The New Stack Podcast

Artificial intelligence (AI) and machine learning (ML) have been under study for years. But what is new is the tremendous impact and overlap AI and ML are now having on application development. Among the benefits, we will continue to see applications based on massive amounts of data sets that make use of human brain-like neural network computing to perform tasks in minutes or seconds that previously required thousands of human hours to perform. On a more practical level, AI is used to automate some of the more rudimentary tasks in software production pipelines, while freeing up time for developers to focus on more creative and intellectually rewarding work.

ML and AI fit are also increasingly leveraging the resources and ability to rapidly scale Kubernetes, and more specifically, Kubeflow offer.

During a podcast from the recently held from KubeCon + CloudNativeCon China, Alex Williams, founder and editor in chief of The New Stack, spoke with Dr. Han Xiao, engineering lead at Tencent AI Lab, and Alejandro Saucedo, chief scientist at the Institute for Ethical AI and machine learning, to learn more leveraging AI’s and ML’s power for today’s at-scale application development and deployments.

The Cloud Foundry Foundation may have faced some skepticism at the outset a few years ago, but it has since more lived up to its reputation as a as a principle hub for creating and leveraging open source software on the cloud. In many respects, Cloud Foundry has matured well beyond the initial phases of a startup, and with this maturity comes inherent challenges. Now, more than ever, Cloud Foundry must true to its core mission and to never “break the user,” Abby Kearns, executive director at the Cloud Foundry Foundation, said.

During a podcast from the recently held from KubeCon + CloudNativeCon China, Kearns spoke with host Alex Williams, founder and editor in chief of The New Stack, about how the foundation continues to serve the developer open source community and what its missions continues to be. Kearns also revealed some especially interesting observations about China-based developers and their approach to the Cloud Foundry and open source community.

Watch on YouTube: https://www.youtube.com/watch?v=Z155K1GuBjI

In this week's episode, we’re talking with a couple of VMware folks about a way to optimize continuous deployment with a new technique called continuous verification.

Dan Illson, native cloud advocate at VMware cloud services, and Bahubali (Bill) Shetti, director of cloud advocacy at VMware,  wrote on the site this week that many applications are not ready for use at the completion of their deployment pipelines.

Post-deployment work to “operationalize” or “harden” services is still fairly common practice and generally slows the overall rate of software delivery. We’ll hear from them about how a practice of continuous verification can help teams deliver software faster. The idea with CV is that it can augment the CI/CD process by moving many of the post-deployment steps into feedback loops within the pipeline. The tools are already there. In fact, any monitoring or security tool that can report on its work by way of an API can be fit into an existing pipeline (depending on how flexible the CI/CD server is at handling APIs, of course),

Then later in the podcast, we discuss some of the week's stories and podcasts on the site. We delve into the basics of Robotic Processing Automation, and Kubernetes. We delve into the Unix pipe command, and how it has proved so instrumental to modern computer programming. And we discuss the evolving role of the site reliability engineer.

Inequality is growing. The climate crisis and global heating will only serve to increase this great human divide. All the while, technology is a huge contributor to both of these problems — from the massive carbon footprint and wasted electricity of data centers to mining limited resources to exploitation of factory workers to the continued lack of diversity and inclusion, there’s a lot of consequences to our supposedly forward-thinking industry.

What are our responsibilities as people working in tech to curb these trends?

In this episode of The New Stack Makers, we sat down with Nabil Hassein a technologist, educator and researcher into the historical link between computing and imperialism, to talk about what they call these “fractal patterns of inequality,” and how we examine and change the often damaging relationships within tech.

Kubernetes continues to spread across the cloud and to on premise and bare metal server environments — and with the wider scale adoption often comes growing pains. Specific to bare metal, for example, Kubernetes platforms lack viable load balancing capabilities. Beijing Yunify Technology, a China-based bare metal service provider, says it has solved the issue, with the development of open source  Porter designed to solve the issue of load balancing on bare metal in production on Kubernetes,

During this The New Stack Makers podcast recorded live at KubeCon + CloudNativeCon Open Source Summit China 2019 in Shanghai, Xuetao Song, senior software engineer at Beijing Yunify Technology, described in more detail about how Porter offers load balancing capabilities for Kubernetes, while also touching on other container-related themes.

Watch on YouTube: https://www.youtube.com/watch?v=zSWypFKaYcY

This episode of The New Stack Makers podcast talks to two Digital Ocean alumni and co-chairs of SREcon 2020 Americas who have had two very different journeys that led them to become one of the most wanted roles in tech — site reliability engineers. As the name suggests, an SRE is someone focused on the reliability of an organization's most important systems. 

The term site reliability engineer dates back to 2003 when it was coined at Google, but it certainly has existed for decades more in different forms — disaster recovery and production testers, for example — as engineers have always tried to keep essential services like healthcare and finance online. The growing demand for SRE came as we went cloud-native and needed these engineers to work in production and on operations, with a heavy focus on automation and observability.

As systems became increasingly distributed, this is a role that has evolved from just shoring up uptime for a monolith to a relationship broker who has views into organization-wide systems, a knack for problem-solving, and a love of metrics.

This week's episode was recorded (mostly) live from O'Reilly's flagship open source conference, OSCON 2019, held this week in The New Stack's home base of Portland, Oregon.

Our special guest for this episode was Thomas Grassl, who is a vice president, and global head of developer relations and community at the enterprise and software services delivery company SAP. One may not initially think of SAP and open source together but in fact the company has had a hand open source projects for decades now, including Cloud Foundry, Eclipse and many more. The company is the second largest contributor to Java, after Oracle itself. "To understand these projects, you need to have an active engagement in," he said.

We also discussed SAP 's own Open Source Programming Office, which has spawned its own project, including CLA Assistant, an effort to handle contributing licensing agreements after the company itself found no rational process to manage them. This opened the conversation about the ongoing tension between open source projects and the giant cloud providers about licensing and fairness. We also chatted about about SAP's involvement in the Open Data Initiative with other enterprise giants such as Adobe and Microsoft. "It's very much a customer-driven initiative," Grassl said. "You have data you need to combine between different vendors. This is definitely one of the big hurdles that a lot of customers have."

It would be a mistake to ignore the immediate impact artificial intelligence (AI) and machine learning (ML) is already having on software development processes and DevOps. While some may see AI and ML as new technologies high on the hype cycle with overall marginal influences — even though they have been available for years — many organizations are already taking advantage of how they can automate many tasks during the development process. This includes their role in performing more mundane and time-consuming tasks that developers, as well as operations staffers, would prefer not to do by letting the machine take over.

During this The New Stack Analysts podcast, two DevOps and development process experts spoke about AI’s and ML’s effects on DevOps and the state of algorithm development today and it impact on IT operations today: Hyoun Park, CEO and chief analyst, Amalgam Insights, and Bola Rotibi, Research Director, Software Development, CCS Insight. This roundtable was hosted by Alex Williams, founder and editor in chief of The New Stack.

Already, AI and ML are affecting DevOps workflows have provided “an amazing access to computing and processing” over the past few years, Park said. They have provided DevOps with the ability to test a wide variety of algorithmic strategies, as well as provide storage and data-management capabilities to handle the processing, the testing and benefits associated with machine learning, and artificial intelligence.

It wasn’t that long ago when Kevin Xu, general manager of global strategy and operations at PingCAP, remembers walking into what he described as a “dark and dingy” basement at an internet cafe to play World of Warcraft and eat noodles in his native China.

“Those days did exist, but not so much anymore — there are many mobile phone vendors now and [almost] everything is being done on your smartphone,” Xu said.

But after attending Stanford University Law School from 2014 until 2017 — when he took advanced computer science classes at the campus because he thought law school was “boring” — the Chinese Internet economy has become a much different place.

“The interesting thing about the Chinese internet economy is that, number one, it has the largest number of Internet users in the world of about 800 million people since my last count, which is like two and a half times the entire population of the United States and is probably more now,” Xu said. “And not only are they internet users, but they are also mostly mobile users.”

KubeCon + CloudNativeCon Open Source Summit China 2019 in Shanghai served as the perfect backdrop to record this latest edition of The New Stack Makers podcast with Xu.

In today’s episode of The New Stack Makers, TC Currie is joined by Tameika Reed, whose day gig is as a  Senior Infrastructure Engineer at EXPANSIA, a company providing full spectrum services for IT migration and integration.  After 16 years in infrastructure, she got tired of not seeing anyone like her. So three years ago she decided to be the change she wanted to see in the world, and founded Women In Linux. This group provides free on-line training in the wide variety of ways in which Linux is used, along with job boards and career advice.

Within 30 minutes of the decision to found Women in Linux, Reed’s friend had her set up with an LLC, started paperwork to become a non-profit, and set up the Women in Linux Meetup page.  The goal of the group is to introduce infrastructure newbies to Linux and other tech useful for those looking at infrastructure careers.  Most of her talks are very technical.

“We talk about getting women and under-represented minorities into tech,” Reed said, “but those conversations revolve around teaching women to code.  They’re missing out on a huge market with cloud, security in general, embedded Linux.”  Along the way she started dispensing career advice during her meetups and manages a job board.