work with, right? So for the quantization, you know, I chatted to Tim Detmers quite a bit and, you know, he very much encouraged me by saying like, yeah, it's possible. He actually thought it'd be easy. It probably would be easy for him, but I'm not Tim Detmers. And, you know, so he wrote bits and bytes, which is his quantization library. You know, he wrote that for a paper. He didn't write that to be production like code. It's now like everybody's using it, at least the CUDA bits. So like, it's not particularly well structured. There's lots of code paths that never get used. There's multiple versions of the same thing. You have to try to figure it out. So trying to get my head around that was hard. And you know, because the interesting bits are all written in CUDA, it's hard to like to step through it and see what's happening. And then, you know, FSTP is this very complicated library and PyTorch, which not particularly well documented. So the only really, really way to understand it properly is again, just read the code and step through the code. And then like bits and bytes doesn't really work in practice unless it's used with PEF, the HuggingFace library and PEF doesn't really work in practice unless you use it with other things. And there's a lot of coupling in the HuggingFace ecosystem where like none of it works separately. You have to use it all together, which I don't love. So yeah, trying to just get a minimal example that I can play with was really hard. And so I ended up having to rewrite a lot of it myself to kind of create this like minimal script. One thing that helped a lot was Medec had this LlamaRecipes repo that came out just a little bit before I started working on that. And like they had a kind of role model example of like, here's how to train FSTP, LoRa, didn't work with QLoRa on Llama. A lot of the stuff I discovered, the interesting stuff would be put together by Les Wright, who's, he was actually the guy in the Fast.ai community I mentioned who created the Ranger Optimizer. So he's doing a lot of great stuff at Meta now. So yeah, I kind of, that helped get some minimum stuff going and then it was great once Benjamin and Jono joined full time. And so we basically hacked at that together and then Kerim joined like a month later or something. And it was like, gee, it was just a lot of like fiddly detailed engineering on like barely documented bits of obscure internals. So my focus was to see if it kind of could work and I kind of got a bit of a proof of concept working and then the rest of the guys actually did all the work to make it work properly. And, you know, every time we thought we had something, you know, we needed to have good benchmarks, right? So we'd like, it's very easy to convince yourself you've done the work when you haven't, you know, so then we'd actually try lots of things and be like, oh, and these like really important cases, the memory use is higher, you know, or it's actually slower. And we'd go in and we just find like all these things that were nothing to do with our library that just didn't work properly. And nobody had noticed they hadn't worked properly because nobody had really benchmarked it properly. So we ended up, you know, trying to fix a whole lot of different things. And even as we did so, new regressions were appearing in like transformers and stuff that Benjamin then had to go away and figure out like, oh, how come flash attention doesn't work in this version of transformers anymore with this set of models and like, oh, it turns out they accidentally changed this thing, so it doesn't work. You know, there's just, there's not a lot of really good performance type evals going on in the open source ecosystem. So there's an extraordinary amount of like things where people say like, oh, we built this thing and it has this result. And when you actually check it, so yeah, there's a shitload of war stories from getting that thing to work. And it did require a particularly like tenacious group of people and a group of people who don't mind doing a whole lot of kind of like really janitorial work, to be honest, to get the details right, to check them. Yeah.Alessio [00:34:09]: We had a trade out on the podcast and we talked about how a lot of it is like systems work to make some of these things work. It's not just like beautiful, pure math that you do on a blackboard. It's like, how do you get into the nitty gritty?Jeremy [00:34:22]: I mean, flash attention is a great example of that. Like it's, it basically is just like, oh, let's just take the attention and just do the tiled version of it, which sounds simple enough, you know, but then implementing that is challenging at lots of levels.Alessio [00:34:36]: Yeah. What about inference? You know, obviously you've done all this amazing work on fine tuning. Do you have any research you've been doing on the inference side, how to make local inference really fast on these models too?Jeremy [00:34:47]: We're doing quite a bit on that at the moment. We haven't released too much there yet. But one of the things I've been trying to do is also just to help other people. And one of the nice things that's happened is that a couple of folks at Meta, including Mark Seraphim, have done a nice job of creating this CUDA mode community of people working on like CUDA kernels or learning about that. And I tried to help get that going well as well and did some lessons to help people get into it. So there's a lot going on in both inference and fine tuning performance. And a lot of it's actually happening kind of related to that. So PyTorch team have created this Torch AO project on quantization. And so there's a big overlap now between kind of the FastAI and AnswerAI and CUDA mode communities of people working on stuff for both inference and fine tuning. But we're getting close now. You know, our goal is that nobody should be merging models, nobody should be downloading merged models, everybody should be using basically quantized plus adapters for almost everything and just downloading the adapters. And that should be much faster. So that's kind of the place we're trying to get to. It's difficult, you know, because like Karim's been doing a lot of work with VLM, for example. These inference engines are pretty complex bits of code. They have a whole lot of custom kernel stuff going on as well, as do the quantization libraries. So we've been working on, we're also quite a bit of collaborating with the folks who do HQQ, which is a really great quantization library and works super well. So yeah, there's a lot of other people outside AnswerAI that we're working with a lot who are really helping on all this performance optimization stuff, open source.Swyx [00:36:27]: Just to follow up on merging models, I picked up there that you said nobody should be merging models. That's interesting because obviously a lot of people are experimenting with this and finding interesting results. I would say in defense of merging models, you can do it without data. That's probably the only thing that's going for it.Jeremy [00:36:45]: To explain, it's not that you shouldn't merge models. You shouldn't be distributing a merged model. You should distribute a merged adapter 99% of the time. And actually often one of the best things happening in the model merging world is actually that often merging adapters works better anyway. The point is, Sean, that once you've got your new model, if you distribute it as an adapter that sits on top of a quantized model that somebody's already downloaded, then it's a much smaller download for them. And also the inference should be much faster because you're not having to transfer FB16 weights from HPM memory at all or ever load them off disk. You know, all the main weights are quantized and the only floating point weights are in the adapters. So that should make both inference and fine tuning faster. Okay, perfect.Swyx [00:37:33]: We're moving on a little bit to the rest of the fast universe. I would have thought that, you know, once you started Answer.ai, that the sort of fast universe would be kind of on hold. And then today you just dropped Fastlight and it looks like, you know, there's more activity going on in sort of Fastland.Jeremy [00:37:49]: Yeah. So Fastland and Answerland are not really distinct things. Answerland is kind of like the Fastland grown up and funded. They both have the same mission, which is to maximize the societal benefit of AI broadly. We want to create thousands of commercially successful products at Answer.ai. And we want to do that with like 12 people. So that means we need a pretty efficient stack, you know, like quite a few orders of magnitude more efficient, not just for creation, but for deployment and maintenance than anything that currently exists. People often forget about the D part of our R&D firm. So we've got to be extremely good at creating, deploying and maintaining applications, not just models. Much to my horror, the story around creating web applications is much worse now than it was 10 or 15 years ago in terms of, if I say to a data scientist, here's how to create and deploy a web application, you know, either you have to learn JavaScript or TypeScript and about all the complex libraries like React and stuff, and all the complex like details around security and web protocol stuff around how you then talk to a backend and then all the details about creating the backend. You know, if that's your job and, you know, you have specialists who work in just one of those areas, it is possible for that to all work. But compared to like, oh, write a PHP script and put it in the home directory that you get when you sign up to this shell provider, which is what it was like in the nineties, you know, here are those 25 lines of code and you're done and now you can pass that URL around to all your friends, or put this, you know, .pl file inside the CGI bin directory that you got when you signed up to this web host. So yeah, the thing I've been mainly working on the last few weeks is fixing all that. And I think I fixed it. I don't know if this is an announcement, but I tell you guys, so yeah, there's this thing called fastHTML, which basically lets you create a complete web application in a single Python file. Unlike excellent projects like Streamlit and Gradio, you're not working on top of a highly abstracted thing. That's got nothing to do with web foundations. You're working with web foundations directly, but you're able to do it by using pure Python. There's no template, there's no ginger, there's no separate like CSS and JavaScript files. It looks and behaves like a modern SPA web application. And you can create components for like daisy UI, or bootstrap, or shoelace, or whatever fancy JavaScript and or CSS tailwind etc library you like, but you can write it all in Python. You can pip install somebody else's set of components and use them entirely from Python. You can develop and prototype it all in a Jupyter notebook if you want to. It all displays correctly, so you can like interactively do that. And then you mentioned Fastlight, so specifically now if you're using SQLite in particular, it's like ridiculously easy to have that persistence, and all of your handlers will be passed database ready objects automatically, that you can just call dot delete dot update dot insert on. Yeah, you get session, you get security, you get all that. So again, like with most everything I do, it's very little code. It's mainly tying together really cool stuff that other people have written. You don't have to use it, but a lot of the best stuff comes from its incorporation of HTMX, which to me is basically the thing that changes your browser to make it work the way it always should have. So it just does four small things, but those four small things are the things that are basically unnecessary constraints that HTML should never have had, so it removes the constraints. It sits on top of Starlet, which is a very nice kind of lower level platform for building these kind of web applications. The actual interface matches as closely as possible to FastAPI, which is a really nice system for creating the kind of classic JavaScript type applications. And Sebastian, who wrote FastAPI, has been kind enough to help me think through some of these design decisions, and so forth. I mean, everybody involved has been super helpful. Actually, I chatted to Carson, who created HTMX, you know, so about it. Some of the folks involved in Django, like everybody in the community I've spoken to definitely realizes there's a big gap to be filled around, like, highly scalable, web foundation-based, pure Python framework with a minimum of fuss. So yeah, I'm getting a lot of support and trying to make sure that FastHTML works well for people.Swyx [00:42:38]: I would say, when I heard about this, I texted Alexio. I think this is going to be pretty huge. People consider Streamlit and Gradio to be the state of the art, but I think there's so much to improve, and having what you call web foundations and web fundamentals at the core of it, I think, would be really helpful.Jeremy [00:42:54]: I mean, it's based on 25 years of thinking and work for me. So like, FastML was built on a system much like this one, but that was of hell. And so I spent, you know, 10 years working on that. We had millions of people using that every day, really pushing it hard. And I really always enjoyed working in that. Yeah. So, you know, and obviously lots of other people have done like great stuff, and particularly HTMX. So I've been thinking about like, yeah, how do I pull together the best of the web framework I created for FastML with HTMX? There's also things like PicoCSS, which is the CSS system, which by default, FastHTML comes with. Although, as I say, you can pip install anything you want to, but it makes it like super easy to, you know, so we try to make it so that just out of the box, you don't have any choices to make. Yeah. You can make choices, but for most people, you just, you know, it's like the PHP in your home directory thing. You just start typing and just by default, you'll get something which looks and feels, you know, pretty okay. And if you want to then write a version of Gradio or Streamlit on top of that, you totally can. And then the nice thing is if you then write it in kind of the Gradio equivalent, which will be, you know, I imagine we'll create some kind of pip installable thing for that. Once you've outgrown, or if you outgrow that, it's not like, okay, throw that all away and start again. And this like whole separate language that it's like this kind of smooth, gentle path that you can take step-by-step because it's all just standard web foundations all the way, you know.Swyx [00:44:29]: Just to wrap up the sort of open source work that you're doing, you're aiming to create thousands of projects with a very, very small team. I haven't heard you mention once AI agents or AI developer tooling or AI code maintenance. I know you're very productive, but you know, what is the role of AI in your own work?Jeremy [00:44:47]: So I'm making something. I'm not sure how much I want to say just yet.Swyx [00:44:52]: Give us a nibble.Jeremy [00:44:53]: All right. I'll give you the key thing. So I've created a new approach. It's not called prompt engineering. It's called dialogue engineering. But I'm creating a system for doing dialogue engineering. It's currently called AI magic. I'm doing most of my work in this system and it's making me much more productive than I was before I used it. So I always just build stuff for myself and hope that it'll be useful for somebody else. Think about chat GPT with code interpreter, right? The basic UX is the same as a 1970s teletype, right? So if you wrote APL on a teletype in the 1970s, you typed onto a thing, your words appeared at the bottom of a sheet of paper and you'd like hit enter and it would scroll up. And then the answer from APL would be printed out, scroll up, and then you would type the next thing. And like, which is also the way, for example, a shell works like bash or ZSH or whatever. It's not terrible, you know, like we all get a lot done in these like very, very basic teletype style REPL environments, but I've never felt like it's optimal and everybody else has just copied chat GPT. So it's also the way BART and Gemini work. It's also the way the Claude web app works. And then you add code interpreter. And the most you can do is to like plead with chat GPT to write the kind of code I want. It's pretty good for very, very, very beginner users who like can't code at all, like by default now the code's even hidden away, so you never even have to see it ever happened. But for somebody who's like wanting to learn to code or who already knows a bit of code or whatever, it's, it seems really not ideal. So okay, that's one end of the spectrum. The other end of the spectrum, which is where Sean's work comes in, is, oh, you want to do more than chat GPT? No worries. Here is Visual Studio Code. I run it. There's an empty screen with a flashing cursor. Okay, start coding, you know, and it's like, okay, you can use systems like Sean's or like cursor or whatever to be like, okay, Apple K in cursors, like a creative form that blah, blah, blah. But in the end, it's like a convenience over the top of this incredibly complicated system that full-time sophisticated software engineers have designed over the past few decades in a totally different environment as a way to build software, you know. And so we're trying to like shoehorn in AI into that. And it's not easy to do. And I think there are like much better ways of thinking about the craft of software development in a language model world to be much more interactive, you know. So the thing that I'm building is neither of those things. It's something between the two. And it's built around this idea of crafting a dialogue, you know, where the outcome of the dialogue is the artifacts that you want, whether it be a piece of analysis or whether it be a Python library or whether it be a technical blog post or whatever. So as part of building that, I've created something called Claudette, which is a library for Claude. I've created something called Cosette, which is a library for OpenAI. They're libraries which are designed to make those APIs much more usable, much easier to use, much more concise. And then I've written AI magic on top of those. And that's been an interesting exercise because I did Claudette first, and I was looking at what Simon Willison did with his fantastic LLM library. And his library is designed around like, let's make something that supports all the LLM inference engines and commercial providers. I thought, okay, what if I did something different, which is like make something that's as Claude friendly as possible and forget everything else. So that's what Claudette was. So for example, one of the really nice things in Claude is prefill. So by telling the assistant that this is what your response started with, there's a lot of powerful things you can take advantage of. So yeah, I created Claudette to be as Claude friendly as possible. And then after I did that, and then particularly with GPT 4.0 coming out, I kind of thought, okay, now let's create something that's as OpenAI friendly as possible. And then I tried to look to see, well, where are the similarities and where are the differences? And now can I make them compatible in places where it makes sense for them to be compatible without losing out on the things that make each one special for what they are. So yeah, those are some of the things I've been working on in that space. And I'm thinking we might launch AI magic via a course called how to solve it with code. The name is based on the classic Polya book, if you know how to solve it, which is, you know, one of the classic math books of all time, where we're basically going to try to show people how to solve challenging problems that they didn't think they could solve without doing a full computer science course, by taking advantage of a bit of AI and a bit of like practical skills, as particularly for this like whole generation of people who are learning to code with and because of ChatGPT. Like I love it, I know a lot of people who didn't really know how to code, but they've created things because they use ChatGPT, but they don't really know how to maintain them or fix them or add things to them that ChatGPT can't do, because they don't really know how to code. And so this course will be designed to show you how you can like either become a developer who can like supercharge their capabilities by using language models, or become a language model first developer who can supercharge their capabilities by understanding a bit about process and fundamentals.Alessio [00:50:19]: Nice. That's a great spoiler. You know, I guess the fourth time you're going to be on learning space, we're going to talk about AI magic. Jeremy, before we wrap, this was just a great run through everything. What are the things that when you next come on the podcast in nine, 12 months, we're going to be like, man, Jeremy was like really ahead of it. Like, is there anything that you see in the space that maybe people are not talking enough? You know, what's the next company that's going to fall, like have drama internally, anything in your mind?Jeremy [00:50:47]: You know, hopefully we'll be talking a lot about fast HTML and hopefully the international community that at that point has come up around that. And also about AI magic and about dialogue engineering. Hopefully dialogue engineering catches on because I think it's the right way to think about a lot of this stuff. What else? Just trying to think about all on the research side. Yeah. I think, you know, I mean, we've talked about a lot of it. Like I think encoder decoder architectures, encoder only architectures, hopefully we'll be talking about like the whole re-interest in BERT that BERT 24 stimulated.Swyx [00:51:17]: There's a safe space model that came out today that might be interesting for this general discussion. One thing that stood out to me with Cartesia's blog posts was that they were talking about real time ingestion, billions and trillions of tokens, and keeping that context, obviously in the state space that they have.Jeremy [00:51:34]: Yeah.Swyx [00:51:35]: I'm wondering what your thoughts are because you've been entirely transformers the whole time.Jeremy [00:51:38]: Yeah. No. So obviously my background is RNNs and LSTMs. Of course. And I'm still a believer in the idea that state is something you can update, you know? So obviously Sepp Hochreiter came up, came out with xLSTM recently. Oh my God. Okay. Another whole thing we haven't talked about, just somewhat related. I've been going crazy for like a long time about like, why can I not pay anybody to save my KV cash? I just ingested the Great Gatsby or the documentation for Starlet or whatever, you know, I'm sending it as my prompt context. Why are you redoing it every time? So Gemini is about to finally come out with KV caching, and this is something that Austin actually in Gemma.cpp had had on his roadmap for years, well not years, months, long time. The idea that the KV cache is like a thing that, it's a third thing, right? So there's RAG, you know, there's in-context learning, you know, and prompt engineering, and there's KV cache creation. I think it creates like a whole new class almost of applications or as techniques where, you know, for me, for example, I very often work with really new libraries or I've created my own library that I'm now writing with rather than on. So I want all the docs in my new library to be there all the time. So I want to upload them once, and then we have a whole discussion about building this application using FastHTML. Well nobody's got FastHTML in their language model yet, I don't want to send all the FastHTML docs across every time. So one of the things I'm looking at doing in AI Magic actually is taking advantage of some of these ideas so that you can have the documentation of the libraries you're working on be kind of always available. Something over the next 12 months people will be spending time thinking about is how to like, where to use RAG, where to use fine-tuning, where to use KV cache storage, you know. And how to use state, because in state models and XLSTM, again, state is something you update. So how do we combine the best of all of these worlds?Alessio [00:53:46]: And Jeremy, I know before you talked about how some of the autoregressive models are not maybe a great fit for agents. Any other thoughts on like JEPA, diffusion for text, any interesting thing that you've seen pop up?Jeremy [00:53:58]: In the same way that we probably ought to have state that you can update, i.e. XLSTM and state models, in the same way that a lot of things probably should have an encoder, JEPA and diffusion both seem like the right conceptual mapping for a lot of things we probably want to do. So the idea of like, there should be a piece of the generative pipeline, which is like thinking about the answer and coming up with a sketch of what the answer looks like before you start outputting tokens. That's where it kind of feels like diffusion ought to fit, you know. And diffusion is, because it's not autoregressive, it's like, let's try to like gradually de-blur the picture of how to solve this. So this is also where dialogue engineering fits in, by the way. So with dialogue engineering, one of the reasons it's working so well for me is I use it to kind of like craft the thought process before I generate the code, you know. So yeah, there's a lot of different pieces here and I don't know how they'll all kind of exactly fit together. I don't know if JEPA is going to actually end up working in the text world. I don't know if diffusion will end up working in the text world, but they seem to be like trying to solve a class of problem which is currently unsolved.Alessio [00:55:13]: Awesome, Jeremy. This was great, as usual. Thanks again for coming back on the pod and thank you all for listening. Yeah, that was fantastic. Get full access to Latent Space at www.latent.space/subscribe

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Pasar de Bash a Zsh fue un auténtico drama. Así como lo estás leyendo. Me resistía a abandonar esa shell que tanto tiempo me había acompañado. Después de un tiempo, me di cuenta que no era para tanto. Al final, los scripts seguiría haciéndolos en Bash, o en Zsh, a mi conveniencia. Y lo cierto, es que han sido muchos mas en Bash, que en Zsh. En este último casi, fue al final de los tiempos cuando quise hacer algunos complementos. Hoy, pasar de Zsh a Fish, no ha supuesto tanto drama para mi. Si, inicialmente, quise resistirme, pero luego todo vino rodado. Así que finalmente le dije adiós a Zsh, y bienvenido al super productivo Fish. En este episodio te cuento mi aventura con Zsh y el porqué del cambio a Fish. Más información, enlaces y notas en https://atareao.es/podcast/559

Pasar de Bash a Zsh fue un auténtico drama. Así como lo estás leyendo. Me resistía a abandonar esa shell que tanto tiempo me había acompañado. Después de un tiempo, me di cuenta que no era para tanto. Al final, los scripts seguiría haciéndolos en Bash, o en Zsh, a mi conveniencia. Y lo cierto, es que han sido muchos mas en Bash, que en Zsh. En este último casi, fue al final de los tiempos cuando quise hacer algunos complementos. Hoy, pasar de Zsh a Fish, no ha supuesto tanto drama para mi. Si, inicialmente, quise resistirme, pero luego todo vino rodado. Así que finalmente le dije adiós a Zsh, y bienvenido al super productivo Fish. En este episodio te cuento mi aventura con Zsh y el porqué del cambio a Fish. Más información, enlaces y notas en https://atareao.es/podcast/559

Como ya te conté hace algún tiempo, Zsh se ha convertido en mi Shell por defecto. Sin embargo, hasta la fecha, he continuado haciendo mis scripts en Bash. Simplemente, porque estoy acostumbrado a utilizar Bash como lenguaje de scripting, entre otras cosas, porque también es el lenguaje de scripting que utilizo habitualmente tanto de forma personal como profesional. Esto no quita que puntualmente haga algún script en Zsh, pero no es lo normal. Sin embargo, el otro día, me topé de nuevo con la realizad de que Zsh no es Bash. No son totalmente compatibles, aunque por poco, la verdad. Más información, enlaces y notas en https://atareao.es/podcast/542

Como ya te conté hace algún tiempo, Zsh se ha convertido en mi Shell por defecto. Sin embargo, hasta la fecha, he continuado haciendo mis scripts en Bash. Simplemente, porque estoy acostumbrado a utilizar Bash como lenguaje de scripting, entre otras cosas, porque también es el lenguaje de scripting que utilizo habitualmente tanto de forma personal como profesional. Esto no quita que puntualmente haga algún script en Zsh, pero no es lo normal. Sin embargo, el otro día, me topé de nuevo con la realizad de que Zsh no es Bash. No son totalmente compatibles, aunque por poco, la verdad. Más información, enlaces y notas en https://atareao.es/podcast/542

Using open source software to get paid for using electricity, automatically formatting your terrible Python code, speeding up Zsh, a couple of ways to get notifications, M1 Macbook Air problems, an epic ThinkPad collection, and more.   Support us on Patreon and get an ad-free RSS feed with early episodes sometimes   Discoveries Control your... Read More

Using open source software to get paid for using electricity, automatically formatting your terrible Python code, speeding up Zsh, a couple of ways to get notifications, M1 Macbook Air problems, an epic ThinkPad collection, and more.   Support us on Patreon and get an ad-free RSS feed with early episodes sometimes   Discoveries Control your... Read More

Topics covered in this episode: Django 5.0 beta 1 released git bash, terminals, and Windows Mastering Integration Testing with FastAPI Reuven Learner has been banned for trading in rare animals (Pythons and Pandas) Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Brian #1: Django 5.0 beta 1 released Django 5.0 release notes supports Python 3.10, 3.11, 3.12 Facet filters in the admin Simplified templates for form field rendering Database-computed default values Database generated model field More options for declaring field choices More Django news Djangonaut Space now accepting applications for our next contributor mentorship cohort Take the Django Developers Survey 2023 Michael #2: git bash, terminals, and Windows See the screenshot Requires Windows 10 Install the Windows Terminal from the Microsoft Store Brian #3: Mastering Integration Testing with FastAPI Alex Jacobs Some great integration testing techniques Focused on FastAPI, but relevant to many frameworks. Mocking authentication Mocking external APIs Fun use of parametrize and indirect fixtures for mocking responses. Mocking MongoDB Mocking AWS S3 Michael #4: Reuven Learner has been banned for trading in rare animals (Pythons and Pandas) via Pat Decker Reuven, like us, teaches Python and Data Sci Tried to advertise his courses (Python and Pandas courses) on Meta Got permanently (life-time) banned for selling rare and endangered animals. Sometimes I really hate these big tech companies My recent beefs have been with app store reviewers and surveillance-based capitalism Extras Brian: Where did everyone go? - Ned Batchelder I do feel like we're more fragmented than before, but I am feeling like we have a community on Mastodon. reminder that Mastodon has text search now On Sunday, I released Ch9, Coverage, as part of The Complete pytest course, specifically part of pytest Working with Projects. It was super fun. I've used coverage a lot since writing the book, for example, I demonstrate branch coverage. It's so much more effective to teach in video than in printed screenshots. Michael: Autin shell enhancer by Ellie Huxtable recommended by recommended by Nik JupyterCon 2023 videos are out More shells follow up from Teemu Hukkanen for “editor like” features Zsh and Bash ruff format and strings, aka format.quote-style = "single" Glyph's programming your computer talk is up. Joke: this is what the experts do

En estos últimos días, he estado actualizando mi terminal Linux. Y no me refiero tanto a Kitty, que como sabes es mi terminal por defecto, sino a todas las herramientas que utilizo junto a Kitty. Herramientas que me proporcionan una mayor productividad, pero, que sobre todo hacen que me sienta mucho más cómodo utilizando la terminal. Así, por ejemplo, he actualizado los complementos de Zsh que utilizo, he modificado algunos scripts, y de paso, he actualizado algunas de estas herramientas. En ese proceso de actualización, me he dado cuenta, de que cada vez hay mas herramientas implementadas en Rust, en mi terminal Linux. Es mas, en los últimos tiempos se han multiplicado como la espuma. Esto me ha hecho pensar que tienes que instalar Rust para exprimir Linux. Y esto es precisamente lo que te quiero contar en este episodio del podcast. Más información, enlaces y notas en https://atareao.es/podcast/527

En estos últimos días, he estado actualizando mi terminal Linux. Y no me refiero tanto a Kitty, que como sabes es mi terminal por defecto, sino a todas las herramientas que utilizo junto a Kitty. Herramientas que me proporcionan una mayor productividad, pero, que sobre todo hacen que me sienta mucho más cómodo utilizando la terminal. Así, por ejemplo, he actualizado los complementos de Zsh que utilizo, he modificado algunos scripts, y de paso, he actualizado algunas de estas herramientas. En ese proceso de actualización, me he dado cuenta, de que cada vez hay mas herramientas implementadas en Rust, en mi terminal Linux. Es mas, en los últimos tiempos se han multiplicado como la espuma. Esto me ha hecho pensar que tienes que instalar Rust para exprimir Linux. Y esto es precisamente lo que te quiero contar en este episodio del podcast. Más información, enlaces y notas en https://atareao.es/podcast/527

In this supper club episode of Syntax, Wes and Scott talk with Colby Fayock about Cloudinary's new AI tools, media flow, removing backgrounds, using AI for video templates, and Colby's stack for creating YouTube content. Show Notes 00:36 Welcome 01:11 Who is Colby Fayock? ColbyFayock.com Colby Fayock (@colbyfayock)on Twitter ColbyFayock - Twitch colbyfayock on GitHub Colby Fayock (@colbyfayock) • Instagram 01:57 What is Cloudinary? Image and Video Upload, Storage, Optimization and CDN 03:03 What's with the space jellyfish? 03:52 How is Cloudinary using AI for the web? Developer resources for using images and videos in your apps 09:54 What is media flow? 13:00 Who is the target audience for AI tools from Cloudinary? 17:03 Removing backgrounds Remove Background from Image for Free – remove.bg iPhone Messages stickers: How to make and use them - 9to5Mac 21:14 Cloudinary's Video API ascorbic/unpic-img: Multi-framework responsive image component 22:44 Function calling in OpenAI 26:22 How do you deal with the random generation of AI? 29:00 What are the community SDKs for Cloudinary? 37:04 What's your process for creating content for YouTube? 42:49 Supper Club Questions Open Broadcaster Software | OBS Facecam Pro – Elgato Recut — Automatic Video Editor Night Owl - Visual Studio Marketplace iTerm2 - macOS Terminal Replacement Oh My Zsh - a delightful & open source framework for Zsh 51:40 SIIIIICK ××× PIIIICKS ××× ××× SIIIIICK ××× PIIIICKS ××× Ready To Drink Cold Brew Coffee | Trader Joe's Shameless Plugs Colby Fayock on YouTube Tweet us your tasty treats Scott's Instagram LevelUpTutorials Instagram Wes' Instagram Wes' Twitter Wes' Facebook Scott's Twitter Make sure to include @SyntaxFM in your tweets Wes Bos on Bluesky Scott on Bluesky Syntax on Bluesky

In this supper club episode of Syntax, Wes and Scott talk with Colby Fayock about Cloudinary's new AI tools, media flow, removing backgrounds, using AI for video templates, and Colby's stack for creating YouTube content. Show Notes 00:36 Welcome 01:11 Who is Colby Fayock? ColbyFayock.com Colby Fayock (@colbyfayock)on Twitter ColbyFayock - Twitch colbyfayock on GitHub Colby Fayock (@colbyfayock) • Instagram 01:57 What is Cloudinary? Image and Video Upload, Storage, Optimization and CDN 03:03 What's with the space jellyfish? 03:52 How is Cloudinary using AI for the web? Developer resources for using images and videos in your apps 09:54 What is media flow? 13:00 Who is the target audience for AI tools from Cloudinary? 17:03 Removing backgrounds Remove Background from Image for Free – remove.bg iPhone Messages stickers: How to make and use them - 9to5Mac 21:14 Cloudinary's Video API ascorbic/unpic-img: Multi-framework responsive image component 22:44 Function calling in OpenAI 26:22 How do you deal with the random generation of AI? 29:00 What are the community SDKs for Cloudinary? 37:04 What's your process for creating content for YouTube? 42:49 Supper Club Questions Open Broadcaster Software | OBS Facecam Pro – Elgato Recut — Automatic Video Editor Night Owl - Visual Studio Marketplace iTerm2 - macOS Terminal Replacement Oh My Zsh - a delightful & open source framework for Zsh 51:40 SIIIIICK ××× PIIIICKS ××× ××× SIIIIICK ××× PIIIICKS ××× Ready To Drink Cold Brew Coffee | Trader Joe's Shameless Plugs Colby Fayock on YouTube Tweet us your tasty treats Scott's Instagram LevelUpTutorials Instagram Wes' Instagram Wes' Twitter Wes' Facebook Scott's Twitter Make sure to include @SyntaxFM in your tweets Wes Bos on Bluesky Scott on Bluesky Syntax on Bluesky

Beginning with Catalina (10.15), Apple changed the default login shell from Bash to Zsh. Many admins, ourselves included, have been slow to move to this new shell. Why should we? It turns out there are few advantages to Zsh over Bash. In this session we'll show off a few ways we've been able to leverage Zsh to write better scripts, and even regain some of what we lost when Python went away. ---------------------------------  Launchpad Podcast is hosted by Rocketman Tech where we discuss recent news, updates and happenings in the Jamf and Apple world. Always relevant and always casual, we'll have a Keynote speaker, discuss current LaunchPad events, and invite group discussion, questions and topic requests throughout the ~1 hour meeting.  

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Encendido remoto de PC, ZSH, modo markdown

En el episodio 442 del podcast titulado creo que tengo tiling-hopping, y una marcha atrás, te comenté que había decidido regresar a Bash, y te expliqué algunas de las razones para volver a Bash. Básicamente, se resumía en que no terminaba de encontrarme y por el otro lado la compatibilidad que todo el ecosistema de Servidores, Raspberry, etc. Sin embargo, no ha pasado ni mes y medio, y me he dado cuenta de que, para el uso que yo le estoy dando, Zsh se adecua mucho mas a mi flujo de trabajo, así que he decidido dejarme de tonterías y ponerme serio. Así que se va Bash y viene Zsh, o como quería haber titualado este episodio del podcast, donde dije Bash, digo Zsh. Sin embargo, no he vuelto a Zsh de la misma forma en la que me encontraba, y esto es precisamente lo que quería contarte, mi regreso a lo especialito. Me he dejado parte del lastre atrás. --- Más información en las notas del podcast sobre Bash y viene Zsh o donde dije Bash…

En el episodio 442 del podcast titulado creo que tengo tiling-hopping, y una marcha atrás, te comenté que había decidido regresar a Bash, y te expliqué algunas de las razones para volver a Bash. Básicamente, se resumía en que no terminaba de encontrarme y por el otro lado la compatibilidad que todo el ecosistema de Servidores, Raspberry, etc. Sin embargo, no ha pasado ni mes y medio, y me he dado cuenta de que, para el uso que yo le estoy dando, Zsh se adecua mucho mas a mi flujo de trabajo, así que he decidido dejarme de tonterías y ponerme serio. Así que se va Bash y viene Zsh, o como quería haber titualado este episodio del podcast, donde dije Bash, digo Zsh. Sin embargo, no he vuelto a Zsh de la misma forma en la que me encontraba, y esto es precisamente lo que quería contarte, mi regreso a lo especialito. Me he dejado parte del lastre atrás. --- Más información en las notas del podcast sobre Bash y viene Zsh o donde dije Bash…

In this episode, I had the absolute pleasure of talking with Mihalis Tsoukalos, a long-time Twitter friend and someone who's given me loads of advice, about software development. He shared with me so much about his journey with C-based languages, particularly Python, C, Go, & Rust. He talked about Linux shells including Bash and Zsh (and of course the excellent Oh My Zsh project). On the flip side, he shared why he's no fan of Java and Microsoft Windows, preferring almost all things Linux and Unix. Then, he finished up by talking about file formats such as Latex, Markdown, and AsciiDoc (my favourite format), the importance of software documentation, and what he believes it takes to become a professional developer. You don't want to miss this closing aspect of the episode!Some key takeaways are: Start by writing small command-line utilities, re-implementing the ones that you know. Then, gradually take on bigger, more complex ones. Keep writing code and keep improving each time. Read a lot of code, experiment even more, talk to other developers, and fail better each time. Even if you only learn a little something, it's something more than you knew before. Software documentation is very important. To learn Rust, you really have to do it full-time. He's a big fan of Go because of the speed, size of the standard library, and because it's a simple and fast language. Links Mastering Go, 3rd edition (written by Mihalis) Go Systems Programming (written by Mihalis) Latex AsciiDoc Markdown Oh My Zsh Guests: Mihalis Tsoukalos (@mactsouk).Hosted By: Matthew Setter.Thanks for tuning in to Free the Geek. If you'd like to be a guest on the podcast or know someone who'd make a great guest, email me: matthew@matthewsetter.com. This podcast is produced by Matthew Setter. SupportIf you want to support the show, you can always buy me a coffee. I'd greatly appreciate your financial support. ★ Support this podcast ★

Shell was ist das? Bash, Powershell, Fish, ZSH... verschiedene Shells. Direkt effizienter arbeiten als Data Engineer und Data Scientist - Mit verschiedenen Shells

FULL SHOW NOTES ►► https://tuxdigital.com/podcasts/destination-linux/dl-287/ Chapters: 00:00 = Welcome to DL 287 00:49 = Community Feedback: 2D Animation Software on Linux 06:22 = DigitalOcean: Cloud Platform ( https://do.co/tux2022 ) 07:44 = Customizing Your Terminal to be a 1337 h@x0r 30:54 = PSA for Beginners about the Terminal 33:15 = Bash vs ZSH vs Fish on […]

In the beginning was the command line. Actually, before that were punch cards and paper tape. But at Multics and RSTS and DTSS came out, programmers and users needed a way to interface with the computer through the teletypes and other terminals that appeared in the early age of interactive computing. Those were often just a program that sat on a filesystem eventually as a daemon, listening for input on keyboards. This was one of the first things the team that built Unix needed, once they had a kernel that could compile. And from the very beginning it was independent of the operating system. Due to the shell's independence from the underlying operating system, numerous shells have been developed during Unix's history, albeit only a few have attained widespread use. Shells are also referred to as Command-Line Interpreters (or CLIs), processes commands a user sends from a teletype, then a terminal. This provided a simpler interface for common tasks, rather than interfacing with the underlying C programming. Over the years, a number of shells have come and gone. Some of the most basic and original commands came from Multics, but the shell as we know it today was introduced as the Thompson shell in the first versions of Unix. Ken Thompson introduced the first Unix shell in 1971 with the Thompson Shell, the ancestor of the shell we still find in /bin/sh. The shell ran in the background and allowed for a concise syntax for redirecting the output of commands to one another. For example, pass the output to a file with > or read input from a file with

Advice on building Docker containers for Shiny applications, an R-centric tutorial on fundamentals with shell, and tips on evaluating GitHub activity for contributors. Episode Links This issue's curator: Tony ElHabr (@TonyElHabr (https://twitter.com/TonyElHabr)) UseR!2022: Best Practices for Shiny Apps with Docker and More (https://hosting.analythium.io/user-2022-best-practicesfor-shiny-apps-with-docker-and-more/) Shell vs R Fundamentals – From Syntax to Control Structures with Zsh & BASH (https://morphoscape.wordpress.com/2022/06/24/shell-vs-r-fundamentals-from-syntax-to-control-structures-with-zsh-amp-bash/) Evaluating GitHub Activity for Contributors (https://ropensci.org/blog/2022/07/01/evaluating-github-activity-for-contributors/) Entire issue available at rweekly.org/2022-W27 (https://rweekly.org/2022-W27.html) Supplement Resources Hosting Data Apps: https://hosting.analythium.io slim.ai: https://www.slim.ai/ {dockerfiler} - Easy Dockerfile creation from R: https://github.com/ThinkR-open/dockerfiler Data Science at the Command Line: https://datascienceatthecommandline.com

Allen Wyma talks with Chris Krycho, host of the now-ended New Rustacean podcast about learning the Rust programming language. Contributing to Rustacean Station Rustacean Station is a community project; get in touch with us if you'd like to suggest an idea for an episode or offer your services as a host or audio editor! Twitter: @rustaceanfm Discord: Rustacean Station Github: @rustacean-station Email: hello@rustacean-station.org Timestamps [@1:08] - Chris' background and introduction [@4:33] - Chris' current career and projects [@12:17] - Rust and WebAssembly [@19:35] - Chris' podcasting plans [@23:47] - Chris' podcasting preparation and processes [@36:02] - Lessons and insights coming from podcasting [@48:08] - ZSH vs Fish [@53:12] - Picking out potential podcast guests and making great interviews [@57:12] - Chris' opinion and comparison on the different programming languages [@1:07:33] - Chris' parting thoughts and future plans Other Resources Chris's Twitter Credits Intro Theme: Aerocity Audio Editing: Plangora Hosting Infrastructure: Jon Gjengset Show Notes: Plangora Hosts: Allen Wyma

About ChrisChris is a robotics engineer turned cloud security practitioner. From building origami robots for NASA, to neuroscience wearables, to enterprise software consulting, he is a passionate builder at heart. Chris is a cofounder of Common Fate, a company with a mission to make cloud access simple and secure.Links: Common Fate: https://commonfate.io/ Granted: https://granted.dev Twitter: https://twitter.com/chr_norm TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: Let's face it, on-call firefighting at 2am is stressful! So there's good news and there's bad news. The bad news is that you probably can't prevent incidents from happening, but the good news is that incident.io makes incidents less stressful and a lot more valuable. incident.io is a Slack-native incident management platform that allows you to automate incident processes, focus on fixing the issues and learn from incident insights to improve site reliability and fix your vulnerabilities. Try incident.io, recover faster and sleep more.Corey: This episode is sponsored in part by Honeycomb. When production is running slow, it's hard to know where problems originate. Is it your application code, users, or the underlying systems? I've got five bucks on DNS, personally. Why scroll through endless dashboards while dealing with alert floods, going from tool to tool to tool that you employ, guessing at which puzzle pieces matter? Context switching and tool sprawl are slowly killing both your team and your business. You should care more about one of those than the other; which one is up to you. Drop the separate pillars and enter a world of getting one unified understanding of the one thing driving your business: production. With Honeycomb, you guess less and know more. Try it for free at honeycomb.io/screaminginthecloud. Observability: it's more than just hipster monitoring.Corey: Welcome to Screaming in the Cloud. I'm Corey Quinn. It doesn't matter where you are on your journey in cloud—you could never have heard of Amazon the bookstore—and you encounter AWS and you spin up an account. And within 20 minutes, you will come to the realization that everyone in this space does. “Wow, logging in to AWS absolutely blows goats.”Today, my guest, obviously had that reaction, but unlike most people I talked to, decided to get up and do something about it. Chris Norman is the co-founder of Common Fate and most notably to how I know him is one of the original authors of the tool, Granted. Chris, thank you so much for joining me.Chris: Hey, Corey, thank you for having me.Corey: I have done podcasts before; I have done a blog post on it; I evangelize it on Twitter constantly, and even now, it is challenging in a few ways to explain holistically what Granted is. Rather than trying to tell your story for you, when someone says, “Oh, Granted, that seems interesting and impossible to Google for in isolation, so therefore, we know it's going to be good because all the open-source projects with hard to find names are,” what is Granted and what does it do?Chris: Granted is a command-line tool which makes it really easy for you to get access and assume roles when you're working with AWS. For me, when I'm using Granted day-to-day, I wake up, go to my computer—I'm working from home right now—crack open the MacBook and I log in and do some development work. I'm going to go and start working in the cloud.Corey: Oh, when I start first thing in the morning doing development work and logging into the cloud, I know. All right, I'm going to log in to AWS and now I know that my day is going downhill from here.Chris: [laugh]. Exactly, exactly. I think maybe the best days are when you don't need to log in at all. But when you do, I go and I open my terminal and I run this command. Using Granted, I ran this assume command and it authenticates me with single-sign-on into AWS, and then it opens up a console window in a particular account.Now, you might ask, “Well, that's a fairly standard thing.” And in fact, that's probably the way that the console and all of the tools work by default with AWS. Why do you need a third-party tool for this?Corey: Right. I've used a bunch of things that do varying forms of this and unlike Granted, you don't see me gushing about them. I want to be very clear, we have no business relationship. You're not sponsoring anything that I do. I'm not entirely clear on what your day job entails, but I have absolutely fallen in love with the Granted tool, which is why I'm dragging you on to this show, kicking and screaming, mostly to give me an excuse to rave about it some more.Chris: [laugh]. Exactly. And thank you for the kind words. And I'd say really what makes it special or why I've been so excited to be working on it is that it makes this access, particularly when you're working with multiple accounts, really, really easy. So, when I run assume and I open up that console window, you know, that's all fine and that's very similar to how a lot of the other tools and projects that are out there work, but when I want to open that second account and that second console window, maybe because I'm looking at like a development and a staging account at the same time, then Granted allows me to view both of those simultaneously in my browser. And we do that using some platform sort of tricks and building into the way that the browser works.Corey: Honestly, one of the biggest differences in how you describe what Granted is and how I view it is when you describe it as a CLI application because yes, it is that, but one of the distinguishing characteristics is you also have a Firefox extension that winds up leveraging the multi-container functionality extension that Firefox has. So, whenever I wind up running a single command—assume with a-c' flag, then I give it the name of my AWS profile, it opens the web console so I can ClickOps my heart's content inside of a tab that is locked to a container, which means I can have one or two or twenty different AWS accounts and/or regions up running simultaneously side-by-side, which is basically impossible any other way that I've ever looked at it.Chris: Absolutely, yeah. And that's, like, the big differentiating factor right now between Granted and between this sort of default, the native experience, if you're just using the AWS command line by itself. With Granted, you can—with these Firefox containers, all of your cookies, your profile, everything is all localized into that one container. It's actually it's a privacy features that are built into Firefox, which keeps everything really separate between your different profiles. And what we're doing with Granted is that we make it really easy to open a specific profiles that correspond with different AWS profiles that you're using.So, you'd have one which could be your development account, one which could be production or staging. And you can jump between these and navigate between them just as separate tabs in your browser, which is a massive improvement over, you know, what I've previously had to use in the past.Corey: The thing that really just strikes me about this is first, of course, the functionality and the rest, so I saw this—I forget how I even came across it—and immediately I started using it. On my Mac, it was great. I started using it when I was on the road, and it was less great because you built this thing in Go. It can compile and install on almost anything, but there were some assumptions that you had built into this in its early days that did not necessarily encompass all of the use cases that I use. For example, it hadn't really occurred to you that some lunatic would try and only use an iPad when they're on the road, so they have to be able to run this to get federated login links via SSHing into an EC2 instance running somewhere and not have it open locally.You seemed almost taken aback when I brought it up. Like, “What lunatic would do that?” Like, “Hi, I'm such a lunatic. Let's talk about this.” And it does that now, and it's awesome. It does seem to me though, and please correct me if I'm wrong on this assumption slash assessment that this is first and foremost aimed at desktop users, specifically people running Mac on the desktop, is that the genesis of it?Chris: It is indeed. And I think part of the cause behind that is that we originally built a tool for ourselves. And as we were building things and as we were working using the cloud, we were running things—you know, we like to think that we're following best practices when we're using AWS, and so we'd set up multiple accounts, we'd have a special account for development, a separate one for staging, a separate one for production, even internal tools that we would build, we would go and spin up an individual account for those. And then you know, we had lots of accounts. and to go and access those really easily was quite difficult.So, we definitely, we built it for ourselves first and I think that that's part of when we released it, it actually a little bit of cause for some of the initial problems. And some of the feedback that we had was that it's great to build tools for yourself, but when you're working in open-source, there's a lot of different diversity with how people are using things.Corey: We take different approaches. You want to try to align with existing best practices, whereas I am a loudmouth white guy who works in tech. So, what I do definitionally becomes a best practice in the ecosystem. It's easier to just comport with the ones that are already existing that smart people put together rather than just trying to competence your way through it, so you took a better path than I did.But there's been a lot of evolution to Granted as I've been using it for a while. I did a whole write-up on it and that got a whole bunch of eyes onto the project, which I can now admit was a nefarious plan on my part because popping into your community Slack and yelling at you for features I want was all well and good, but let's try and get some people with eyes on this who are smarter than me—which is not that high of a bar when it comes to SSO, and IAM, and federated login, and the rest—and they can start finding other enhancements that I'll probably benefit from. And sure enough, that's exactly what happened. My sneaky plan has come to fruition. Thanks for being a sucker, I guess. I mean—[laugh] it worked. I'm super thrilled by the product.Chris: [laugh]. I guess it's a great thing I think that the feedback and particularly something that's always been really exciting is just seeing new issues come through on GitHub because it really shows the kinds of interesting use cases and the kinds of interesting teams and companies that are using Granted to make their lives a little bit easier.Corey: When I go to the website—which again is impossible to Google—the website for those wondering is granted.dev. It's short, it's concise, I can say it on a podcast and people automatically know how to spell it. But at the top of the website—which is very well done by the way—it mentions that oh, you can, “Govern access to breakglass roles with Common Fate Cloud,” and it also says in the drop shadow nonsense thing in the upper corner, “Brought to you by Common Fate,” which is apparently the name of your company.So, the question I'll get to in a second is what does your company do, but first and foremost, is this going to be one of those rug-pull open-source projects where one day it's, “Oh, you want to log into your AWS accounts? Insert quarter to continue.” I'm mostly being a little over the top with that description, but we've all seen things that we love turn into molten garbage. What is the plan around this? Are you about to ruin this for the rest of us once you wind up raising a round or something? What's the deal?Chris: Yeah, it's a great question, Corey. And I think that to a degree, releasing anything like this that sits in the access workflow and helps you assume roles and helps you day-to-day, you know, we have a responsibility to uphold stability and reliability here and to not change things. And I think part of, like, not changing things includes not [laugh] rug-pulling, as you've alluded to. And I think that for some companies, it ends up that open-source becomes, like, a kind of a lead-generation tool, or you end up with, you know, now finally, let's go on add another login so that you have to log into Common Fate to use Granted. And I think that, to be honest, a tool like this where it's all about improving the speed of access, the incentives for us, like, it doesn't even make sense to try and add another login for to try to get people to, like, to say, login to Common Fate because that would make your signing process for AWS take even longer than it already does.Corey: Yeah, you decided that you know, what's the biggest problem? Oh, you can sleep at night, so let's go ahead and make it even worse, by now I want you to be this custodian of all my credentials to log into all of my accounts. And now you're going to be critical path, so if you're down, I'm not able to log into anything. And oh, by the way, I have to trust you with full access to my bank stuff. I just can't imagine that is a direction that you would be super excited about diving head-first into.Chris: No, no. Yeah, certainly not. And I think that the, you know, building anything in this space, and with what we're doing with Common Fate, you know, we're building a cloud platform to try to make IAM a little bit easier to work with, but it's really sensitive around granting any kind of permission and I think that you really do need that trust. So, trying to build trust, I guess, with our open-source projects is really important for us with Granted and with this project, that it's going to continue to be reliable and continue to work as it currently does.Corey: The way I see it, one of the dangers of doing anything that is particularly open-source—or that leans in the direction of building in Amazon's ecosystem—it leads to the natural question of, well, isn't this just going to be some people say stolen—and I don't think those people understand how open-source works—by AWS themselves? Or aren't they going to build something themselves at AWS that's going to wind up stomping this thing that you've built? And my honest and remarkably cynical answer is that, “You have built a tool that is a joy to use, that makes logging into AWS accounts streamlined and efficient in a variety of different patterns. Does that really sound like something AWS would do?” And followed by, “I wish they would because everyone would benefit from that rising tide.”I have to be very direct and very clear. Your product should not exist. This should be something the provider themselves handles. But nope. Instead, it has to exist. And while I'm glad it does, I also can't shake the feeling that I am incredibly annoyed by the fact that it has to.Chris: Yeah. Certainly, certainly. And it's something that I think about a little bit. I like to wonder whether there's maybe like a single feature flag or some single sort of configuration setting in AWS where they're not allowing different tabs to access different accounts, they're not allowing this kind of concurrent access. And maybe if we make enough noise about Granted, maybe one of the engineers will go and flick that switch and they'll just enable it by default.And then Granted itself will be a lot less relevant, but for everybody who's using AWS, that'll be a massive win because the big draw of using Granted is mainly just around being able to access different accounts at the same time. If AWS let you do that out of the box, hey, that would be great and, you know, I'd have a lot less stuff to maintain.Corey: Originally, I had you here to talk about Granted, but I took a glance at what you're actually building over at Common Fate and I'm about to basically hijack slash derail what probably is going to amount the rest of this conversation because you have a quick example on your site for by developers, for developers. You show a quick Python script that tries to access a S3 bucket object and it's denied. You copy the error message, you paste it into what you're building over a Common Fate, and in return, it's like, “Oh. Yeah, this is the policy that fixes it. Do you want us to apply it for you?”And I just about fell out of my chair because I have been asking for this explicit thing for a very long time. And AWS doesn't do it. Their IAM access analyzer claims to. Like, “Oh, just go look at CloudTrail and see what permissions it uses and we'll build a policy to scope it down.” “Okay. So, it's S3 access. Fair enough. To what object or what bucket?” “Guess,” is what it tells you there.And it's, this is crap. Who thinks this is a good user experience? You have built the thing that I wish AWS had built in natively. Because let's be honest here, I do what an awful lot of people do and overscope permissions massively just because messing around with the bare minimum set of permissions in many cases takes more time than building the damn thing in the first place.Chris: Oh, absolutely. Absolutely. And in fact, this—was a few years ago when I was consulting—I had a really similar sort of story where one of the clients that we were working with, the CTO of this company, he was needing to grant us access to AWS and we were needing to build a particular service. And he said, “Okay, can you just let me know the permissions that you will need and I'll go and deploy the role for this.” And I came back and I said, “Wait. I don't even know the permissions that I'm going to need because the damn thing isn't even built yet.”So, we went sort of back and forth around this. And the compromise ended up just being you know, way too much access. And that was sort of part of the inspiration for, you know, really this whole project and what we're building with Common Fate, just trying to make that feedback loop around getting to the right level of permissions a lot faster.Corey: Yeah, I am just so overwhelmingly impressed by the fact that you have built—and please don't take this as a criticism—but a set of very simple tools. Not simple in the terms of, “Oh, that's, like, three lines of bash, and a fool could write that on a weekend.” No. Simple in the sense of it solves a problem elegantly and well and it's straightforward—well, straightforward as anything in the world of access control goes—to wrap your head around exactly what it does. You don't tend to build these things by sitting around a table brainstorming with someone you met at co-founder dating pool or something and wind up figuring out, “Oh, we should go and solve that. That sounds like a billion-dollar problem.”This feels very much like the outcome of when you're sitting around talking to someone and let's start by drinking six beers so we become extraordinarily honest, followed immediately by let's talk about what sucks. What pisses you off the most? It feels like this is sort of the low-hanging fruit of things that upset people when it comes to AWS. I mean, if things had gone slightly differently, instead of focusing on AWS bills, IAM was next on my list of things to tackle just because I was tired of smacking my head into it.This is very clearly a problem space that you folks have analyzed deeply, worked within, and have put a lot of thought into. I want to be clear, I've thrown a lot of feature suggestions that you for Granted from start to finish. But all of them have been around interface stuff and usability and expanding use cases. None of them have been, “Well, that seems screamingly insecure.” Because it hasn't been.Chris: [laugh].Corey: It has been effective, start to finish, I think that from a security posture, you make terrific choices, in many cases better than ones I would have made a starting from scratch myself. Everything that I'm looking at in what you have built is from a position of this is absolutely amazing and it is transformative to my own workflows. Now, how can we improve it?Chris: Mmm. Thank you, Corey. And I'll say as well, maybe around the security angle, that one of the goals with Granted was to try and do things a little bit better than the default way that AWS does them when it comes to security. And it's actually been a bit of a source for challenges with some of the users that we've been working with with Granted because one of the things we wanted to do was encrypt the SSO token. And this is the token that when you sign in to AWS, kind of like, it allows you to then get access to all of the rest of the accounts.So, it's like a pretty—it's a short-lived token, but it's a really sensitive one. And you know, by default, it's just stored in plain text on your disk. So, we dump to a file and, you know, anything that can go and read that, they can go and get it. It's also a little bit hard to revoke and to lock people out. There's not really great workflows around that on AWS's side.So, we thought, “Okay, great. One of the goals for Granted can be that we will go and store this in your keychain in your system and we'll work natively with that.” And that's actually been a cause for a little bit of a hassle for some users, though, because by doing that and by storing all of this information in the keychain, it's actually broken some of the integrations with the rest of the tooling, which kind of expects tokens and things to be in certain places. So, we've actually had to, as part of dealing with that with Granted, we've had to give users the ability to opt out for that.Corey: DoorDash had a problem. As their cloud-native environment scaled and developers delivered new features, their monitoring system kept breaking down. In an organization where data is used to make better decisions about technology and about the business, losing observability means the entire company loses their competitive edge. With Chronosphere, DoorDash is no longer losing visibility into their applications suite. The key? Chronosphere is an open-source compatible, scalable, and reliable observability solution that gives the observability lead at DoorDash business, confidence, and peace of mind. Read the full success story at snark.cloud/chronosphere. That's snark.cloud slash C-H-R-O-N-O-S-P-H-E-R-E.Corey: That's why I find this so, I think, just across the board, fantastic. It's you are very clearly engaged with your community. There's a community Slack that you have set up for this. And I know, I know, too many Slacks; everyone has this problem. This is one of those that is worth hanging in, at least from my perspective, just because one of the problems that you have, I suspect, is on my Mac it's great because I wind up automatically updating it to whatever the most recent one is every time I do a brew upgrade.But on the Linux side of the world, you've discovered what many of us have discovered, and that is that packaging things for Linux is a freaking disaster. The current installation is, “Great. Here's basically a curl bash.” Or, “Here, grab this tarball and install it.” And that's fine, but there's no real way of keeping that updated and synced.So, I was checking the other day, oh wow, I'm something like eight versions behind on this box. But it still just works. I upgraded. Oh, wow. There's new functionality here. This is stuff that's actually really handy. I like this quite a bit. Let's see what else we can do.I'm just so impressed, start to finish, by just how receptive you've been to various community feedbacks. And as well—I want to be very clear on this point, too—I've had folks who actually know what they're doing in an InfoSec sense look at what you're up to, and none of them had any issues of note. I'm sure that they have a pile of things like, with that curl bash, they should really be doing a GPG check. Yes, yes, fine. Whatever. If that's your target threat model, okay, great. Here in reality-land for what I do, this is awesome.And they don't seem to have any problems with, “Oh, yeah. By the way, sending analytics back up”—which, okay, fine, whatever. “And it's not disclosing them.” Okay, that's bad. “And it's including the contents of your AWS credentials.”Ahhhh. I did encounter something that was doing that on the back-end once. [cough]—Serverless Framework—sorry, something caught in my throat for a second.Chris: [laugh].Corey: No faster way I can think of to erode trust in that. But everything you're doing just makes sense.Chris: Oh, I do remember that. And that was a little bit of a fiasco, really, around all of that, right? And it's great to hear actually around that InfoSec folks and security people being, you know, not unhappy, I guess, with a tool like this. It's been interesting for me personally. We've really come from a practitioner's background.You know, I wouldn't call myself a security engineer at all. I would call myself as a sometimes a software developer, I guess. I have been hacking my way around Go and definitely learning a lot about how the cloud has worked over the past seven, eight years or so, but I wouldn't call myself a security engineer, so being very cautious around how all of these things work. And we've really tried to defer to things like the system keychain and defer to things that we know are pretty safe and work.Corey: The thing that I also want to call out as well is that your licensing is under the MIT license. This is not one of those, “Oh, you're required to wind up doing a bunch of branding stuff around it.” And, like some people say, “Oh, you have to own the trademark for all of these things.” I mean, I'm not an expert in international trademark law, let's be very clear, but I also feel that trademarking a term that is already used heavily in the space such as the word ‘Granted,' feels like kind of an uphill battle. And let's further be clear that it doesn't matter what you call this thing.In fact, I will call attention to an oddity that I've encountered a fair bit. After installing it, the first thing you do is you run the command ‘granted.' That sets it up, it lets you configure your browser, what browser you want to use, and it now supports standard out for that headless, EC2 use case. Great. Awesome. Love it. But then the other binary that ships with it is Assume. And that's what I use day-to-day. It actually takes me a minute sometimes when it's been long enough to remember that the tool is called Granted and not Assume what's up with that?Chris: So, part of the challenge that we ran into when we were building the Granted project is that we needed to export some environment variables. And these are really important when you're logging into AWS because you have your access key, your secret key, your session token. All of those, when you run the assume command, need to go into the terminal session that you called it. This doesn't matter so much when you're using the console mode, which is what we mentioned earlier where you can open 100 different accounts if you want to view all of those at the same time in your browser. But if you want to use it in your terminal, we wanted to make it look as really smooth and seamless as possible here.And we were really inspired by this approach from—and I have to shout them out and kind of give credit to them—a tool called AWSume—they're spelled A-W-S-U-M-E—Python-based tool that they don't do as much with single-sign-on, but we thought they had a really nice, like, general approach to the way that they did the scripting and aliasing. And we were inspired by that and part of that means that we needed to have a shell script that called this executable, which then will export things back out into the shell script. And we're doing all this wizardry under the hood to make the user experience really smooth and seamless. Part of that meant that we separated the commands into granted and assume and the other part of the naming for everything is that I felt Granted had a far better ring to it than calling the whole project Assume.Corey: True. And when you say assume, is it AWS or not? I've used the AWSume project before; I've used AWS Vault out of 99 Designs for a while. I've used—for three minutes—the native AWS SSO config, and that is just trash. Again, they're so good at the plumbing, so bad at the porcelain, I think is the criticism that I would levy toward a lot of this stuff.Chris: Mmm.Corey: And it's odd to think there's an entire company built around just smoothing over these sharp, obnoxious edges, but I'm saying this as someone who runs a consultancy and have five years that just fixes the bill for this one company. So, there's definitely a series of cottage industries that spring up around these things. I would be thrilled, on some level, if you wound up being completely subsumed by their product advancements, but it's been 15 years for a lot of this stuff and we're still waiting. My big failure mode that I'm worried about is that you never are.Chris: Yeah, exactly, exactly. And it's really interesting when you think about all of these user experience gaps in AWS being opportunities for, I guess, for companies like us, I think, trying to simplify a lot of the complexity for things. I'm interested in sort of waiting for a startup to try and, like, rebuild the actual AWS console itself to make it a little bit faster and easier to use.Corey: It's been done and attempted a bunch of different times. The problem is that the console is a lot of different things to a lot of different people, and as you step through that, you can solve for your use case super easily. “Yeah, what do I care? I use RDS, I use some VPC nonsense, and I use EC2. The end.” “Great. What about IAM?”Because I promise you're using that whether you know it or not. And okay, well, I'm talking to someone else who's DynamoDB, and someone else is full-on serverless, and someone else has more money than sense, so they mostly use SageMaker, and so on and so forth. And it turns out that you're effectively trying to rebuild everything. I don't know if that necessarily works.Chris: Yeah, and I think that's a good point around maybe while we haven't seen anything around that sort of space so far. You go to the console, and you click down, you see that list of 200 different services and all of those have had teams go and actually, like, build the UI and work with those individual APIs. Yeah.Corey: Any ideas as far as what's next for features on Granted?Chris: I think that, for us, it's continuing to work with everybody who's using it, and with a focus of stability and performance. We actually had somebody in the community raise an issue because they have an AWS config file that's over 7000 lines long. And I kind of pity that person, potentially, for their day-to-day. They must deal with so much complexity. Granted is currently quite slow when the config files get very big. And for us, I think, you know, we built it for ourselves; we don't have that many accounts just yet, so working to try to, like, make it really performant and really reliable is something that's really important.Corey: If you don't mind a feature request while we're at it—and I understand that this is more challenging than it looks like—I'm willing to fund this as a feature bounty that makes sense. And this also feels like it might be a good first project for a very particular type of person, I would love to get tab completion working in Zsh. You have it—Chris: Oh.Corey: For Fish because there's a great library that automatically populates that out, but for the Zsh side of it, it's, “Oh, I should just wind up getting Zsh completion working,” and I fell down a rabbit hole, let me tell you. And I come away from this with the perception of yeah, I'm not going to do it. I have not smart enough to check those boxes. But a lot of people are so that is the next thing I would love to see. Because I will change my browser to log into the AWS console for you, but be damned if I'm changing my shell.Chris: [laugh]. I think autocomplete probably should be higher on our roadmap for the tool, to be honest because it's really, like, a key metric and what we're focusing on is how easy is it to log in. And you know, if you're not too sure what commands to use or if we can save you a few keystrokes, I think that would be the, kind of like, reaching our goals.Corey: From where I'm sitting, you definitely have. I really want to thank you for taking the time to not only build this in the first place, but also speak with me about it. If people want to learn more, where's the best place to find you?Chris: So, you can find me on Twitter, I'm @chr_norm, or you can go and visit granted.dev and you'll have a link to join the Slack community. And I'm very active on the Slack.Corey: You certainly are, although I will admit that I fall into the challenge of being in just the perfectly opposed timezone from you and your co-founder, who are in different time zones to my understanding; one of you is on Australia and one of you was in London; you're the London guy as best I'm aware. And as a result, invariably, I wind up putting in feature requests right when no one's around. And, for better or worse, in the middle of the night is not when I'm usually awake trying to log into AWS. That is Azure time.Chris: [laugh]. Yeah, no, we don't have the US time zone properly covered yet for our community support and help. But we do have a fair bit of the world timezone covered. The rest of the team for Common Fate is all based in Australia and I'm out here over in London.Corey: Yeah. I just want to thank you again, for just being so accessible and, like, honestly receptive to feedback. I want to be clear, there's a way to give feedback and I do strive to do it constructively. I didn't come crashing into your Slack one day with a, “You know what your problem is?” I prefer to take the, “This is awesome. Here's what I think would be even better. Does that make sense?” As opposed to the imperious demands and GitHub issues and whatnot? It's, “I'd love it if it did this thing. Doesn't do this thing. Can you please make it do this thing?” Turns out that's the better way to drive change. Who knew?Chris: Yeah. [laugh]. Yeah, definitely. And I think that one of the things that's been the best around our journey with Granted so far has been listening to feedback and hearing from people how they would like to use the tool. And a big thank you to you, Corey, for actually suggesting changes that make it not only better for you, but better for everybody else who's using Granted.Corey: Well, at least as long as we're using my particular byzantine workload patterns in some way, or shape, or form, I'll hear that. But no, it's been an absolute pleasure and I really want to thank you for your time as well.Chris: Yeah, thank you for having me.Corey: Chris Norman, co-founder of Common Fate, as well as one of the two primary developers originally behind the Granted project that logs you into AWS without you having to lose your mind. I'm Cloud Economist Corey Quinn and this is Screaming in the Cloud. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you've hated this podcast, please leave a five-star review on your podcast platform of choice along with an angry, incensed, raging comment that talks about just how terrible all of this is once you spend four hours logging into your AWS account by hand first.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.Announcer: This has been a HumblePod production. Stay humble.

Guest Julia Ferraioli Panelists Richard Littauer | Justin Dorfman | Alyssa Wright Show Notes Hello and welcome to Sustain! The podcast where we talk about sustaining open source for the long haul. Today, we have joining us as our guest, Julia Ferraioli, who's an open source human, co-founded Open Source Stories, and has been part of the Sustain community for a while. Our conversations today take us through learning about Julia's background, what Open Source Stories is, and how she quantifies a black swan open source. We also learn about two camps of people who work on open source that Julia encountered, a detailed explanation of what “matters” means, and what Julia does when she works on standardizing open source information. Go ahead and download this episode now to hear more! [00:01:40] Julia talks about her history and how she got to where she is today. [00:02:43] What is Open Source Stories? [00:06:05] We find out the story how Julia and Amanda Casari ended up working together on Open Source Stories. [00:10:48] Julia explains how she quantifies a black swan open source and what she worries about in terms of recognition. [00:15:11] Alyssa asks Julia if there are people that are contributing to open source projects that don't feel recognized and acknowledged and if there's an invisible community that we're trying to not only grow and diversify. [00:16:32] Justin shares a story about Guist, a designer he worked on a Zsh project with. [00:18:07] Julia brings up how you can sponsor a developer on GitHub, but wonders if you can sponsor a designer on GitHub. [00:20:00] Alyssa asks Julia why we have to recognize people in order to sustain the open source software communities. [00:23:35] Richard brings up the topic of recognition of individuals and how do we make sure that recognition is equal across the board, and Julia shares her thoughts. [00:26:57] Julia explains two camps she's encountered, the camp where the contribution matters and the camp where the whole person matters. [00:30:03] We find out what “matters” means to the whole ecosystem, what matters to a sub ecosystem, and what matters to a project. [00:32:42] What does Julia work on when she works on standardizing open source information? [00:35:18] Find out where you can follow Julia online. Quotes [00:08:14] “The conversations that we have tend to lead to some really interesting explorations and one of our talks was about black swans and open source.” [00:10:51] “I think it's completely subjective.” [00:13:22] “We've made really good strides in recognizing contributions outside of code such as technical writing, triage, and code reviews.” [00:14:15] “It's really important as more and more companies are relying on open source because it makes it into products.” Spotlight [00:36:22] Justin's spotlight is The Non-Code Contributor newsletter. [00:36:57 Alyssa's spotlight is Wikipedia for quick searches and seeing people outside and meeting each other in person. [00:37:50] Richard's spotlight is Marquette University and the J.R.R. Tolkien Fandom Oral History Collection. [00:38:24] Julia's spotlight is a paper called Chalk: Materials and Concepts in Mathematics Research. Links SustainOSS (https://sustainoss.org/) SustainOSS Twitter (https://twitter.com/SustainOSS?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor) SustainOSS Discourse (https://discourse.sustainoss.org/) podcast@sustainoss.org (mailto:podcast@sustainoss.org) Julia Ferraioli LinkedIn (https://www.linkedin.com/in/juliaferraioli) Julia Ferraioli Twitter (https://twitter.com/juliaferraioli) Julia Ferraioli Website (https://www.juliaferraioli.com/) Julia Ferraioli LeadDev (https://leaddev.com/search/results?search-index=julia+ferraioli) Open Source Stories (https://www.opensourcestories.org/) Vermont Complex Systems Center (https://vermontcomplexsystems.org/) StoryCorps (https://storycorps.org/) Sustain Open Source Design Podcast (https://sosdesign.sustainoss.org/) Amanda Casari Twitter (https://twitter.com/amcasari?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor) Z shell (https://en.wikipedia.org/wiki/Z_shell) guist.eth Twitter (https://twitter.com/g_uist) Black Swan theory (https://en.wikipedia.org/wiki/Black_swan_theory) Bananas Are Berries? (Stanford Magazine) (https://stanfordmag.org/contents/bananas-are-berries) The Non-Code Contributor By Justin Dorfman (https://www.getrevue.co/profile/tncc?via=twitter-profile) The J.R.R. Tolkien Fandom Oral History Collection (https://www.marquette.edu/library/archives/tolkienfandom.php) [Chalk: Materials and Concepts in Mathematics Research by Michael J. Barany and Donald MacKenzie](https://www.sps.ed.ac.uk/sites/default/files/assets/pdf/Chalk0.pdf)_ The Non-Code Contributor- Issue #32 by Justin Contributor (https://www.getrevue.co/profile/tncc/issues/the-non-code-contributor-issue-32-1120100) Credits Produced by Richard Littauer (https://www.burntfen.com/) Edited by Paul M. Bahr at Peachtree Sound (https://www.peachtreesound.com/) Show notes by DeAnn Bahr Peachtree Sound (https://www.peachtreesound.com/) Special Guest: Julia Ferraioli.

Estaba repasando los últimos títulos de los podcast y voy de cambio en cambio y tiro porque me toca. En estos últimos tiempos he ido sustituyéndolo todo. He cambiado de editor de Vim a NeoVim, de shell de Bash a Zsh, de tiling window manager de bspwm a sway (que mola mucho mas el nombre). Incluso he cambiado de distribución en el escritorio de Ubuntu a Manjaro, en los servidores sigue Ubuntu. Pero faltaba una pieza fundamental, una pieza imprescindible el ordenador. Así que he reemplazado mi Dell xps-13 por un Slimbook One con AMD Ryzen 9. Si he pasado de portátil a un ¿sobremesa? (no se si le puede llamar así). --- Puedes seguir las publicaciones en Twitter

Estaba repasando los últimos títulos de los podcast y voy de cambio en cambio y tiro porque me toca. En estos últimos tiempos he ido sustituyéndolo todo. He cambiado de editor de Vim a NeoVim, de shell de Bash a Zsh, de tiling window manager de bspwm a sway (que mola mucho mas el nombre). Incluso he cambiado de distribución en el escritorio de Ubuntu a Manjaro, en los servidores sigue Ubuntu. Pero faltaba una pieza fundamental, una pieza imprescindible el ordenador. Así que he reemplazado mi Dell xps-13 por un Slimbook One con AMD Ryzen 9. Si he pasado de portátil a un ¿sobremesa? (no se si le puede llamar así). --- Puedes seguir las publicaciones en Twitter

After solving a moral dilemma in our particular kind of way, Mike dishes on some ambitious plans that might kick off a new era of development for him.

Hace algunos meses que publiqué en el canal de Youtube sobre como personalizar el prompt de la terminal, utilizando Zsh, Oh-My-Zsh y un tema como es PowerLevel10k. Por aquel entonces estaba realmente satisfecho con la personalización que me proporcionaba el tema PowerLevel10k, porque con solo mirar el prompt en el directorio que me encontrara, era capaz de obtener una gran cantidad de información, sin necesidad de pulsar una tecla. No solo esto, sino que además quedaba realmente resultón. Realmente estaba muy satisfecho con el resultado obtenido. Sin embargo, y a la vez, por aquel entonces también probé, starship, el promp definitivo (al menos por ahora) que viene a sustituir el tema que he estado utilizando hata el momento. --- Mas información en las notas del podcast sobre Un prompt para gobernarlos a todos Linux, Windows y MacOS

Hace algunos meses que publiqué en el canal de Youtube sobre como personalizar el prompt de la terminal, utilizando Zsh, Oh-My-Zsh y un tema como es PowerLevel10k. Por aquel entonces estaba realmente satisfecho con la personalización que me proporcionaba el tema PowerLevel10k, porque con solo mirar el prompt en el directorio que me encontrara, era capaz de obtener una gran cantidad de información, sin necesidad de pulsar una tecla. No solo esto, sino que además quedaba realmente resultón. Realmente estaba muy satisfecho con el resultado obtenido. Sin embargo, y a la vez, por aquel entonces también probé, starship, el promp definitivo (al menos por ahora) que viene a sustituir el tema que he estado utilizando hata el momento. --- Mas información en las notas del podcast sobre Un prompt para gobernarlos a todos Linux, Windows y MacOS

Where did my bash go says James! Well I am swimming with Fish over here says Frank! We explore what the heck is going on in terminals on all of the different operating systems and how to get them setup to your liking. Register for James's webinar with Syncfusion on .NET MAUI & Blazor Hybrid: https://bit.ly/3qV6Fij Fish Shell: https://fishshell.com/ Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

Show Synopsis: In Season 05 Episode 02, we discuss Crypto, Braggots, and ZSH. Working from home. What we are drinking: Melona Let's talk about zsh Crypto over the break TON Avian RavenCoin Cosmos Atom     We have a twitter @BeerandBroad  Get 25 dollars in credit at Ting. This Episode of Beer and Broadband is licensed under the Creative Commons Attribution License   Creative Commons License

Where did my bash go says James! Well I am swimming with Fish over here says Frank! We explore what the heck is going on in terminals on all of the different operating systems and how to get them setup to your liking. Register for James's webinar with Syncfusion on .NET MAUI & Blazor Hybrid: https://bit.ly/3qV6Fij Fish Shell: https://fishshell.com/ Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

Siempre me tomo a la ligera aquello de el tiempo vuela. Sin embargo, lo cierto, es que ya han pasado aproximadamente unos cuatro meses desde que adopté Zsh, como mi shell de trabajo, y Oh My Zsh como el framework que lo acompaña. Ha llegado el momento de echar la vista atrás, hacer una valoración y contarte mi experiencia con este shell y este framework. Ha llegado el momento de contarte mi experiencia con Zsh y Oh My Zsh, y, replantearse en su caso, si continuar con esta pareja, o recular. Desde luego, no quiero que estés con la duda hasta haber leído las notas del podcast, o hasta haber escuchado el mismo. La valoración de mi experiencia con Zsh y Oh My Zsh no puede ser mas positiva, y en este sentido, te tengo que decir, que definitivamente me quedo con ambos, al menos durante los próximos tiempos. --- Más información en las notas del podcas sobre mi experiencia con Zsh y Oh My Zsh tras cuatro meses de uso

We all love the Hollywood portrayal of the "brilliant programmer" who can step in and just crush it at a moment's notice. We've probably all fantasized about being that programmer. But, that's not how people work. And it's not how teams work. Highly effective developers don't just "crush it" - they cultivate good habits that they then apply consistently, day-in and day-out, for years. This week, the crew discusses which habits make - or break - the most effective developers.Triumphs & FailuresAdam's Triumph - After struggling to get several Java-based feature flag services configured correctly in ColdFusion (which is one layer of indirection above Java), Adam decided to pull the ultimate power move and created his own open-source, ColdFusion-based feature flag library: Semaphore. While still in active development, it's already feeling very "feature complete". Pull-requests welcome!Ben's Failure - Without being able to point at anything in particular, this week kind of just kicked his butt. Without a Product Manager (PM) or an Engineering Manager (EM) on his team, he's felt as though noone is "protecting" him or his people. And, even though an EM may not have actually made a the week better, there's an emotional cost to feeling so exposed. One saving grace, however, is that he received a stellar review from someone on the Customer Facing Team (CFT). So, he must be doing something right.Carol's Triumph - She totally survived a mercury-based allergic reaction to something she ate! That which doesn't kill Carol only makes her bolder when it comes to that sweet, sweet shellfish.Tim's Triumph - He recently built a custom solution for one of his customers. However, he built it with clean boundaries and multi-tenancy in mind. Which means, now that he's successfully rolled-it-out to his first customer, he's ready to cash-in on that work by using the same solution as an upsell opportunity for his other customers. He's even gone back and refactored some of the architecture using the Clean Code tips from our earlier book review.Notes & LinksSemaphore - A minimalist Feature Flag engine for CFML apps.Taffy - A low friction, extremely simple way to build REST-ful end-points in your CFML apps.FW/1 - A family of small, lightweight, convention-over-configuration frameworks, primarily for CFML apps.Oh My Zsh - A delightful, open source, community-driven framework for managing your Zsh configuration.Follow the show! Our website is workingcode.dev and we're @WorkingCodePod on Twitter and Instagram. Or, leave us a message at (512) 253-2633‬ (that's 512-253-CODE). New episodes drop weekly on Wednesday.And, if you're feeling the love, support us on Patreon.

Oh My Zsh! - https://ohmyz.sh/GitHub - https://github.com/ohmyzsh/ohmyzsh/ ZSH - ( Z Shell) is an extended Bourne Shell (sh) with features from other shells like Bash, Korn Shell, and tsch (tee shell) macOS Catalina made Zsh default back in 2019 replacing Bash Oh My Zsh is an open-source, community-driven framework for managing your zsh configuration.Plugins - Git, Docker, VS Code, OSX, programming languagesThemes - customize the look and feel of ZSH

In this episode of The Linux Cast, Matt and Ricky talk about their first experiences with ZSH and Fish, the two most popular replacements for Bash. 

Picking a compiler for debuggability, how to port Rust apps to FreeBSD, what the point of Docker is on FreeBSD/Solaris, another EuroBSDcon recap, and network manager control in OpenBSD This episode was brought to you by Headlines Compile once, Debug twice: Picking a compiler for debuggability, part 1 of 3 (https://backtrace.io/blog/compile-once-debug-twice-picking-a-compiler-for-debuggability-1of3/) An interesting look into why when you try to debug a crash, you can often find all of the useful information has been ‘optimized out' Have you ever had an assert get triggered only to result in a useless core dump with missing variable information or an invalid callstack? Common factors that go into selecting a C or C++ compiler are: availability, correctness, compilation speed and application performance. A factor that is often neglected is debug information quality, which symbolic debuggers use to reconcile application executable state to the source-code form that is familiar to most software engineers. When production builds of an application fail, the level of access to program state directly impacts the ability for a software engineer to investigate and fix a bug. If a compiler has optimized out a variable or is unable to express to a symbolic debugger how to reconstruct the value of a variable, the engineer's investigation process is significantly impacted. Either the engineer has to attempt to recreate the problem, iterate through speculative fixes or attempt to perform prohibitively expensive debugging, such as reconstructing program state through executable code analysis. Debug information quality is in fact not proportionally related to the quality of the generated executable code and wildly varies from compiler to compiler. Different compilers emit debug information at varying levels of quality and accuracy. However, certain optimizations will certainly impact any debugger's ability to generate accurate stack traces or extract variable values. In the above program, the value of argv is extracted and then the program is paused. The ckprloadptr function performs a read from the region of memory pointed to by argv, in a manner that prevents the compiler from performing optimization on it. This ensures that the memory access occurs and for this reason, the value of argv must be accessible by the time ckprloadptr is executed. When compiled with gcc, the debugger fails to find the value of the variable. The compiler determines that the value of argv is no longer needed after the ckprload_ptr operation and so doesn't bother paying the cost of saving the value. Some optimizations generate executable code whose call stack cannot be sufficiently disambiguated to reconcile a call stack that mirrors that of the source program. Two common culprits for this are tail call optimization and basic block commoning. In another example If the program receives a first argument of 1, then function is called with the argument of "a". If the program receives a first argument of 2, then function is called with the argument of "b". However, if we compile this program with clang, the stack traces in both cases are identical! clang informs the debugger that the function f invoked the function("b") branch where x = 2 even if x = 1. Though some optimizations will certainly impact the accuracy of a symbolic debugger, some compilers simply lack the ability to generate debug information in the presence of certain optimizations. One common optimization is induction variable elimination. A variable that's incremented or decremented by a constant on every iteration of a loop or derived from another variable that follows this pattern, is an induction variable. Coupled with other optimizations, the compiler is then able to generate code that doesn't actually rely on a dedicated counter variable “i” for maintaining the current offset into “buffer”. As you can see, i is completely optimized out. The compiler determines it doesn't have to pay the cost of maintaining the induction variable i. It maintains the pointer in the register %rdi. The code is effectively rewritten to something closer to this: So the for loop, changes into a while loop, with a condition of the end of the input We have shown some common optimizations that may get in the way of the debuggability of your application and demonstrated a disparity in debug information quality across two popular compilers. In the next blog post of this series, we will examine how gcc and clang stack up with regards to debug information quality across a myriad of synthetic applications and real world applications. Looking forward to part 2 *** This is how you can port your rust application to FreeBSD (https://medium.com/@andoriyu/this-is-how-you-can-port-your-rust-application-to-freebsd-7d3e9f1bc3df) This is how you can port your rust application to FreeBSD The FreeBSD Ports Collection is the way almost everyone installs applications (“ports”) on FreeBSD. Like everything else about FreeBSD, it is primarily a volunteer effort. It is important to keep this in mind when reading this document. In FreeBSD, anyone may submit a new port, or volunteer to maintain an existing unmaintained port. No special commit privilege is needed. For this guide I will use fd tool written by David Peter as example project. Prerequisites FreeBSD installation (VM is fine) Local ports tree (done via svn) portlint (located at devel/portlint) poudriere (located at ports-mgmt/poudriere)[optional] Getting ports tree When you install FreeBSD opt-out of the ports tree. Install svn: pkg install svn svn checkout https://svn.freebsd.org/ports/head /usr/ports Poudriere Sometimes you might get asked to show poudriere build log, sometimes you won't. It's good to have anyway. If you choose to use poudriere, use ZFS. There are plenty of guides on the subject. FreeBSD Porter's Handbook is the most complete source of information on porting to FreeBSD. Makefile Whole porting process in most cases is writing one Makefile. I recommend doing something like this. Here is the one I wrote for fd: Port metadata Each port must have one primary category in case of fd it will be sysutils, therefore it's located in /usr/ports/systuils/fd. PORTNAME= fd CATEGORIES= sysutils Since this port conflicts with other util named fd I specified package suffix as: PKGNAMESUFFIX= -find and indicate conflict: CONFLICTS_INSTALL= fd-[0-9]*. That means to install it from packages user will have to type: pkg install fd-find Licenses This section is different for every port, but in case of fd it's pretty straightforward: LICENSE= MIT APACHE20 LICENSE_COMB= dual Since fd includes the text of licenses you should do this as well: LICENSE_FILE_MIT= ${WRKSRC}/LICENSE-MIT LICENSE_FILE_APACHE20= ${WRKSRC}/LICENSE-APACHE Distfiles FreeBSD has a requirement that all ports must allow offline building. That means you have specified which files are needed to be downloaded. Luckily we now have helpers to download GitHub sources directly from GitHub: USE_GITHUB= yes GH_ACCOUNT= sharkdp Since PORTNANE is fd it will try to download sources for sharkdp/fd. By default it's going to download tag: ${DISTVERSIONPREFIX}${DISTVERSION}${DISTVERSIONSUFFIX} fd uses v as the prefix, therefore we need to specify: DISTVERSIONPREFIX= v. It's also possible to specify GH_TAGNAME in case tag name doesn't match that pattern. Extra packages There are very few rust projects that are standalone and use no crates dependencies. It's used to be PITA to make it work offline, but now cargo is a first class citizen in ports: USES= cargo CARGO_CRATES= aho-corasick-0.6.3 atty-0.2.3 # and so goes on Yes, you have to specify each dependency. Luckily, there is a magic awk script that turns Cargo.lock into what you need. Execute make cargo-crates in the port root. This will fail because you're missing checksum for the original source files: make makesum make cargo-crates This will give you what you need. Double check that result is correct. There is a way to ignore checksum error, but I can't remember… Execute make makesum again. CARGO_OUT If. build.rs relies on that you have to change it. fd allows you to use SHELLCOMPLETIONSDIR to specify where completions go, while ripgrep doesn't. In our case we just specify SHELLCOMPLETIONSDIR: SHELL_COMPLETIONS_DIR= ${WRKDIR}/shell-completions-dir CARGO_ENV= SHELL_COMPLETIONS_DIR=${SHELL_COMPLETIONS_DIR} PLIST FreeBSD is very strict about files it's installing and it won't allow you to install random files that get lost. You have to specify which files you're installing. In this case, it's just two: PLIST_FILES= bin/fd man/man1/fd.1.gz Note that sources for fd have uncompressed man file, while here it's listed as compressed. If port installs a lot of files, specify them in pkg-plist like here. To actually install them: post-install: @${STRIP_CMD} ${STAGEDIR}${PREFIX}/bin/fd ${INSTALL_MAN}${WRKSRC}/doc/fd.1 ${STAGEDIR}${MAN1PREFIX}/man/man1 Shell completions clap-rs can generate shell completions for you, it's usually handled by build.rs script. First, we need to define options: OPTIONS_DEFINE= BASH FISH ZSH # list options OPTIONS_DEFAULT= BASH FISH ZSH # select them by default BASH_PLIST_FILES= etc/bash_completion.d/fd.bash-completion FISH_PLIST_FILES= share/fish/completions/fd.fish ZSH_PLIST_FILES= share/zsh/site-functions/_fd To actually install them: post-install-BASH-on: @${MKDIR} ${STAGEDIR}${PREFIX}/etc/bash_completion.d ${INSTALL_DATA} ${SHELL_COMPLETIONS_DIR}/fd.bash-completion ${STAGEDIR}${PREFIX}/etc/bash_completion.d post-install-FISH-on: @${MKDIR} ${STAGEDIR}${PREFIX}/share/fish/completions ${INSTALL_DATA} ${SHELL_COMPLETIONS_DIR}/fd.fish ${STAGEDIR}${PREFIX}/share/fish/completions post-install-ZSH-on: @${MKDIR} ${STAGEDIR}${PREFIX}/share/zsh/site-functions ${INSTALL_DATA} ${SHELL_COMPLETIONS_DIR}/_fd ${STAGEDIR}${PREFIX}/share/zsh/site-functions Bonus round - Patching source code Sometimes you have to patch it and send the patch upstream. Merging it upstream can take awhile, so you can patch it as part of the install process. An easy way to do it: Go to work/ dir Copy file you want to patch and add .orig suffix to it Edit file you want to patch Execute make makepatch in port's root Submitting port First, make sure portlint -AC doesn't give you any errors or warnings. Second, make sure poudriere can build it on both amd64 and i386. If it can't?—?you have to either fix it or mark port broken for that arch. Follow this steps like I did steps. If you have any issues you can always ask your question in freebsd-ports on freenode try to find your answer in porter's handbook before asking. Conference Recap: EuroBSDCon 2017 Recap (https://www.freebsdfoundation.org/blog/conference-recap-eurobsdcon-2017-recap/) The location was wonderful and I loved sneaking out and exploring the city when I could. From what I heard, it was the largest BSD conference in history, with over 320 attendees! Each venue is unique and draws many local BSD enthusiasts, who normally wouldn't be able to travel to a conference. I love having the chance to talk to these people about how they are involved in the projects and what they would like to do. Most of the time, they are asking me questions about how they can get more involved and how we can help. Magical is how I would describe the conference social event. To stand in front of the dinner cruise on the Seine, with the Eiffel Tower standing tall, lit up in the night, while working – talking to our community members, was incredible. But, let me start at the beginning. We attend these conferences to talk to our community members, to find out what they are working on, determine technologies that should be supported in FreeBSD, and what we can do to help and improve FreeBSD. We started the week with a half-day board meeting on Wednesday. BSD conferences give us a chance to not only meet with community members around the world, but to have face-to-face meetings with our team members, who are also located around the world. We worked on refining our strategic direction and goals, determining what upcoming conferences we want FreeBSD presence at and who can give FreeBSD talks and workshops there, discussed current and potential software development projects, and discussed how we can help raise awareness about and increase the use of FreeBSD in Europe. Thursday was the first day of the FreeBSD developer summit, led by our very own Benedict Reuschling. He surprised us all by having us participate in a very clever quiz on France. 45 of us signed into the software, where he'd show the question on the screen and we had a limited amount of time to select our answers, with the results listed on the screen. It was actually a lot of fun, especially since they didn't publicize the names of the people who got the questions wrong. The lucky or most knowledgeable person on France, was des@freebsd.org. Some of our board members ran tutorials in parallel to the summit. Kirk McKusick gave his legendary tutorial, An Introduction to the FreeBSD Open-Source Operating System , George Neville-Neil gave his tutorial, DTrace for Developers, and Benedict Reuschling gave a tutorial on, Managing BSD systems with Ansible. I was pleased to have two chairs from ACM-W Europe run an “Increasing Diversity in the BSDs” BoF for the second year in a row. We broke up into three groups to discuss different gender bias situations, and what we can do to address these types of situations, to make the BSD projects more diverse, welcoming, and inclusive. At the end, people asked that we continue these discussions at future BSD conferences and suggested having an expert in the field give a talk on how to increase the diversity in our projects. As I mentioned earlier, the social dinner was on a boat cruising along the Seine. I had a chance to talk to community members in a more social environment. With the conference being in France, we had a lot of first time attendees from France. I enjoyed talking to many of them, as well as other people I only get to see at the European conferences. Sunday was full of more presentations and conversations. During the closing session, I gave a short talk on the Foundation and the work we are doing. Then, Benedict Reuschling, Board Vice President, came up and gave out recognition awards to four FreeBSD contributors who have made an impact on the Project. News Roundup Playing with the pine64 (https://chown.me/blog/playing-with-the-pine64.html) Daniel Jakots writes in his blog about his experiences with his two pine64 boards: Finding something to install on it 6 weeks ago, I ordered two pine64 units. I didn't (and still don't) have much plan for them, but I wanted to play with some cheap boards. I finally received them this week. Initially I wanted to install some Linux stuff on it, I didn't have much requirement so I thought I would just look what seems to be easy and/or the best supported systemd flavour. I headed over their wiki. Everything seems either not really maintained, done by some random people or both. I am not saying random people do bad things, just that installing some random things from the Internet is not really my cup of tea. I heard about Armbian (https://www.armbian.com/pine64/) but the server flavour seems to be experimental so I got scared of it. And sadly, the whole things looks like to be alot undermanned. So I went for OpenBSD because I know the stuff and who to har^Wkindly ask for help. Spoiler alert, it's boring because it just works. Getting OpenBSD on it I downloaded miniroot62.fs, dd'ed it on the micro SD card. I was afraid I'd need to fiddle with some things like sysutils/dtb because I don't know what I would have needed to do. That's because I don't know what it does and for this precise reason I was wrong and I didn't need to do anything. So just dd the miniroot62.fs and you can go to next checkpoint. I plugged an HDMI cable, ethernet cable and the power, it booted, I could read for 10 seconds but then it got dark. Of course it's because you need a serial console. Of course I didn't have one. I thought about trying to install OpenBSD blindly, I could have probably succeeded with autoinstall buuuuuut… Following some good pieces of advice from OpenBSD people I bought some cp2102 (I didn't try to understand what it was or what were the other possibilities, I just wanted something that would work :D). I looked how to plug the thing. It appears you can plug it on two different places but if you plug it on the Euler bus it could power a bit the board so if you try to reboot it, it would then mess with the power disruption and could lead a unclean reboot. You just need to plug three cables: GND, TXD and RXD. Of course, the TXD goes on the RXD pin from the picture and the RXD goes on the TXD pin. Guess why I'm telling you that! That's it Then you can connect with the usual $ cu -dl /dev/cuaU0 -s 115200 What's the point of Docker on FreeBSD or Solaris? (http://blog.frankleonhardt.com/2017/whats-the-point-of-docker-on-freebsd-or-solaris/) Penguinisters are very keen on their docker, but for the rest of us it may be difficult to see what the fuss is all about – it's only been around a few years and everyone's talking about it. And someone asked again today. What are we missing? Well docker is a solution to a Linux (and Windows) problem that FreeBSD/Solaris doesn't have. Until recently, the Linux kernel only implemented the original user isolation model involving chroot. More recent kernels have had Control Groups added, which are intended to provide isolation for a group of processes (namespaces). This came out of Google, and they've extended to concept to include processor resource allocation as one of the knobs, which could be a good idea for FreeBSD. The scheduler is aware of the JID of the process it's about to schedule, and I might take a look in the forthcoming winter evenings. But I digress. So if isolation (containerisation in Linux terms) is in the Linux kernel, what is Docker bringing to the party? The only thing I can think of is standardisation and an easy user interface (at the expense of having Python installed). You might think of it in similar terms to ezjail – a complex system intended to do something that is otherwise very simple. To make a jail in FreeBSD all you need do is copy the files for your system to a directory. This can even be a whole server's system disk if you like, and jails can run inside jails. You then create a very simple config file, giving the jail a name, the path to your files and an what IP addresses to pass through (if any) and you're done. Just type “service jail nameofjal start”, and off it goes. Is there any advantage in running Docker? Well, in a way, there is. Docker has a repository of system images that you can just install and run, and this is what a lot of people want. They're a bit like virtual appliances, but not mind-numbingly inefficient. You can actually run docker on FreeBSD. A port was done a couple of years ago, but it relies on the 64-bit Linux emulation that started to appear in 10.x. The newer the version of FreeBSD the better. Docker is in ports/sysutils/docker-freebsd. It makes uses of jails instead of Linux cgroups, and requires ZFS rather than UFS for file system isolation. I believe the Linux version uses Union FS but I could be completely wrong on that. The FreeBSD port works with the Docker hub repository, giving you access to thousands of pre-packaged system images to play with. And that's about as far as I've ever tested it. If you want to run the really tricky stuff (like Windows) you probably want full hardware emulation and something like Xen. If you want to deploy or migrate FreeBSD or Solaris systems, just copy a new tarball in to the directory and go. It's a non-problem, so why make it more complicated? Given the increasing frequency Docker turns up in conversations, it's probably worth taking seriously as Linux applications get packaged up in to images for easy access. Jails/Zones may be more efficient, and Docker images are limited to binary, but convenience tends to win in many environments. Network Manager Control for OpenBSD (http://www.vincentdelft.be/post/post_20171023) I propose you a small script allowing you to easily manage your networks connections. This script is integrated within the openbox dynamic menus. Moreover, it allow you to automatically have the connections you have pre-defined based. I was frustrated to not be able to swap quickly from one network interface to an another, to connect simply and quickly to my wifi, to my cable connection, to the wifi of a friend, ... Every time you have to type the ifconfig commands, .... This is nice, but boring. Surely, when you are in a middle of a presentation and you just want a quick connection to your mobile in tethering mode. Thanks to OpenBSD those commands are not so hard, but this frustrate me to not be able to do it with one click. Directly from my windows environment. Since I'm using Openbox, from a menu of openbox. So, I've looked around to see what is currently existing. One tool I've found was netctl (https://github.com/akpoff/netctl). The idea is to have a repository of hostname.if files ready to use for different cases. The idea sounds great, but I had some difficulties to use it. But what annoys me the most, is that it modify the current hostname.if files in /etc. To my eyes, I would avoid to modify those files because they are my working basis. I want to rely on them and make sure that my network will be back to a normal mode after a reboot. Nevertheless, if I've well understood netctl, you have a feature where it will look for the predefined network config matching the environment where you are. Very cool. So, after having played with netctl, look for alternative on internet, I've decided to create nmctl. A small python script which just perform the mandatory network commands. 1. nmctl: a Network Manager Control tool for OpenBSD Nmctl a small tool that allow you to manage your network connections. Why python ? Just because it's the easiest programming language for me. But I should maybe rewrite it in shell, more standard in the OpenBSD world than python. 1.1. download and install I've put nmctl on my sourceforge account here (https://sourceforge.net/p/nmctl/code/ci/master/tree/) You can dowload the last version here (https://sourceforge.net/p/nmctl/code/ci/master/tarball) To install you just have to run: make install (as root) The per-requists are: - having python2.7 installed - Since nmctl must be run as root, I strongly recommend you to run it via doas (http://man.openbsd.org/doas.conf.5). 1.2. The config file First you have to create a config and store it in /etc/nmctl.conf. This file must respect few rules: Each block must starts with a line having the following format: ''':''' Each following lines must start by at least one space. Those lines have more or less the same format as for hostname.if. You have to create a block with the name "open". This will be used to establish a connection to the Open Wifi around you (in restaurant for example) The order of those elements is important. In case you use the -restart option, nmctl will try each of those network configs one after one until it can ping www.google.com. (if you wan to ping something else, you can change it in the python script if you want). You can use external commands. Just preced them with the "!". You have macors. Macros allow you to perform some actions. The 2 currently implemented are '''''' and ''''''. You can use keywords. Currently the only one implemented is "dhcp" Basically you can put all commands that nmctl will apply to the interface to which those commands are referring to. So, you will always have "ifconfig ". Check the manpage of ifconfig to see how flexible command is. You have currently 2 macros: - which refers to the "nwid " when you select an Open Wifi with the -open option of nmctl. - is a macro generating a random mac address. This is useful test a dhcp server for example. The keyword "dhcp" will trigger a command like "dhclient ". 1.3. Config file sample. Let me show you one nmctl.conf example. It speaks by itself. ``` # the name open is required for Open wifi. # this is the interface that nmctl will take to establish a connection # We must put the macro . This is where nmctl will put the nwid command # and the selected openwifi selected by the parameter --open open:iwn0 !route flush -wpa dhcp cable:em0 !route flush dhcp lgg4:iwn0 !route flush nwid LGG4s_8114 wpakey aanotherpassword dhcp home:iwn0 !route flush nwid Linksys19594 wpakey apassword dhcp college:iwn0 !route flush nwid john wpakey haahaaaguessme dhcp cable_fixip:em0 !route flush inet 192.168.3.3 netmask 255.255.255.0 !route add -host default 192.168.3.1 # with this network interface I'm using the macro # which will do what you guess it will do :-) cable_random:em0 !route flush lladdr dhcp ``` In this config we have several cable's networks associated with my interface "em0" and several wifi networks associated with my wireless interface "iwn0". You see that you can switch from dhcp, to fixed IP and even you can play with the random mac address macro. Thanks to the network called "open", you can connect to any open wifi system. To do that, just type ''' nmctl --open ''' So, now, with just one command you can switch from one network configuration to an another one. That's become cool :-). 2. Integration with openbox Thanks to the dynamic menu feature of oenbox[sic], you can have your different pre-defined networks under one click of your mouse. For that, you just have to add, at the most appropriate place for you, the following code in your ./config/openbox/menu.xml In this case, you see the different networks as defined in the config file just above. 3. Automatically identify your available connection and connect to it in one go But the most interesting part, is coming from a loop through all of your defined networks. This loop is reachable via the -restart option. Basically the idea is to loop from the first network config to the last and test a ping for each of them. Once the ping works, we break the loop and keep this setting. Thus where ever you are, you just have to initiate a nmctl -restart and you will be connected to the network you have defined for this place. There is one small exception, the open-wifis. We do not include them in this loop exercise. Thus the way you define your config file is important. Since the network called "open" is dedicated to "open wifi", it will not be part of this scan exercise. I propose you keep it at the first place. Then, in my case, if my mobile, called lgg4, is open and visible by my laptop, I will connect it immediately. Second, I check if my "home wifi" is visible. Third, if I have a cable connected on my laptop, I'm using this connection and do a dhcp command. Then, I check to see if my laptop is not viewing the "college" wifi. ? and so on until a ping command works. If you do not have a cable in your laptop and if none of your pre-defined wifi connections are visible, the scan will stop. 3.1 examples No cable connected, no pre-defined wifi around me: t420:~$ time doas nmctl -r nwids around you: bbox2-d954 0m02.97s real 0m00.08s user 0m00.11s system t420:~$ t420:~$ I'm at home and my wifi router is running: ``` t420:~$ time doas nmctl -r nwids around you: Linksys19594 bbox2-d954 ifconfig em0 down: 0 default fw done fw 00:22:4d:ac:30:fd done nas link#2 done route flush: 0 ifconfig iwn0 nwid Linksys19594 ...: 0 iwn0: no link ........... sleeping dhclient iwn0: 0 Done. PING www.google.com (216.58.212.164): 56 data bytes 64 bytes from 216.58.212.164: icmp_seq=0 ttl=52 time=12.758 ms --- www.google.com ping statistics --- 1 packets transmitted, 1 packets received, 0.0% packet loss round-trip min/avg/max/std-dev = 12.758/12.758/12.758/0.000 ms ping -c1 -w2 www.google.com: 0 0m22.49s real 0m00.08s user 0m00.11s system t420:~$ ``` I'm at home but tethering is active on my mobile: ``` t420:~$ t420:~$ time doas nmctl -r nwids around you: Linksys19594 bbox2-d954 LGG4s8114 ifconfig em0 down: 0 default fw done fw 00:22:4d:ac:30:fd done nas link#2 done route flush: 0 ifconfig iwn0 nwid LGG4s8114 ...: 0 iwn0: DHCPDISCOVER - interval 1 iwn0: DHCPDISCOVER - interval 2 iwn0: DHCPOFFER from 192.168.43.1 (a0:91:69:be:10:49) iwn0: DHCPREQUEST to 255.255.255.255 iwn0: DHCPACK from 192.168.43.1 (a0:91:69:be:10:49) iwn0: bound to 192.168.43.214 -- renewal in 1800 seconds dhclient iwn0: 0 Done. ping: Warning: www.google.com has multiple addresses; using 173.194.69.99 PING www.google.com (173.194.69.99): 56 data bytes 64 bytes from 173.194.69.99: icmp_seq=0 ttl=43 time=42.863 ms --- www.google.com ping statistics --- 1 packets transmitted, 1 packets received, 0.0% packet loss round-trip min/avg/max/std-dev = 42.863/42.863/42.863/0.000 ms ping -c1 -w2 www.google.com: 0 0m13.78s real 0m00.08s user 0m00.13s system t420:~$ ``` Same situation, but I cut the tethering just after the scan. Thus the dhcp command will not succeed. We see that, after timeouts, nmctl see that the ping is failing (return code 1), thus he pass to the next possible pre-defined network. ``` t420:~$ time doas nmctl -r nwids around you: Linksys19594 bbox2-d954 LGG4s8114 ifconfig em0 down: 0 default 192.168.43.1 done 192.168.43.1 a0:91:69:be:10:49 done route flush: 0 ifconfig iwn0 nwid LGG4s8114 ...: 0 iwn0: no link ........... sleeping dhclient iwn0: 0 Done. ping: no address associated with name ping -c1 -w2 www.google.com: 1 ifconfig em0 down: 0 192.168.43.1 link#2 done route flush: 0 ifconfig iwn0 nwid Linksys19594 ...: 0 iwn0: DHCPREQUEST to 255.255.255.255 iwn0: DHCPACK from 192.168.3.1 (00:22:4d:ac:30:fd) iwn0: bound to 192.168.3.16 -- renewal in 302400 seconds dhclient iwn0: 0 Done. PING www.google.com (216.58.212.164): 56 data bytes 64 bytes from 216.58.212.164: icmp_seq=0 ttl=52 time=12.654 ms --- www.google.com ping statistics --- 1 packets transmitted, 1 packets received, 0.0% packet loss round-trip min/avg/max/std-dev = 12.654/12.654/12.654/0.000 ms ping -c1 -w2 www.google.com: 0 3m34.85s real 0m00.17s user 0m00.20s system t420:~$ ``` OpenVPN Setup Guide for FreeBSD (https://www.c0ffee.net/blog/openvpn-guide) OpenVPN Setup Guide Browse securely from anywhere using a personal VPN with OpenVPN, LDAP, FreeBSD, and PF. A VPN allows you to securely extend a private network over the internet via tunneling protocols and traffic encryption. For most people, a VPN offers two primary features: (1) the ability to access services on your local network over the internet, and (2) secure internet connectivity over an untrusted network. In this guide, I'll describe how to set up a personal VPN using OpenVPN on FreeBSD. The configuration can use both SSL certificates and LDAP credentials for authentication. We'll also be using the PF firewall to NAT traffic from our VPN out to the internet. One important note about running your own VPN: since you are most likely hosting your server using a VPS or hosting provider, with a public IP address allocated specifically to you, your VPN will not give you any extra anonymity on the internet. If anything, you'll be making yourself more of a target, since all your activity can be trivially traced back to your server's IP address. So while your VPN will protect you from a snooping hacker on the free WiFi at Starbucks, it won't protect you from a federal investigation. This guide assumes you are running FreeBSD with the PF firewall. If you're using a different Unix flavor, I'll probably get you most of the way there—but you'll be on your own when configuring your firewall and networking. Finally, I've used example.com and a non-routable public IP address for all the examples in this guide. You'll need to replace them with your own domain name and public IP address. Beastie Bits BSDCan 2017 videos (https://www.youtube.com/channel/UCuQhwHMJ0yK2zlfyRr1XZ_Q/feed) Getting started with OpenBSD device driver development PDF (https://www.openbsd.org/papers/eurobsdcon2017-device-drivers.pdf) AWS CloudWatch Logs agent for FreeBSD (https://macfoo.wordpress.com/2017/10/27/aws-cloudwatch-logs-agent-for-freebsd/) FreeBSD Foundation November 2017 Development Projects Update (https://www.freebsdfoundation.org/blog/november-2017-development-projects-update/) Schedule for the BSD Devroom at FOSDEM 2018 (https://fosdem.org/2018/schedule/track/bsd/) *** Feedback/Questions Matt - The show and Cantrill (http://dpaste.com/35VNXR5#wrap) Paulo - FreeBSD Question (http://dpaste.com/17E9Z2W#wrap) Steven - Virtualization under FreeBSD (http://dpaste.com/1N6F0TC#wrap) ***

PodKit returns with Ryan, Brian and Brandon discussion Ryan's new work, Puppet and ZSH, Microsoft's surprise BASH at BUILD, iOS colors and more!