Kubernetes for Humans

This episode features Matt Butcher, CEO of Fermyon and creator of Helm, and Ari Weil from Akamai, as they discuss the evolution of the cloud-native ecosystem. They share their professional origins, highlighting how Kubernetes transitioned from a complex tool for experts to a foundational technology for global enterprises.

Part of the conversation focuses on the history of Helm, explaining its growth from a simple hackathon project into a standard package manager. Another part takes on the future of distributed computing, specifically how Akamai is integrating infrastructure as a service to support modern workloads.

Lastly, a prediction that the next major industry phase will involve the operationalization of AI, where SREs focus on managing intelligence at the edge rather than in centralized regions.

In this episode, Itiel joins forces with Shemer, Director of Platform Solutions at the gaming giant Playtika, and Scott Rosenberg, Lead Architect at TeraSky, to discuss the realities of platform engineering at a massive scale. The trio dissects Playtika’s multi-year journey from a legacy, homegrown Kubespray infrastructure to a modern, holistic platform built on Spectro Cloud, all while running strictly on-premise to support 25+ games and high-volume traffic.

The conversation focuses heavily on the art of abstraction, specifically how using tools like Crossplane allowed Playtika to modernize their backend without disrupting the developer experience - a philosophy Scott describes as taking the "long path" to ultimately achieve the "short path" of seamless adoption.

Learn about the challenges of overcoming "people and culture" hurdles during migration, the concept of using Kubernetes as a control plane rather than just a runtime, and realistic predictions for the role of AI agents and RAG in future DevOps workflows.

Follow Scott and Shemer on LinkedIn.

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.