The New Stack Podcast

Open source software has taken new and exciting directions since the early days when collaboration and sharing source code was first introduced a few decades ago. Whether or not the original spirit of the free software movement has been maintained or not is a subject of debate, open source has evolved to underpin computing today, ranging from the Linux operating systems of most servers to Kubernetes and the cloud.

Before open open source reached its mainstream status of today, there were some amazing things that happened, as well as some bumps and even wars that took place. These and other open source-related themes were discussed during a podcast with Danese Cooper, vice president, special initiatives for NearForm, a long-time member of the Apache Software Foundation and an emeritus board member of the Open Source Initiative (OSI); and Umur Cubukcu, CEO and co-founder of Citus Data. In addition to the past and present trials and tribulations of the open source movement, they also discussed what lies ahead.

Ant Financial, a spinoff from Alipay of  China search engine giant Alibaba, offers credit card payment and financial services at scale in a country whose population is 1.4 billion, as well as to consumers worldwide.  Zhengyu He, head of systems engineering at Ant Financial, described what it has taken to bring monolithic and outdated systems to meet today’s computing challenges at scale during a podcast hosted by Alex Williams, founder and editor-in-chief of The New Stack, recorded at KubeCon + CloudNativeCon 2018 in Shanghai.

Before Ant Financial was founded in 2014, Alipay had already begun to offer credit card payment services to consumers. “At that moment, China was not a really developed country and  we didn’t really have..sophisticated credit card systems,” He said, who worked at Google as a software engineer for over six years. “Ant Financial took the responsibility of actually building the national scale payment systems...And this is actually one of the greatest inventions I would say, in the last couple of years in China — so it’s like what we now call a cashless society."

Watch on YouTube: https://youtu.be/rmL_oxsMZuM

Machine learning (ML) should have a profound effect on many facets of our lives in the future, from self-driving cars and trucks to utility grid management. As artificial intelligence (AI) engineers and data scientists develop advanced systems based on neural networks and other technologies designed to teach machines to learn and act in ways similar to the human brain, workflows that integrate all facets of the underlying software development and deployments for ML applications will play an obvious and critical role.

To that end, David Aronchick, Co-Founder of Kubeflow, described how Kubeflow can make setting up machine learning software production pipelines easier, during a podcast, Alex Williams, founder and editor-in-chief of The New Stack, recorded at KubeCon + CloudNativeCon 2018 in Shanghai.

Watch on YouTube: https://youtu.be/pdkXhXmJoK8

The whole point of the movement-within-a-movement that Utsav Sanghani, Senior Product Manager for Desktop and AppDev Security for code security platform provider Synopsys, calls “DevSecOps,” is to engage information security professionals in the task of automating enterprise processes.  That engagement requires a shared understanding among all departments of the infrastructure with which applications and critical functions are being hosted.

That knowledge is cast to the wind, suggested Sanghani in an interview for The New Stack Makers, when an organization opts to host its applications on a cloud-native platform, and then attempt to leverage DevSecOps to secure it.

“Let’s assume that your production builds are happening in the cloud,” said Sanghani.  “You’re working for a big financial institution.  As part of your production builds, you’re running scans using market-leading tools like, let’s say, Synopsys’ Coverity.  As part of that, if at any point something were to leak out that this application has a high-security CSRF issue with it, that’s going to be a PR nightmare for that big financial institution.

Ride-sharing firm Lyft will continue to rely heavily in Kubernetes and microservices platforms in the race to offer mobility solutions that should eventually include AI-piloted cars in the very near future. This was a key point Vicki Cheung, engineering manager at Lyft,  told Alex Williams, founder and editor-in-chief of The New Stack, hosted during a podcast recorded at KubeCon + CloudNativeCon 2018 in Shanghai.

After serving as head of engineering at OpenAI, a non-profit AI research group Tesla founder and CEO Elon Musk co-founded; Cheung joined Lyft after it had attempted to make the switch to a container-based stack a few years prior. This was “when like it was really, the hype was building up and everyone is trying to make the switch but before Kubernetes was a thing,” Cheung said.

Watch on YouTube: https://youtu.be/PZ3T-UEzdRs

Software will likely continue to underpin advances in tech throughout the indefinite future, especially as artificial intelligence, machine learning and other technologies begin to have a direct influence on new stack development. But the very male-dominated world of software development can also stand to benefit from new concepts and industries beyond the traditional realm of tech. The fashion industry is a perfect example, says Charmmie Hendon, who very recently transitioned into a key marketing role as the Special Projects Manager at Serverless Inc.  after joining the company as an Executive Assistant.

How Hendon has successfully convinced the decision makers at Serverless of the many lessons the fashion industry can offer was one of the themes of Hendon’s conversation during a podcast Alex Williams, founder and editor-in-chief of The New Stack, hosted at ServerlessConf 2018.

“Fashion is a lot faster in terms of tech, if you would believe it or not — they’re pushing product every three months. So, when you’re pushing product every three months, there’s a level of insanity or level of do or die, jumping off the cliff a lot of times just getting it done,” Hendon said. “So, coming to tech, this was the right speed for me. I was like, ‘okay, I’m not pushing product every three months,’ and I actually get to take a breath and think about what we’re doing here.”

Watch on YouTube: https://youtu.be/5tqiWuHqAy8

In the telecommunications industry, the level of manual labor involved in maintaining large and complex applications at scale on a traditional software architecture has become untenable. In an effort to avoid costly service outages, system administrators are frequently up all night monitoring dashboards for spikes in activity that may signal trouble, said Sana Tariq, a senior architect of Exchange-to-Exchange (E2E) service orchestration at Canadian telecommunications service provider Telus.

“I don’t think that should exist anymore, the staying up all night,” Tariq said in a livestream and podcast with The New Stack at Open Source Summit held in Vancouver, B.C. this past August. “We need to advance to the point where we trust the algorithms to act on our behalf.”

Like so many milestones that were achieve in the history of computing, creators and inventors rarely had eureka moments, but instead, found a very practical way to solve a problem. The creation of Kubernetes is but another example of something very big that was created with little initial fanfare, before becoming one of the most important developments in modern computing that will likely serve as the cornerstone of how software is deployed and developed for at least years to come.

As Brendan Burns, distinguished engineer at Microsoft and one of the founders of Kubernetes, said during a podcast Alex Williams, founder and editor-in-chief of The New Stack, hosted during KubeCon + CloudNativeCon 2018 in Shanghai: “I don’t think we could have ever imagined that this would be where we’d be sitting five years from then — it’s really unbelievable.”

Watch on YouTube: https://youtu.be/MuKVrEaQopY

The programming languages and platforms of tomorrow when code for machine learning and artificial intelligence code become as common as writing java scripts are just beginning. They should also be Kubernetes and cloud-native-centric, according to  to emerge, co-founder and COO  Jiayao (Julia) Han and CEO Xin Zhang of Caicloud, as the role operating systems and other components will play, during the podcast Alex Williams, founder and editor-in-chief of The New Stack, hosted live during KubeCon + CloudNativeCon 2018 in Shanghai.

Watch on YouTube: https://youtu.be/m7A75WApeY0

Welcome to The New Stack Context, a weekly podcast discussing the latest news around at-scale application development and management.

For this week's episode, we discuss the latest developments in serverless computing, with Sebastien Goasguen who this month launched a new company, TriggerMesh, offering an event triggering cloud service for serverless workloads. Goasguen's last company, Skippbox was acquired by Bitnami, where he subsequently became senior director of cloud technologies. We're looking forward to hearing all about TriggerMesh.

Also this week, we discuss the latest OpenStack Summit, held this week in Berlin.  The OpenStack Foundation is expanding its scope to include other infrastructure technology, which no doubt will cause ripples in the open source ecosystem.

TNS editorial director Libby Clark hosts this episode of Context, with the help of TNS founder Alex Williams and TNS managing editor Joab Jackson.