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The Great Stack Debate

The Great Stack Debate

2022-08-1826:07

The software stack is like an onion. Or a sheet cake. Or lasagna. Or is it? It’s often described as having layers that sit on top of each other. The reality is much more complicated—and learning about it can help any tech career. The Great Stack Debate is the first episode in Compiler’s series on the software stack. We call it Stack/Unstuck. We explore each layer of the stack, what it’s like to work on them, and how they come together into a whole application.  
Mistakes are part of growth. If we’re lucky, we’re in an environment where they’re not punished harshly. That lets us fix the problem, learn to do better, and move on—but also to tell the story once the sting has passed.Last episode, we heard three stories of people blundering into trouble and coming out the other side a little bit wiser. This episode adds three more stories of mistakes being made—but the culprit isn’t always as clear. 
Oops. We all make mistakes. Most of the time, they’re small enough no one notices. But every now and then, we do something that makes us break into a cold sweat. The “Oops” becomes a curse, desperate pleas—or horrified silence as we process what just happened. In the moment, they’re panic-inducing. But once the dust settles, are those big mistakes that big of a deal?On this episode of Compiler, we hear three stories of people who wish they had an easy undo button. But making those mistakes taught them all something important—and changed how they do their jobs. Because those big mistakes end up being valuable lessons for the rest of their careers. 
Movies are culturally important. They transform language and communication. Motion pictures present fantasy worlds we can get lost in, helping us understand the world differently. Discussing data and movies can make the fantasy seem…a little less fantastic. It can feel sterile, mass produced, and devoid of imagination. But data is vital, both for those behind the camera and those sitting in theaters (or at home). This episode will cover some ways data science and machine learning can inform filmmaking, from conception to post-production.
Updates. They take time out of your day and your devices out of commission. That’s about the extent of it for an end user. But for organizations? Updating their systems is a big deal. And forgoing regular updates is a recipe for disaster. “If it ain’t broke, don’t fix it” isn’t a good option for enterprise IT. Your system may keep running but if you haven’t updated in awhile, you may be missing some stability and performance improvements—and probably some security patches too. Regularly updating is a good habit. How do we make it less annoying? 
When Should Data Die?

When Should Data Die?

2022-05-1230:561

We have a finite time on earth. But the data we generate? It can last much, much longer. We have limited control over what happens to our data during our lives. And while you might not care about anything when you’re gone, you and your loved ones might have an interest in how your information is used after you pass. So we wondered: When should data die? It’s a tricky question. In the digital age, individuals generate mountains of data over their lifetimes. But who has the right to decide whether that data remains, or when it is deleted? How should IT organizations handle their datasets given the complexities of privacy, legacy, and ownership that they need to consider?
Technologists are often asked to make decisions based on future industry advancements—or basically, things that haven’t happened yet. It’s already difficult to choose the right path for a project without the pressure to be clairvoyant. But everyone wants to feel like they are leading the pack on the next big thing. What do we need to know to make a good prediction for where technology is headed? Alternatively, what do we need to know to avoid the wrong choice? We speak to experts in the DevOps space about betting wrong on the future, how development projects go awry, and what teams can do to get things back on track.  
We live in what some call a “distraction economy.” There are countless messages, emails, tickets, bugs to fix, and meetings to attend. For those who have to build software, platforms, and services, as well as those who maintain them and keep them running, it can be difficult to decide what to focus on first. The immense pressure to be productive is challenging to balance with passion projects, personal responsibilities, or just with the need to rest. Our team spoke with tech-minded creators in the productivity space on how to achieve full focus, and how to make time for work, relaxation, and creativity. We would love to see you (virtually) at Red Hat Summit. Register for the virtual experience of Red Hat Summit at red.ht/summit2022.
It’s about time we asked a question about compilers. It’s been a scary proposition. Compilers have a reputation for density, complexity, and a fair bit of mysticism. But when we looked into them, we learned they’re really just like any other program. So we wondered: Who’s afraid of compilers? In this episode of Compiler, we start to break down the reputation by opening up the black box. What do compilers do? How do they work? And what can you gain by learning more about the inner workings of compilers? 
Traffic jams and congested streets are an annoyance many people have to endure. Turns out, the same technology keeping us constantly connected—the Internet of Things—can also improve how we move people and things from place to place. But what are the considerations for technologists? Connectivity can’t be the only piece of the puzzle. Smart road technology can make travel safer, easier, and more efficient. But how can it make travel enjoyable?
Computer literacy is supposedly coming naturally to younger generations who seem to be born with smartphones in their hands. But there’s a difference between tech familiarity and actually knowing how technology works. And when kids learn about the wide world of IT, what else are they learning? Kids know tech is everywhere. In this episode of Compiler, we spoke to middle school, high school, and college educators about what it is their students are hoping to learn—and what skills they pick up on the way. 
Hey listeners—we’ve got something different for you to try. If you enjoyed our Caturday episode and want more stories about security, we think you’ll like Season 9 of Command Line Heroes. It’s Red Hat’s tech history show, and this new season is all about malware. Here’s the first episode:Computer viruses and worms haunt the internet. They worm their way into a system, replicate, and spread again. It’s a simple process—with devastating consequences. But there’s a whole industry of people that rose up to fight back. Craig Schmugar recalls how he and his team responded to MyDoom, one of the fastest-spreading worms ever. Dr. Nur Zincir-Heywood reveals the inner workings of viruses and worms, and how they draw their names from the world of biology. And security expert Mikko Hypponen shares advice on avoiding malware. But he also warns that we’re in an arms race against malware developers.
Memes are goofy. They’re easily recognizable. And they’re often used to make a point. So it’s no wonder that people on both sides of the InfoSec community are not only familiar with memes, but often use them in their endless games of cat and mouse. Consequently, memes are often a sign of a breach of security. Because there’s little as satisfying as leaving a meme as proof of your security prowess. On this episode of Compiler, we hear from a couple of Red Hatters who rose to an unusual security challenge. And while intentions were good, the memes could have easily been something much more nefarious. 
Valentine’s Day is a time for roses, candy, wine, and time with that special someone. And more than ever, people are meeting their romantic partners through dating apps and websites. These apps have different features, and can vary in user experience. What technology can meet the unique demands of those looking for love across cultures, time zones, and even across oceans?In this episode of Compiler, our team goes on a date with Kubernetes to discover how container orchestration speaks to the needs of a constantly-growing user base. From thoughts on scalability, on through to testing and deployment, we hear from those who swipe right on Kubernetes.
In tech, there's a lot of pressure to keep things running smoothly. That makes even a small mistake or a brief outage seem disastrous. When people fail at something, they can experience many different emotions: Anger, regret, or even fear. In this episode of Compiler, Jen Krieger and 2019 TED Fellow Dr. Erika Hamden join us to discuss how we should handle failure, and how teams and individuals can benefit from processing it safely and effectively. Compiler is all about asking questions. And we've got some for you—our audience. Help us compile your thoughts about the show by filling out our survey at compilerpodcast.com/survey.
Since the debut of Compiler, our team has posed a few interesting questions, and the answers have gotten people talking. Do the words ‘manager’ and ‘leader’ mean the same thing? How can technical debt become more complex, outside of team areas of responsibility? We revisit some of our past topics on the show and let others weigh in on what they liked, what they didn’t like, and what we may have missed on the first pass. Want to learn more about Jeff Walter’s work? Pay a virtual visit the Atmospheric Data Science Center or earthdata.nasa.gov.
Working on a popular open source project can be demanding. Just ask the maintainers on GitHub’s ReadME podcast. In a special episode of Compiler, we teamed up with ReadME’s Brian Douglas to learn more about the challenges open source maintainers face—and investigate why burnout seems to be so prevalent in the industry. Burnout’s always going to be a problem. But we can still try to avoid it. To do so, we wanted to understand the recipe for burnout: what factors could we identify that seem to bring it about? This episode’s guests share their own experiences and bring the weight of academic research to uncover the reasons too many of our beloved maintainers burn out.
Start-ups. Newly affluent neighborhoods. Overpriced coffee shops. Tech hubs evoke a lot of imagery, opinions, and emotions. Traditionally, if someone wanted a career in tech, they had to make the move to one of these cities. The influx of new people and new ideas into a city can cause shifts in discourse, culture, and power. After all, technology can transform people, and it can transform places, too. But things are starting to change. In this episode of Compiler, we unwrap what has made tech hubs into spaces of collaboration and creativity, and how that energy can alter cities over time. Lastly, we speak to a few of the change-makers who are thinking outside of the physical and social dimensions we’ve come to associate with innovation.
We’ve all encountered technical documentation: Readmes, product manuals, and how-to guides, to name a few. Some are good, some are not so good, and some are less than helpful. Open source communities often need more people to write and update their projects’ documentation—but it’s not an easy task. So why not help out?In this episode of Compiler, we find out why everyone should write at least a little bit of technical documentation. We speak to people who contributed to documentation to help, to learn, and even to start their careers in open source.If you want to get involved with Fedora—technical writing included—check out whatcanidoforfedora.org.
New tech graduates enter the workforce every year. What generational differences and unique challenges will these younger professionals face? Mentorship is essential to make the transition into enterprise IT, regardless of where a person worked before. But it’s not always clear what mentees need, or what would be most beneficial for them. In this episode of Compiler, we speak to people about what makes a good mentor, how learning can go both ways, and what is most meaningful in mentoring relationships.
Comments (4)

Pedram Parsian

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Jul 24th
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