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This week on The Changelog, Jerod is joined by Paul Biggar the creator of Dark, a new way to build serverless backends. Paul shares all the details about this all-in-one language, editor, and infrastructure, why he decided to make Dark in the first place, his view on programming language design, the advantages Dark has as an integrated solution, and also why it’s source available, but NOT open source.
Go Time’s Mat Ryer joins Jerod, KBall, and Nick to play Story of the Week, Today I Learned, Unpopular Opinions, and Shout Outs!
This is the second part of a discussion about Go language proposals that may or may not make it into the language. Listen to part one as well!
This week on Founders Talk I’m joined by John-Daniel Trask, co-founder & CEO of Raygun. Raygun is an award-winning application monitoring company founded by John-Daniel Trask (better known as JD) and Jeremy Boyd in Wellington, New Zealand. They have revenues in the 8 digits annually, and have done it with very little funding (~1.7M USD). Today’s conversation with JD shares a ton of wisdom. Listen twice and take notes.
In this Fully-Connected episode, Chris and Daniel discuss low code / no code development, GPU jargon, plus more data leakage issues. They also share some really cool new learning opportunities for leveling up your AI/ML game!
Eric Normand (long-time FP advocate and author of Grokking Simplicity) joins Jerod and KBall for a deep conversation about Functional Programming in JavaScript. Eric teaches us what FP is all about, details the functional side of JS, and reviews the good/bad/ugly of React.
Oh, and join us in the #jsparty channel of our community slack where we’re giving away three FREE e-book copies of Eric’s new book! 🎁
Documentation. You can treat it as a dictionary or reference manual that you look up things in when you get stuck during your day-to-day work OR (and this is where things get interesting) you can immerse yourself in a subject, domain, or technology by deeply and purposefully consuming its manuals cover-to-cover to develop expertise, not just passing familiarity.
In this episode we pull in perspectives and anecdotes from beginners and veterans alike to understand the impact of RTFM deeply. Also Sweet Filepath O’ Mine?!?!
This week on The Changelog we’re talking about the recent falling out between Elastic and AWS around the relicensing of Elasticsearch and Kibana. Like many in the community, we have been watching this very closely.
Here’s the tldr for context. On January 21st, Elastic posted a blog post sharing their concerns with Amazon/AWS misleading and confusing the community, saying “They have been doing things that we think are just NOT OK since 2015 and it has only gotten worse.” This lead them to relicense Elasticsearch and Kibana with a dual license, a proprietary license and the Sever Side Public License (SSPL). AWS responded two days later stating that they are “stepping up for a truly open source Elasticsearch,” and shared their plans to create and maintain forks of Elasticsearch and Kibana based on the latest ALv2-licensed codebases.
There’s a ton of detail and nuance beneath the surface, so we invited a handful of folks on the show to share their perspective. On today’s show you’ll hear from: Adam Jacob (co-founder and board member of Chef), Heather Meeker (open-source lawyer and the author of the SSPL license), Manish Jain (founder and CTO at Dgraph Labs), Paul Dix (co-founder and CTO at InfluxDB), VM (Vicky) Brasseur (open source & free software business strategist), and Markus Stenqvist (everyday web dev from Sweden).
Elad Walach of Aidoc joins Chris to talk about the use of AI for medical imaging interpretation. Starting with the world’s largest annotated training data set of medical images, Aidoc is the radiologist’s best friend, helping the doctor to interpret imagery faster, more accurately, and improving the imaging workflow along the way. Elad’s vision for the transformative future of AI in medicine clearly soothes Chris’s concern about managing his aging body in the years to come. ;-)
Our debate format returns! Divya & Feross take the “Nope” side while Amal & Nick represent the “Yep”s. Whose side will you take?
In this episode, we discuss some proposed changes to Go covering a range of subjects, from magical interfaces, to enhancing range loops, make and new with inferred types, lazy values, and more. We also talk a lot about ints, so get this episode in your ears.
Benjamin Coe joins Amal and Divya to discuss his wide-ranging open source projects, test coverage with Istanbul, and the future of testing in JavaScript.
Michael Knyszek from the Go team joins us to talk about what happens when a program ends. How are file handles cleaned up? When are deferred functions run, and when are they skipped entirely? Is there a way to terminate all running goroutines? Tune in to learn the answers to these questions and more!
John Myers of Gretel puts on his apron and rolls up his sleeves to show Dan and Chris how to cook up some synthetic data for automated data labeling, differential privacy, and other purposes. His military and intelligence community background give him an interesting perspective that piqued the interest of our intrepid hosts.
This week we’re talking about open source industrial machines. We’re joined by Marcin Jakubowski from Open Source Ecology where they’re developing open source industrial machines that can be made for a fraction of commercial costs, and they’re sharing their designs online for free. The goal is to create an efficient open source economy that increases innovation through open collaboration. We talk about what it takes to build a civilization from scratch, the Open Building Institute and their Eco-Building Toolkit, the right to repair movement, DIY maker culture, and how Marcin plans to build 10,000 micro factories worldwide where anyone can come and make.
KBall hangs with Nick and Jerod to analyze and discuss the trends of the web world according to the latest State of CSS and State of JS survey results.
In this episode we talk about various types of writing and how we as Go developers can learn from them. Whether it is planning and preparing to write, communicating with team members, or making our code clearer for future developers to read through style guides.
Daniel and Chris sniff out the secret ingredients for collecting, displaying, and analyzing odor data with Terri Jordan and Yanis Caritu of Aryballe. It certainly smells like a good time, so join them for this scent-illating episode!
This week we’re talking with Gregory Kurtzer about Rocky Linux. Greg is the founder of the CentOS project, which recently shifted its strategy and has the Linux community scrambling. Rocky Linux aims to continue where the CentOS project left off — to provide a free and open source community-driven enterprise grade Linux operating system. We discuss the history of the CentOS project, how it fell under Red Hat’s control, the recent shift in Red Hat’s strategy with CentOS, and how Rocky Linux is designed to be 100% bug-for-bug compatible with Red Hat Enterprise Linux.
Kamran Ahmed, creator of Developer Roadmaps, joins Jerod to talk through his 2021 roadmaps to becoming a web developer.
We cover why Kamran created these resources, who they’re for, how to interpret them, and then take a stroll down the paths to becoming a frontend and backend developer.
Which path are you on in 2021?
On this episode we learn how to Configure, Unify, and Execute things. What’s CUE all about? Well, it’s an open source language with a rich set of APIs and tooling for defining, generating, and validating all kinds of data: configuration, APIs, database schemas, code, … you name it.
Now that we’ve copy/pasted the project’s description… let’s dig in and learn how we can use CUE to make our Go programs better!
MLCommons launched in December 2020 as an open engineering consortium that seeks to accelerate machine learning innovation and broaden access to this critical technology for the public good. David Kanter, the executive director of MLCommons, joins us to discuss the launch and the ambitions of the organization.
In particular we discuss the three pillars of the organization: Benchmarks and Metrics (e.g. MLPerf), Datasets and Models (e.g. People’s Speech), and Best Practices (e.g. MLCube).
Preact creator Jason Miller joins Jerod and Nick to discuss WMR– the tiny all-in-one development tool for modern web apps.
We ask Jason what “modern web app” means, how WMR fits in to the JS tooling landscape, why the Preact team created it in the first place, and dig into all it has to offer. Where’s My Roomba?
Continuous integration and continuous delivery are both terms we have heard, but what do they really mean? What does CI/CD look like when done well? What are some pitfalls we might want to avoid? In this episode Jérôme and Marko, authors of the book “CI/CD with Docker and Kubernetes” join us to share their thoughts.
American Express is running what is perhaps the largest commercial ML model in the world; a model that automates over 8 billion decisions, ingests data from over $1T in transactions, and generates decisions in mere milliseconds or less globally. Madhurima Khandelwal, head of AMEX AI Labs, joins us for a fascinating discussion about scaling research and building robust and ethical AI-driven financial applications.
KBall, Amal, Chris, Divya, Jerod, and Emma discuss 2020: the good, the bad, and the ugly. Then they change direction and discuss their 2021 resolutions and wishes!
Mat Ryer hosts our don’t-call-it-jeopardy game show live at GopherCon! Kat Zień, Mark Bates, and L Körbes put their Go knowledge to the test! Can you outwit our intrepid contestants?
It’s the end of 2020 and on this year’s “State of the log” episode Adam and Jerod carry on the tradition of looking back at our favorite moments of the year – we talk through our most popular episodes, our personal favorites and must listen episodes, top posts from Changelog Posts, and what we have in the works for 2021 and beyond.
Braden Hancock joins Chris to discuss Snorkel Flow and the Snorkel open source project. With Flow, users programmatically label, build, and augment training data to drive a radically faster, more flexible, and higher quality end-to-end AI development and deployment process.
