HeyJaredThe AI Kubernetes Show
Is your platform ready for the AI revolution? Tune into The AI Kubernetes Show, a limited series recorded live at KubeCon Atlanta 2025.
- Indexed episodes, last 90 days
- 6
- Latest publication
- Sep 23, 2026
- Audience
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- Earliest in this view
- Jul 15, 2026
Latest episodes
Is It Easier to Write a Vulnerability Than to Find One? (opens the original)
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Static analysis tools used to be right about as often as a coin flip. Kathleen Goeschel, Principal Product Security Engineer at Red Hat, spent years using machine learning to fix that, and now she's watching large language models change both sides of the fight. How fast vulnerable code gets written, and how fast it gets found. Goeschel walks through how she trained machine learning models on aggregated scanner alerts, software metrics, and prior CVEs to cut false positives in static analysis, an
Durable Execution for AI Agents in Kubernetes (opens the original)
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If your AI agent restarts and loses everything it was doing, your platform team is stuck retrofitting recovery logic Kubernetes was never built for. Mark Fussell, CEO of Diagrid and creator of the Dapr project, joins the AI Kubernetes Show to explain why that's the real infrastructure problem in the agentic AI era, not the model. Fussell built the platform running Azure SQL Server at scale during 20 years at Microsoft, then spent the last 9 years building Dapr (Distributed Application Runtime),
Matt Barker (BoltMCP) on SPIFFE, AI Agent Identity, and Kubernetes (opens the original)
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AI-generated code is 40% more likely to leak a secret. Matt Barker, co-founder of the company that built cert-manager and later led secure workload access at CyberArk, explains why SPIFFE might finally fix workload identity for AI agents. Matt and William Morgan cover why SPIFFE replaces long-lived secrets with short-lived, cryptographic workload identities, what Matt is building at BoltMCP to control what an AI agent can see and do once it's trusted, and why CISOs are being told to enable AI ad
Disaggregated Inference on Kubernetes (opens the original)
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Every LLM inference request splits into two phases with completely different hardware profiles: pre-fill and decode. But most Kubernetes clusters still run them on the same pod. Morgan Foster, who works on the llm-d project and the AI Gateway Working Group out of Red Hat's Office of the CTO, joins William Morgan to explain what that means. Foster and Morgan get into why real-time inference workloads fit the primitives Kubernetes already has, while training often runs on Slurm instead. They walk
The State of Cloud Native AI and What’s Still Evolving (opens the original)
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There is no agreed upon definition of what cloud native AI means yet, but if you're trying to figure out where Kubernetes AI standards are really headed, check out this episode with someone who's worked on the CNCF's first attempt to define cloud native AI. William Morgan talks with Ron Petty (RXM, CNCF founding contributor, and member of the CNCF's TCG AI) about what's actually settled in cloud native AI and what isn't. They cover the CNCF's shift from working groups to technical community grou
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