Kubernetes for Humans

From the early days of "neural nets" and WebSphere to the modern complexities of Kubernetes, Hayato Shimizu has seen the evolution of infrastructure firsthand. In this episode of Kubernetes for Humans, the co-founder of Digitalis joins the show to discuss the harsh realities of enterprise platform engineering and his personal journey from corporate employee to consultancy owner.

Hayato recounts his career path starting in the late 1990s, highlighting how early application delivery methods at companies like Citrix served as precursors to modern containerization. He provides expert insights into the challenges of Kubernetes migration, emphasizing the transition from traditional, stateful systems to scalable, cloud-native architectures. The conversation explores the complexities of day-two operations, such as managing unpredictable traffic loads and prioritizing production firefighting over development backlogs. Finally, he touches upon the future of the industry, specifically how AI-driven root cause analysis can streamline incident resolution in high-pressure enterprise environments.

Follow Hayato on LinkedIn, and check out Digitalis & AxonOps to learn more about his work in the DevOps ecosystem.

In this episode Itiel hosts Veeam experts Julia and Michael, to share their distinct paths into cloud-native technology.

Julia discusses her transition from a background in law and marketing to becoming a CNCF ambassador and AWS container hero. Michael, a veteran who has been with Veeam for over 10 years, details his traditional CIS admin background (virtualization, storage) and the evolution of this role into platform engineering.

We explore the critical need for backup and data resilience, which is often the last thing companies consider in cloud-native application deployment. The discussion covers why backup serves as the essential insurance policy against modern threats like ransomware, emphasizing the importance of application consistency and data portability across multiple platforms, including Kubernetes, SaaS, and public cloud services.

In this episode, Itiel Shwartz kicks off a series on MLOps, LLM, and GenAI in Kubernetes. 

Starting with Alexei Ledenev, who has over two decades in software development and deep experience in cloud architecture and distributed systems. He shares his journey from CoreOS Fleet to his current role on the Platform Team at Doit.

The conversation focuses on tackling the complexity of Kubernetes, which Alexei notes can be overwhelming even for experienced DevOps engineers. He discusses how he developed the idea to leverage AI assistants and the Model Context Protocol (MCP) to access and execute tools like kubectl. This concept creates a "translator between AI and the Kubernetes environment", allowing users to troubleshoot complex cluster issues or quickly create ad hoc testing environments using natural language.

They also explore the challenges of implementation, such as hallucination, and how providing context helps the AI self-correct. Looking ahead, Alexei predicts that infrastructure is moving towards self-aware and self-healing platforms that integrate AI deeply.

Meet Idan Gazit from GitHub Next, a team responsible for projects like GitHub Copilot. Gazit, despite jokingly claiming to be "the least knowledgeable about Kubernetes," shares his diverse career journey, spanning from early web development with Perl and Django to his time at Heroku and eventually GitHub. He discusses his team's role in prototyping future software development solutions, emphasizing the importance of identifying and nurturing risky, impactful ideas for developers, even if it means "killing projects" that don't gain traction. Gazit also provides insights into GitHub's evolving focus on AI to enhance developer experiences and envisions a future where software creation becomes more accessible to a broader audience, with professional developers empowered by advanced tools, fostering a more integrated approach to the entire software development lifecycle.

 

Connect with Idan on social: https://gazit.me/

Meet Dustin Kirkland, VP of Engineering at Chainguard. Dustin shares his fascinating 26-year journey in the tech industry, from IBM and two stints at Canonical to roles at Google (working on GKE), Apex, and Goldman Sachs, eventually leading him back to engineering at Chainguard.

Discover how Chainguard is helping secure the software supply chain, focusing on building secure containers primarily for Kubernetes. Learn about the critical problem of software vulnerabilities (CVEs) and how Chainguard's products, including their hardened container images with a zero CVE goal and accelerated patching SLAs, address this challenge.

Dustin also introduces their newer initiatives, like Chainguard Libraries, which secures open source dependencies and builds hardened virtual machines (kernels) for Kubernetes worker nodes. He explains Chainguard's automation-driven approach, which allows them to monitor upstream fixes and rapidly rebuild and retest images and libraries.