Dear friend, you have built a Kubernetes, with Mac Chaffee
Mac Chaffee, a platform engineer and security champion, examines why developers often underestimate the complexity of running modern applications and how overconfidence leads to expensive technical mistakes.You will learn:Why teams reject Kubernetes then rebuild it piece by piece - understanding the psychological factors, like overconfidence, that drive initial rejection of complex but proven toolsHow to identify the tipping point when DIY solutions become more complex than adopting established orchestration tools, especially around scaling and high availability challengesThe right approach to abstracting Kubernetes complexity - why hiding the Kubernetes API often backfires and how to build effective guardrails instead of reinventing interfacesWhy mentorship gaps lead to poor technical decisions - how the lack of proper apprenticeship programs in tech results in teams making expensive mistakes when building infrastructureSponsorThis 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/9nFPmG85fInterested in sponsoring an episode? Learn more.
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Beyond Kubernetes: Serverless Execution Models for Variable Workloads, with Marc Campora
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.
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Shared Nothing, Shared Everything: The Truth About Kubernetes Multi-Tenancy, with Molly Sheets
Molly Sheets, Director of Engineering for Kubernetes at Zynga, discusses her team's approach to platform engineering. She explains why their initial one-cluster-per-team model became unsustainable and how they're transitioning to multi-tenant architectures.You will learn:Why slowing down deployments actually increases risk and how manual approval gates can make systems less resilient than faster, smaller deploymentsThe operational reality of cluster proliferation - why managing hundreds of clusters becomes unsustainable and when multi-tenancy becomes necessaryPractical multi-tenancy implementation strategies including resource quotas, priority classes, and namespace organization patterns that work in productionBetter metrics for multi-tenant environments - why control plane uptime doesn't matter and how to build meaningful SLOs for distributed platform healthSponsorThis 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/Rmpl8948_Interested in sponsoring an episode? Learn more.
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My pipelines from GitLab Commit to ArgoCD got beaten by FTP, with David Pech
A sophisticated GitLab CI/CD pipeline integrated with Argo CD was ultimately rejected in favour of simple FTP deployment, offering crucial insights into the real barriers facing cloud-native adoption in traditional organisations.David Pech, Staff Cloud Ops Engineer at Wrike and holder of all CNCF certifications, shares his experience supporting a PHP team after a company merger. He details how he built a complete cloud-native platform with Kubernetes, Helm charts, and GitOps workflows, only to see it fail against cultural and organizational resistance despite its technical superiority.You will learn:The hidden costs of sophisticated tooling - How GitOps pipelines with multiple moving parts can create trust issues when developers lose local control and must rely on remote processes they don't understandCultural factors that trump technical benefits - Why customer expectations, existing Windows-based infrastructure, and team readiness matter more than the elegance of your Kubernetes solutionPractical strategies for incremental adoption - The importance of starting small, building in-house operational expertise, and ensuring management advocacy at all levels before attempting cloud-native transformationsSponsorThis 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/_MWX5m6G_Interested in sponsoring an episode? Learn more.
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Performance testing Kubernetes workloads, with Stephan Schwarz
If you're tasked with performance testing Kubernetes workloads without much guidance, this episode offers clear, experience-based strategies that go beyond theory.Stephan Schwarz, a DevOps engineer at iits-consulting, walks through his systematic approach to performance testing Kubernetes applications. He covers everything from defining what performance actually means, to the practical methodology of breaking individual pods to understand their limits, and navigating the complexities of Kubernetes-specific components that affect test results.You will learn:How to establish baseline performance metrics by systematically testing individual pods, disabling autoscaling features, and documenting each incremental change to understand real application limitsWhy shared Kubernetes components skew results and how ingress controllers, service meshes, and monitoring stacks create testing challenges that require careful consideration of the entire request chainPractical approaches to HPA configuration, including how to account for scaling latency, the time delays inherent in Kubernetes scaling operations, and planning for spare capacity based on your SLA requirementsThe role of observability tools like OpenTelemetry in production environments where load testing isn't feasible, and how distributed tracing helps isolate performance bottlenecks across interdependent servicesSponsorThis 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/yY-FnmGfHInterested in sponsoring an episode? Learn more.
Discover all the great things happening in the world of Kubernetes, learn (controversial) opinions from the experts and explore the successes (and failures) of running Kubernetes at scale.
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