KubeFM

Mike Stefaniak, Head of Product, Kubernetes and Registries at Amazon Web Services (AWS), discusses the challenges of operating across multiple Kubernetes clusters and environments without requiring custom scripting or multiple kubeconfig files. Mike outlines AWS's strategy to host the MCP server centrally, providing AWS with context for all clusters across accounts and regions. This architectural shift transforms troubleshooting from a single-cluster operation to fleet-wide visibility, eliminating the need for users to configure access to individual clusters manually. Watch the full interview: https://ku.bz/PzjrglcZJ

What is Udi bringing to KCD New York? Kubernetes was never easy, and AI workloads just turned the difficulty up to eleven. Udi will break down why operations are getting harder, where the cost pressure is coming from, and how AI SRE is a practical answer—not a buzzword. We also have 10 free tickets available—email hello@kube.events to grab one. KCD website: https://ku.bz/JkjmffBzw

Ryan Brainard, Software Engineering PMTS @ Heroku by Salesforce, explains how GitOps serves as a crucial source of truth and addresses the configuration drift problems his team experienced with Helm-based pipelines. Ryan emphasizes that they avoid manual changes entirely and treat clusters as cattle, not pets - making them completely disposable and enabling seamless upgrades. This approach leverages their immutable and ephemeral workloads to maintain consistency and eliminate configuration drift at scale. Watch the full interview: https://ku.bz/WY43k-PBd This interview is a reaction to Andrew Jeffree's episode https://ku.bz/Xvyp1_Qcv

What does Stacey have in store for KCD New York? A practical conversation about why open-source security still creates too much cognitive load, why secure-by-design can't succeed without broad adoption, and how projects like SLSA and Sigstore help make security resources more useful and accessible—not just academically correct. If you're interested in open-source security, software supply chain security, cloud-native infrastructure, platform engineering, and community-driven security practices, this session is a strong reason to get your ticket. We also have 10 free tickets available—email hello@kube.events to grab one before they're gone. 🌎 https://ku.bz/JkjmffBzw

Kubernetes cost optimization starts with Node Autoscaler and proper resource sizing. Amin Astaneh shares strategies: dynamically size clusters with Node Autoscaler and ensure workloads fit within resource requests. The combination of autoscaling and proper sizing prevents wasted capacity and unnecessary costs. Watch the full interview: https://ku.bz/p1RNM5ldZ This interview is a reaction to Marc Campora's episode https://ku.bz/5gMTkzLhV

GPU requests often run 2-3x higher than actual consumption in inference workloads. Why? Andrew Hillier explains the core problem: inference is transactional, not batch. GPUs sit idle between requests, but you still have to size for peak load. Unlike CPUs with Linux schedulers filling utilization gaps, GPUs run monolithic models — what you allocate is what you get. The fix? MIGs to partition GPUs, or time slicing for less critical workloads. Both help squeeze more value out of expensive hardware. Watch the full interview: https://ku.bz/wL-0d1X0y

🎙️ What is Brandt bringing to KCD New York? A practical session on software assurance at scale, why verification material becomes harder to manage across organizational boundaries, and why runtime is where trust and verification matter most. If you're interested in supply chain security, cloud-native platform engineering, observability, AI-enabled infrastructure, and practical Kubernetes operations, KCD New York is the place to be. We also have 10 free tickets available. Email hello@kube.events to claim one before they are gone. Register for KCD New York and claim your spot. 🔗 https://ku.bz/JkjmffBzw

Dave, Software Engineer and Founder at Compute Gardener, explains how carbon awareness can be integrated into Kubernetes scheduling decisions through workload shifting strategies. He breaks down the concept of temporal shifting (moving workloads to cleaner times) and spatial shifting (moving workloads to cleaner locations), with his current focus on the time-based approach. Watch the full episode: https://ku.bz/zk2xM1lfW

The right AI governance pattern for Kubernetes is not one agent doing everything. It is multiple agents doing specific work well. Henrik Rexed of Dynatrace says teams should think in terms of specialized review lanes: one AI system for infrastructure-heavy changes, another for observability concerns, and a human reviewer to confirm the final result. That reduces the chance of subtle platform-specific issues being missed by a generic review pass. Watch the full interview: https://ku.bz/KGQ_b20nQ