The New Stack Podcast

Betty Junod, the CMO and SVP at Heroku, shares insights on Heroku's ambitious re-platforming efforts. She discusses the shift to Kubernetes and open-source engagement, including becoming a platinum member of the CNCF. Heroku's new features like Cloud Native Buildpacks allow developers to create container images more efficiently. Additionally, Betty highlights innovations aimed at supporting data scientists and the impact of AI and 'vibe coding' on developer productivity. This transformation aligns Heroku with contemporary cloud-native needs.

Ville Aikas, founder of Chainguard and an early Kubernetes contributor, shares insights on the evolution of container security. He discusses the initial security challenges, including unrealistic trust in user validations and the implications of lack of secure defaults. Aikas emphasizes the importance of trusted, minimal, and verifiable container images and the move towards locked-down AI images. The conversation also addresses the complexities surrounding AI/ML security in Kubernetes and the growing need for community collaboration in enhancing software supply chain security.

Kelsey Hightower, a Kubernetes pioneer focused on making complex systems accessible, teams up with Eswar Bala, AWS's EKS Director, who specializes in container orchestration. They discuss the grassroots origins of open source and its role in democratizing tech access. Hightower shares his personal journey and the importance of contributions over credentials. Bala highlights AWS's commitment to open source, introducing projects like Karpenter and Cedar. Their conversation emphasizes collaboration and how community-driven innovation is reshaping the cloud landscape.

Guests Jesse Butler, Principal Product Manager at AWS, and Nic Slattery, Product Manager at Google Cloud, discuss the exciting new Kro project born from customer demand. This open-source tool aims to simplify Kubernetes resource orchestration across cloud providers, reducing complexity for developers. They share insights on the unique collaboration among Google, Amazon, and Microsoft, driven by community needs rather than top-down decisions. The project has quickly gained traction, attracting numerous contributors as it prepares for a production-ready release.

Amanda Katona, who leads an open source engineering team at NetApp, dives into the transformative journey of OpenSearch since its launch. She discusses its move to the Linux Foundation, which has boosted community contributions and enterprise adoption. A striking 56% increase in downloads showcases growing interest. Katona highlights the upcoming OpenSearch 3.0, enhancing search speed amid rising data volumes. She emphasizes the importance of vendor-neutral governance and invests in machine learning tools, underscoring OpenSearch's promising future in data infrastructure.

Marco Palladino, CTO and co-founder of Kong, dives into the transformative power of AI in the tech landscape. He discusses the evolution from simple chatbots to intelligent AI agents that enhance organizational efficiency. Key topics include Kong's AI Gateway, which simplifies AI integration while addressing security concerns. Palladino highlights the automated Retrieval-Augmented Generation (RAG) feature that minimizes errors. He emphasizes the critical need for consistent security measures to empower developers to drive innovation safely.

Mallory Haigh, Director of Customer Success at Humanitec, and Nathen Harvey, DORA Lead and Developer Advocate at Google, dive into the complexities of platform engineering. They discuss the pitfalls of rushing into building internal development platforms without a clear purpose. Mallory emphasizes that success hinges more on cultural change than technical skills. The transformative role of AI in streamlining processes and enhancing developer satisfaction is also explored, suggesting that the future of platform engineering will involve integrating AI-driven automation with a focus on user needs.

Mark Hinkle, CEO of Peripety Labs and a veteran in serverless technologies, discusses the intriguing role of AI agents in software development. He describes these agents as 'dumb robots' that automate tasks but rely on large language models for real intelligence. Hinkle highlights the transformative potential of AI in creating bespoke tools on-the-fly and emphasizes the necessity of effective management practices. The conversation also spans his three-decade journey through technological evolution and the shift towards innovative GPU utilization in AI.

Join Janakiram MSV, a seasoned analyst known for his insights into data evolution and AI, as he discusses the shift from traditional SaaS to intelligent AI agents. He highlights how data management has advanced over the years, emphasizing the journey from spreadsheets to sophisticated AI solutions. Janakiram delves into the complexities of orchestrating these agents, akin to Kubernetes managing containers, and the new challenges of handling dynamic data. The conversation offers a glimpse into the future of service delivery and the transformative role of actionable AI in enterprises.

Amazon Q Developer is streamlining the software development lifecycle by integrating AI-powered tools into AWS. In an interview at AWS in Seattle, Srini Iragavarapu, director of generative AI Applications and Developer Experiences at AWS, discussed how Amazon Q Developer enhances the developer experience. Initially focused on inline code completions, Amazon Q Developer evolved by incorporating generative AI models like Amazon Nova and Anthropic models, improving recommendations and accelerating development. British Telecom reported a 37% acceptance rate for AI-generated code.Beyond code completion, Amazon Q Developer enables developers to interact with Q for code reviews, test generation, and migrations. AWS also developed agentic frameworks to automate undifferentiated tasks, such as upgrading Java versions. Iragavarapu noted that internally, AWS used Q Developer to migrate 30,000 production applications, saving $260 million annually. The platform offers code generation, testing suites, RAG capabilities, and access to AWS custom chips, further flattening the SDLC by automating routine work. Listen to The New Stack Makers for the full discussion.Learn more from The New Stack about Amazon Q Developer: Amazon Q Developer Now Handles Your Entire Code Pipeline Amazon Q Apps: AI-Powered Development for All Amazon Revamps Developer AI With Code Conversion, Security Join our community of newsletter subscribers to stay on top of the news and at the top of your game.