DevOps Paradox

Pete Hunt, CEO of Dagster and a former member of the original React team, shares his journey from building trust-and-safety tools at Facebook and Twitter to creating modern data orchestration solutions. He discusses common pitfalls in data pipelines like lateness, quality issues, and the challenges of multi-agent orchestration. Pete emphasizes the critical role of user adoption over sophisticated technology and critiques the current complexity in microservices. His insights offer valuable lessons for tackling infrastructure problems across industries.

The conversation dives into the slow AI adoption in operations, contrasting it with the rapid embrace by developers. It draws parallels with previous tech waves, noting how skepticism often precedes acceptance. They explore the significance of documentation for AI integration and warn against feeding outdated processes into AI systems. The hosts argue that coding is only a small part of development; the real challenge lies in design and requirements. A future filled with personal AI agents is envisioned, aimed at enhancing productivity.

#331: At the end of 2024, predictions were made about what 2025 would bring to the tech industry. A year later, on New Year's Eve, it's time to look back and see what actually happened. The prediction episode from January 1st covered four major topics: rug pulls from companies switching to business source licenses, the rise of WebAssembly adoption, a wave of company acquisitions, and AI becoming embedded in existing tools. Some predictions hit the mark while others missed entirely, but what emerged was something nobody fully anticipated. YouTube channel: https://youtube.com/devopsparadox Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/ Slack: https://www.devopsparadox.com/slack/ Connect with us at: https://www.devopsparadox.com/contact/

Darin and Viktor kick off with some light-hearted holiday banter. They encourage listeners to savor the festive season and save the podcast for later. Darin opens up about a challenging year, touching on personal loss and job changes. He advises everyone to take a meaningful break, recommending 36 hours off to reconnect with loved ones or find solace in public spaces. The duo wraps up with warm holiday wishes and teases their upcoming predictions for 2025.

Vibe coding is a new way to quickly generate code with AI, but it has limits for scalable applications. The hosts discuss three levels of software development: personal tools, internal applications, and public-facing systems, each needing different approaches. They use a cooking analogy to illustrate that simple meals can be made by anyone, but large-scale feeding requires expertise. The conversation also touches on the evolving role of AI in programming, emphasizing the need for experienced engineers to oversee complex projects and the future of pair programming with AI agents.

#328: The build versus buy decision isn't as binary as most companies think. Every technology choice involves elements of both - you might use Linux (buy) but still configure and customize it extensively (build). The real question isn't whether to build or buy, but finding the right balance between the two approaches based on your company's resources, size, and unique requirements. Companies often fall into the trap of thinking their processes are so unique that existing solutions won't work, leading to unnecessary custom development. This "not invented here" syndrome is particularly common in large enterprises that mistake their size for complexity. In reality, most businesses face challenges that have already been solved by others. The key is recognizing when you truly need a custom solution versus when you can adapt existing tools. The decision becomes more nuanced when considering factors like maintenance costs, compliance requirements, and long-term sustainability. Building internally requires ongoing resources for updates, security patches, and knowledge retention within your team. Meanwhile, buying from vendors shifts much of this burden but introduces dependencies and integration challenges. The conversation features insights from Alex Gusev from Uploadcare, along with perspectives from hosts Darin and Viktor on navigating these complex technology decisions. Alex's contact information: X: https://x.com/alxgsv LinkedIn: https://www.linkedin.com/in/alxgsv/ YouTube channel: https://youtube.com/devopsparadox Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/ Slack: https://www.devopsparadox.com/slack/ Connect with us at: https://www.devopsparadox.com/contact/

#327: When AI tools suggest putting glue on pizza, it's a harmless laugh. But when autonomous AI agents start managing your infrastructure, the stakes become much higher. The reality is that current AI technology isn't ready for unsupervised deployment in critical systems, and treating it like it is could lead to catastrophic failures. The challenge isn't just about AI capabilities—it's about management and oversight. Most developers aren't trained as managers, yet they're being asked to supervise AI agents that need constant guidance and correction. Just like hiring a new employee, AI agents require company-specific knowledge, proper guardrails, and ongoing supervision to be effective. The same principles that apply to managing human workers—code reviews, testing, and performance evaluations—need to be adapted for AI management. As the ecosystem around AI continues to evolve rapidly, new challenges emerge. From sleeper agents that activate on specific dates to the need for completely new approaches to technical SEO for LLMs, the landscape is changing faster than most organizations can adapt. Darin and Viktor explore these challenges and discuss practical approaches for keeping AI systems from going rogue while maintaining the productivity benefits they can provide. YouTube channel: https://youtube.com/devopsparadox Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/ Slack: https://www.devopsparadox.com/slack/ Connect with us at: https://www.devopsparadox.com/contact/

Mark Fussell, co-founder of Dapr and Diagrid, previously a Microsoft engineer, discusses the need for simplifying microservices. He delves into how Dapr was created to eliminate repetitiveness in developing distributed systems by providing standardized APIs. The conversation also explores Dapr's evolution from a Microsoft project to a CNCF graduate, its support for durable workflows, and integration with AI. Mark highlights its multi-language SDKs and practical first use cases, demonstrating how Dapr enhances developer productivity while managing complex infrastructure.

Whitney Lee, a CNCF ambassador and seasoned KubeCon reviewer, shares insights from KubeCon North America 2025. The conference spotlighted worrisome trends, like the deprecation of NGINX Ingress amid maintainer burnout. Big players like AWS and Google are becoming the mainstay for open-source project support. AI transitioned from buzzword to operational focus, with developers emerging as key buyers of AI tools. Meanwhile, startups face tough choices: pivot to AI, maintain revenue, or risk failing at both.

Omer Hamerman, an engineer at Zesty, specializes in Kubernetes resource optimization. He discusses the evolution of Kubernetes, highlighting the importance of stability amid changing workloads like AI. Omer delves into the critical role of auto-scaling in managing resource demands, especially as AI applications push infrastructure limits. He emphasizes that developers often misjudge CPU and memory needs, making automation for right-sizing essential. The conversation also covers strategic advice for startups on outsourcing complexity to focus on core business value.