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Alessandro Pomponio from IBM Research explains how his team transformed their chaotic bare-metal clusters into a well-governed, self-service platform for AI and scientific workloads. He walks through their journey from manual cluster interventions to a fully automated GitOps-first architecture using ArgoCD, Kyverno, and Kueue to handle everything from policy enforcement to GPU scheduling.You will learn:How to implement GitOps workflows that reduce administrative burden while maintaining governance and visibility across multi-tenant research environmentsPractical policy enforcement strategies using Kyverno to prevent GPU monopolization, block interactive pod usage, and automatically inject scheduling constraintsFair resource sharing techniques with Kueue to manage scarce GPU resources across different hardware types while supporting both specific and flexible allocation requestsOrganizational change management approaches for gaining stakeholder buy-in, upskilling admin teams, and communicating policy changes to research usersSponsorThis episode is brought to you by Testkube—the ultimate Continuous Testing Platform for Cloud Native applications. Scale fast, test continuously, and ship confidently. Check it out at testkube.ioMore infoFind all the links and info for this episode here: https://ku.bz/5sK7BFZ-8Interested in sponsoring an episode? Learn more.

Mac Chaffee, a platform engineer and security champion, dives into the underestimated complexities of running modern applications. He discusses how overconfidence can lead to costly mistakes, particularly when teams reject proven tools like Kubernetes. Mac highlights the tipping point where DIY solutions become burdensome and stresses the importance of mentorship in preventing poor technical decisions. He advocates for transparency in technology, urging teams to establish effective guardrails rather than hiding complexity.

Marc Campora, a systems consultant with experience in high-throughput platforms, shares his analysis of a real customer deployment with 500+ microservices. He breaks down the cost implications, technical constraints, and operational trade-offs between Kubernetes containers and AWS Lambda functions based on actual production data and migration assessments.You will learn:Cost analysis frameworks for comparing Lambda vs Kubernetes across different traffic patterns, including specific examples of 3x savings potential and the 80/20 rule for service utilizationMigration complexity factors when moving existing microservices to Lambda, including cold start issues, runtime model changes, and why it's often a complete rewrite rather than a simple portDecision criteria for choosing between platforms based on traffic consistency, computational requirements, and operational overhead toleranceSponsorThis episode is sponsored by Learnk8s — get started on your Kubernetes journey through comprehensive online, in-person or remote training.More infoFind all the links and info for this episode here: https://ku.bz/5gMTkzLhVInterested in sponsoring an episode? Learn more.

Molly Sheets, Director of Engineering for Kubernetes at Zynga, leads platform engineering behind popular games like Words with Friends. She discusses how her team shifted from a one-cluster-per-team model to a more efficient multi-tenant architecture. Molly highlights the dangers of slowing deployment speeds and shares practical strategies for resource allocation and SLOs. She also delves into the unique challenges of Kubernetes in the gaming sector and candidly addresses the balance between technical roles and her journey as a new parent.