Fabián Sellés Rosa, Tech Lead of the Runtime team at Adevinta, walks through a real engineering investigation that started with a simple request: allowing tenants to use third-party Kafka services. What seemed straightforward turned into a complex DNS resolution problem that required testing seven different approaches before a working solution was found.

You will learn:

• Why Kafka's multi-step DNS resolution creates unique challenges in multi-tenant environments, where bootstrap servers and dynamic broker lists complicate standard DNS approaches

• The iterative debugging process from Route 53 split DNS through Kubernetes native pod DNS config, custom DNS servers, Kafka proxies, and CoreDNS solutions

• How to implement the final solution using node-local DNS and CoreDNS templating with practical details including ndots configuration and Kyverno automation

• Platform engineering evaluation criteria for assessing solutions based on maintainability, self-service capability, and evolvability in multi-tenant environments

Sponsor

This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training.

More info

• Find all the links and info for this episode here: https://ku.bz/NsBZ-FwcJ

• Interested in sponsoring an episode? Learn more.

Amos Wenger walks through his production incident where adding a home computer as a Kubernetes node caused TLS certificate renewals to fail. The discussion covers debugging techniques using tools like netshoot and K9s, and explores the unexpected interactions between Kubernetes overlay networks and consumer routers.

You will learn:

• How Kubernetes networking assumptions break when mixing cloud VMs with nodes behind consumer routers, and why cert-manager challenges fail in NAT environments

• The differences between CNI plugins like Flannel and Calico, particularly how they handle IPv6 translation

• Debugging techniques for network issues using tools like netshoot, K9s, and iproute2

• Best practices for mixed infrastructure including proper node labeling, taints, and scheduling controls

Sponsor

This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training.

More info

• Find all the links and info for this episode here: https://ku.bz/6Ll_7slr9

• Interested in sponsoring an episode? Learn more.

Tanat Lokejaroenlarb shares the complete journey of replacing EKS Managed Node Groups and Cluster Autoscaler with AWS Karpenter. He explains how this migration transformed their Kubernetes operations, from eliminating brittle upgrade processes to achieving significant cost savings of €30,000 per month through automated instance selection and AMD adoption.

You will learn:

• How to decouple control plane and data plane upgrades using Karpenter's asynchronous node rollout capabilities

• Cost optimization strategies including flexible instance selection, automated AMD migration, and the trade-offs between cheapest-first selection versus performance considerations

• Scaling and performance tuning techniques such as implementing over-provisioning with low-priority placeholder pods

• Policy automation and operational practices using Kyverno for user experience simplification, implementing proper Pod Disruption Budgets

Sponsor

This episode is sponsored by StormForge by CloudBolt — automatically rightsize your Kubernetes workloads with ML-powered optimization

More info

• Find all the links and info for this episode here: https://ku.bz/T6hDSWYhb

• Interested in sponsoring an episode? Learn more.

Festus Owumi walks through his project of building a lightweight version of Kubernetes in Go. He removed etcd (replacing it with in-memory storage), skipped containers entirely, dropped authentication, and focused purely on the control plane mechanics. Through this process, he demonstrates how the reconciliation loop, API server concurrency handling, and scheduling logic actually work at their most basic level.

You will learn:

• How the reconciliation loop works - The core concept of desired state vs current state that drives all Kubernetes operations

• Why the API server is the gateway to etcd - How Kubernetes prevents race conditions using optimistic concurrency control and why centralized validation matters

• What the scheduler actually does - Beyond simple round-robin assignment, understanding node affinity, resource requirements, and the complex scoring algorithms that determine pod placement

• The complete pod lifecycle - Step-by-step walkthrough from kubectl command to running pod, showing how independent components work together like an orchestra

Sponsor

This episode is sponsored by StormForge by CloudBolt — automatically rightsize your Kubernetes workloads with ML-powered optimization

More info

• Find all the links and info for this episode here: https://ku.bz/pf5kK9lQF

• Interested in sponsoring an episode? Learn more.

Understanding what's actually happening inside a complex Kubernetes system is one of the biggest challenges architects face.

Oleksii Kolodiazhnyi, Senior Architect at Mirantis, shares his structured approach to Kubernetes workload assessment. He breaks down how to move from high-level business understanding to detailed technical analysis, using visualization tools and systematic documentation.

You will learn:

• A top-down assessment methodology that starts with business cases and use cases before diving into technical details

• Practical visualization techniques using tools like KubeView, K9s, and Helm dashboard to quickly understand resource interactions

• Systematic resource discovery approaches for different scenarios, from well-documented Helm-based deployments to legacy applications with hard-coded configurations buried in containers

• Documentation strategies for creating consumable artifacts that serve different audiences, from business stakeholders to new team members joining the project

Sponsor

This episode is sponsored by StormForge by CloudBolt — automatically rightsize your Kubernetes workloads with ML-powered optimization

More info

• Find all the links and info for this episode here: https://ku.bz/zDThxGQsP

• Interested in sponsoring an episode? Learn more.

Andrew Jeffree from SafetyCulture walks through their complete migration of 250+ microservices from a fragile Helm-based setup to GitOps with ArgoCD, all without any downtime. He explains how they replaced YAML configurations with a domain-specific language built in CUE, creating a better developer experience while adding stronger validation and reducing operational pain points.

You will learn:

• Zero-downtime migration techniques using temporary deployments with prune-last sync options to ensure healthy services before removing legacy ones

• How CUE lang improves on YAML by providing schema validation, early error detection, and a cleaner interface for developers

• Human-centric platform engineering approaches that prioritize developer experience and reduce on-call burden through empathy-driven design decisions

Sponsor

This episode is brought to you by Testkube—where teams run millions of performance tests in real Kubernetes infrastructure. From air-gapped environments to massive scale deployments, orchestrate every testing tool in one platform. Check it out at testkube.io

More info

• Find all the links and info for this episode here: https://ku.bz/Xvyp1_Qcv

• Interested in sponsoring an episode? Learn more.

Mai Nishitani, Director of Enterprise Architecture at NTT Data and AWS Community Builder, demonstrates how Model Context Protocol (MCP) enables Claude to directly interact with Kubernetes clusters through natural language commands.

You will learn:

• How MCP servers work and why they're significant for standardizing AI integration with DevOps tools, moving beyond custom integrations to a universal protocol

• The practical capabilities and critical limitations of AI in Kubernetes operations

• Why fundamental troubleshooting skills matter more than ever as AI abstractions can fail in unexpected ways, especially during crisis scenarios and complex system failures

• How DevOps roles are evolving from manual administration toward strategic architecture and orchestration

Sponsor

This episode is brought to you by Testkube—where teams run millions of performance tests in real Kubernetes infrastructure. From air-gapped environments to massive scale deployments, orchestrate every testing tool in one platform. Check it out at testkube.io

More info

• Find all the links and info for this episode here: https://ku.bz/3hWvQjXxp

• Interested in sponsoring an episode? Learn more.

In this closing episode, Bryan Ross (Field CTO at GitLab), Jane Yan (Principal Program Manager at Microsoft), Sean O’Meara (CTO at Mirantis) and William Rizzo (Strategy Lead, CTO Office at Mirantis) discuss how GitOps evolves in practice.

• How enterprises are embedding Flux into developer platforms and managed cloud services.

• Why bridging CI/CD and infrastructure remains a core challenge—and how GitOps addresses it.

• What leading platform teams (GitLab, Microsoft, Mirantis) see as the next frontier for GitOps.

Sponsor

Join the Flux maintainers and community at FluxCon, November 11th in Atlanta—register here

More info

• Find all the links and info for this episode here: https://ku.bz/tVqKwNYQH

• Interested in sponsoring an episode? Learn more.

Niels Claeys shares how his team at Dataminded built Conveyor, a data platform processing up to 1.5 million core hours monthly. He explains the specific optimizations they discovered through production experience, from scheduler changes that immediately reduce costs by 10-15% to achieving 97% spot instance usage without reliability issues.

You will learn:

• Why the default Kubernetes scheduler wastes money on batch workloads and how switching from "least allocated" to "most allocated" scheduling enables faster scale-down and better resource utilization

• How to achieve 97% spot instance adoption through strategic instance type diversification, region selection, and Spark-specific techniques

• Node pool design principles that balance Kubernetes overhead with workload efficiency

• Platform-specific gotchas like AWS cross-AZ data transfer costs that can spike bills unexpectedly

Sponsor

This episode is brought to you by Testkube—where teams run millions of performance tests in real Kubernetes infrastructure. From air-gapped environments to massive scale deployments, orchestrate every testing tool in one platform. Check it out at testkube.io

More info

• Find all the links and info for this episode here: https://ku.bz/hGRfkzDJW

• Interested in sponsoring an episode? Learn more.

In this episode, Philippe Ensarguet, VP of Software Engineering at Orange, and Arnab Chatterjee, Global Head of Container & AI Platforms at Nomura, share how large enterprises are adopting Flux to drive reliable, compliant, and scalable platforms.

• How Orange uses Flux to manage bare-metal Kubernetes through its SYLVR project.

• Why FSIs rely on GitOps to balance agility with governance.

• How Flux helps enterprises achieve resilience, compliance, and repeatability at scale.

Sponsor

Join the Flux maintainers and community at FluxCon, November 11th in Atlanta—register here

More info

• Find all the links and info for this episode here: https://ku.bz/tWcHlJm7M

• Interested in sponsoring an episode? Learn more.