De Nederlandse Kubernetes Podcast

In this episode, recorded live at KubeCon, Ronald and Jan talk with Jannis Relakis and Michael Seiwald-McCarty, both senior platform engineers at Celonis. Celonis manages over 150 Kubernetes clusters across GKE, AKS, and EKS, but it wasn't always that clean. They started with six different Kubernetes flavors, including Gardener, K-Ops, and OpenShift (both Rosa and ARO), spread across multiple cloud providers.

In their KubeCon talk "No Shame in Just Paying," they shared how they tackled this consolidation project: migrating all workloads to three standardized, fully managed Kubernetes distributions. Key topics include their self-built cross-cluster connectivity tool called "Wormhole" (powered by Envoy's dynamic forward proxy), RabbitMQ federation for seamless message queue migration, and how they used Karpenter and Cilium to align node and network management across clouds.

They also get candid about what went wrong: an accidental ArgoCD sync that caused a 10-minute full environment outage, the pain of "snowflake" environments (including one requiring full HIPAA compliance with Istio mTLS), and the constant fight against scope creep that threatened to derail the entire project.

The episode closes with a forward-looking discussion on FinOps, resource rightsizing, the future of VPA, and whether Kubernetes and serverless can ever truly converge.Powered by ACC ICT

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In this episode, Ronald and Jan sit down with Luigi Nardi, founder and CEO of DB tune, at KubeCon. Luigi brings a rare mix of academic depth (PhD in computer science, postdocs at Imperial College London and Stanford, professor at Lund University) and startup pragmatism. The conversation digs into why database tuning is fundamentally a combinatorial optimization problem that humans aren't wired to solve well, and why AI is uniquely suited for it.

DB tune focuses entirely on Postgres and deploys a narrow, production-safe AI agent that reads performance metrics and iteratively adjusts server parameters (GUCs) until the system converges on an optimal configuration. No LLMs, no hallucinations — just purpose-built ML that operates in a closed feedback loop. The agent integrates with AWS RDS, Aurora, Azure Flexible Server, Google Cloud SQL, and Cloud Native PG (the Kubernetes Postgres operator).

Luigi shares a standout story: a water management company ran the agent on their production system — with a hospital's water supply on the line — and achieved a 2.5x performance improvement in just a few hours. He also explains how tuning isn't a one-time exercise: cloud workloads change, hardware scales up and down, and DB tune's model called "Newton" was specifically engineered to prevent unstable, oscillating parameter changes. The episode closes with a compelling FinOps angle: tuning doesn't just make your database faster, it can also shrink your instance size and cut infrastructure costs — a perfect fit for the Kubernetes-native world.

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In this episode, hosts Ronald and Jan are joined at KubeCon by two guests from Red Hat: Brian Stevens, AI CTO and one of the original architects behind the creation of Kubernetes and the CNCF, and Rob Shaw, co-lead of the vLLM project and maintainer of LMD.

Brian shares the remarkable backstory of how Kubernetes came to be open source, including how Red Hat negotiated a single committer seat before agreeing to be a launch partner, and how he later pushed Google to contribute Kubernetes to the newly formed CNCF rather than keeping it proprietary like TensorFlow.

Rob explains what an inference runtime actually is: the critical piece of software that takes an abstract AI model and runs it as efficiently as possible on a GPU or other accelerator — handling everything from CUDA-level kernel optimization to memory management and concurrent request scheduling. vLLM serves as a "Rosetta Stone" between the ever-growing zoo of models (Llama, DeepSeek, Mistral, Qwen, Nvidia Nemotron) and accelerators (Nvidia, AMD, Intel, Google TPUs).

The conversation covers model compression and quantization how techniques like 4-bit precision can deliver 2x hardware efficiency gains while preserving 99%+ model accuracy. Brian and Rob also address the "big model vs. many small models" debate, recommending to always start with the largest capable model to validate a use case before optimizing down.

Looking ahead, both guests see inference as potentially the single largest workload ever run on Kubernetes, and position LMD (now contributed to the CNCF) as the distributed inference layer that will make this possible across heterogeneous accelerator environments  preventing enterprises from ending up with 42 incompatible AI stacks.
The episode closes with a discussion on AI slop, human-in-the-loop thinking, and the future of Kubernetes as the universal platform for running AI agents at scale.

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In Episode 135 of the Dutch Kubernetes Podcast, Ronald Kers and Jan Stomphorst sit down with Mohamed Nasser, CEO of VEXXHOST and OpenInfra Foundation board member, together with Thierry Carrez, General Manager of the OpenInfra Foundation and Linux Foundation Europe. The conversation explores the growing relevance of OpenStack in a world increasingly focused on digital sovereignty, private cloud, AI workloads, and secure infrastructure.

The episode dives into how the industry shifted from private infrastructure toward hyperscalers between 2016 and 2020, and why many organizations are now reconsidering that strategy. Thierry explains how geopolitical tensions, vendor lock-in, and changing licensing models have renewed interest in sovereign cloud solutions powered by open source technologies like OpenStack.

Mohamed and Thierry discuss why OpenStack is still highly relevant at massive scale, especially for organizations requiring multi-tenancy, hardware abstraction, GPU enablement, HPC workloads, and advanced networking performance. They explain how Kubernetes has become the user-facing interface, while OpenStack increasingly operates invisibly underneath many modern platforms. Examples discussed include rail infrastructure, gaming companies, telecom providers, and even government environments.

The discussion also explores how Kubernetes and OpenStack complement each other instead of competing. Mohamed explains how many providers now run OpenStack itself on Kubernetes, leveraging cloud-native tooling such as Prometheus and Loki to simplify operations and observability. The hosts also discuss storage abstraction, CSI drivers, bare-metal provisioning with Ironic, and why virtualization still offers major operational advantages in large-scale Kubernetes environments.

Towards the end of the episode, the conversation shifts toward the future of open infrastructure, including confidential computing, Kata Containers, AI security, GPU orchestration, and the growing collaboration between the Linux Foundation, CNCF, and OpenInfra Foundation. Thierry highlights how secure container isolation and confidential computing are becoming increasingly important as AI workloads spread across Kubernetes platforms.

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In episode 134, Ronald and Jan reconnect with Carl Moberg from Avassa, live from KubeCon Amsterdam, nearly two years after their first spontaneous conversation about edge computing.

Since that first meeting, the edge landscape has evolved rapidly. What was once a niche topic has now become a serious focus area for industries ranging from retail and manufacturing to telecom and AI-driven infrastructure.

Carl shares how organizations are increasingly moving workloads closer to where data is created, whether that is inside factories, retail stores, industrial environments or remote edge locations. The discussion explores the differences between IoT, edge and far edge computing, and why these environments introduce unique operational and security challenges.

A major theme throughout the episode is the role of Kubernetes at the edge. While Kubernetes remains a powerful platform, Carl explains why it is not always the most practical solution for highly distributed or resource-constrained environments. The real challenge is often not starting containers, but everything around them: observability, secrets management, lifecycle management, networking, upgrades and reliability at scale.

The conversation also connects naturally to the previous episode with Neil Cresswell from Portainer. Both episodes explore the same core question from different perspectives:

How do you reliably run modern applications across thousands of edge locations?

An in-depth discussion about containers, operational complexity, AI at the edge, industrial automation and the future of distributed application platforms.

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In this episode, Ronald and Jan talk with Neil Cresswell, CEO, CTO, and co-founder of Portainer. Neil shares how Portainer started as a simple Docker UI and evolved into a platform for managing Docker, Podman, and Kubernetes environments at scale.

A key topic in this episode is Kube Solo, a lightweight Kubernetes distribution that can run on roughly 200 MB of RAM. The goal is to make Kubernetes usable in environments where traditional clusters are too heavy, such as IoT, edge, and far edge use cases. Think of AI-powered cameras, self-checkout systems, Nvidia Jetsons, and even tractors running intelligent workloads.

Neil explains that Kubernetes itself isn’t getting simpler, but it does need to become more intuitive. Portainer aims to make Kubernetes accessible to IT generalists, reducing the need for highly specialized teams while still leveraging the full power of the ecosystem.

This episode explores simplicity, scalability, edge computing, and what it takes to bring Kubernetes everywhere.

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In this episode, Ronald and Jan are joined by Nigel Douglas, Head of Developer Relations at Cloudsmith, to discuss the upcoming Kubernetes 1.36 release and the broader evolution of the Kubernetes ecosystem.

Nigel shares his journey from help desk and cybersecurity roles into open source, eventually working closely with Kubernetes through projects like Calico and Falco within the CNCF ecosystem. 

The conversation centers around Kubernetes 1.36, which marks a shift from foundational features toward optimization and new use cases. A major theme in this release is the growing importance of AI workloads. Kubernetes is increasingly positioned as the orchestration platform for AI, with features like Dynamic Resource Allocation (DRA) enabling better management of GPUs and specialized hardware. 

Security is another dominant theme. Many of the changes in this release focus on closing gaps and improving control, such as more fine-grained authorization, better admission control during node startup, and addressing previously existing vulnerabilities. 

Additionally, the episode highlights several practical improvements, including better snapshot capabilities for stateful workloads, enhanced observability features like native histograms, and improvements in workload scheduling that take hardware topology into account. 

The discussion also touches on a common challenge in the Kubernetes world: upgrading. Many organizations still run older versions due to the complexity of dependencies and ecosystem changes, making transitions non-trivial. 

Looking ahead, Nigel emphasizes the need for more standardization within Kubernetes to make it easier for organizations to adapt when components change or become deprecated, reinforcing the importance of a stable and predictable ecosystem. 

‍

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In this episode, Ronald and Jan talk with Zahra Dehghanpour (platform engineer at bol.com) and Feike Wierda (Senior DevOps Engineer @Bol. via HCS Company) about software supply chain security in Kubernetes environments.

Zahra shares her journey from development to platform engineering, driven by the constant challenges and unpredictability of working with infrastructure. Her earlier experience working in Iran, where infrastructure had to be built and maintained under constraints, shaped her approach to designing resilient and fault-tolerant systems.

Feike explains that software supply chain security covers everything that touches your software, from dependencies and tooling to people and processes. At bol.com, this is addressed by standardizing pipelines, controlling dependencies through internal repositories, and applying security scanning early in the process.

A key theme is balance: developers need freedom, but within secure guardrails. That’s why pipelines are not immediately blocked on vulnerabilities, but first used to provide visibility and gradually increase maturity.

The episode also highlights that security is never “done.” It’s an ongoing process where automation, better tooling, and AI will play an increasingly important role, especially in areas like code review and vulnerability management.

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In this episode, Ronald and Jan are joined by Hannah Hawken, partner sales at Chainguard,  who brings a fresh perspective on something every Kubernetes team struggles with: security.

What starts as a conversation about career paths quickly turns into a deeper discussion about how we’ve been approaching security all wrong for years. Coming from a background in development and later moving into security, she reflects on what it feels like to build software without truly understanding the risks—and why so many teams are still in that exact position today.

Instead of reacting to vulnerabilities after they appear, the conversation explores a different mindset. One where security isn’t something you bolt on later, but something you start with. Not “shift left”… but start left.

From there, the discussion moves into the reality many teams face: thousands of CVEs, endless patching cycles, and security teams constantly playing catch-up. What if that entire model could be flipped? What if the software you build on is already secure by design?

That idea opens the door to a broader conversation about trust in open source, the hidden complexity of dependencies, and the trade-offs between speed and security. Along the way, Ronald and Jan challenge what this means in practice. How do you actually adopt a different approach? What changes for developers? And where does this fit in real-world environments?

The episode also touches on the future. Not just of Kubernetes, but of the infrastructure powering AI and modern applications. Because if workloads are becoming more complex and critical, the foundation they run on needs to evolve as well.

By the end, one thing becomes clear:
security isn’t just a step in the process anymore… it’s becoming the starting point

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In aflevering 129 spreken Ronald en Jan met Jan Buurman van HCS Company iemand die al sinds zijn 17e in de IT zit en de evolutie van mainframes tot Kubernetes van dichtbij heeft meegemaakt 

Jan begon als COBOL-programmeur en groeide door richting organisatie, processen en platformstrategie 

Vanuit die brede ervaring kijkt hij anders naar Kubernetes dan veel engineers: niet als eindoplossing, maar als onderdeel van een groter geheel.

Een van de scherpste inzichten uit het gesprek:

Veel organisaties draaien al vijf jaar Kubernetes, maar hebben vaak nog maar 5–10% van hun applicatielandschap gemoderniseerd 

Volgens Jan ligt het echte probleem niet bij het platform, maar bij legacy-applicaties en de businesscontext eromheen. Hij deelt een confronterende anekdote van een overheidsorganisatie waar Kubernetes technisch succesvol was geïmplementeerd, maar het onderliggende probleem niet oploste, omdat de oude COBOL- en Oracle Forms-applicaties nog steeds herbouwd moesten worden 

We praten over:

• Waarom platform engineering niet automatisch modernisering betekent
• De kloof tussen “de bubbel” en de realiteit bij developers buiten de cloud-native wereld 
• Community-denken binnen organisaties als versneller voor standaardisatie 
  
  
• AI als mogelijke katalysator om legacy sneller te migreren naar Kubernetes 
  
  
• En waarom standaardisatie vaak het ondergeschoven kindje blijft 
  
  

Jan sluit af met een nuchtere blik op de toekomst van Kubernetes: niets is permanent in IT. Ook Kubernetes zal ooit verdwijnen — maar tot die tijd is het dé standaard 

Een aflevering over realisme, organisatieverandering en waarom techniek zelden het echte probleem is.

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In this episode of The Dutch Kubernetes Podcast, Ronald and Jan are joined by Maurice Côté, VP of Products at Devolutions, to talk about one of the most misunderstood topics in modern IT security: Privileged Access Management (PAM).

Too often, PAM is treated as a compliance checkbox. Something you buy because an auditor, insurer, or regulation tells you to. Maurice explains why that mindset is dangerous — and why access itself has become one of the biggest attack surfaces in today’s infrastructures.

The conversation explores how Zero Trust principles apply in real-world environments, including Kubernetes and DevOps workflows. Topics include least privilege, just-in-time access, identity-based authentication, service accounts, and why traditional passwords are slowly disappearing in favor of certificates, passkeys, and identity providers.

They also discuss upcoming regulations like NIS2 and DORA, and why security isn’t about passing audits, but about being able to survive, recover, and continue operating when something goes wrong. From bastion hosts and privileged access workstations to secret rotation and Kubernetes-native integrations, this episode focuses on practical security — not buzzwords.

The key takeaway is clear:
Security is not a product you buy once. It’s a discipline you practice continuously.

A must-listen episode for platform engineers, DevOps teams, security architects, and anyone working with Kubernetes in regulated or high-risk environments.

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In this episode of The Dutch Kubernetes Podcast, Ronald and Jan talk with Yahya Al-Salqan, CEO and co-founder of Jaffa.Net Software, about building and scaling global software companies far beyond the traditional tech hubs.

Yahya shares his personal journey from academia and Silicon Valley, where he worked at Sun Microsystems, back to Palestine to found Jaffa.Net. What started as a mission-driven decision to contribute to his community has grown into a company with over 26 years of experience, serving international clients such as Intel, BMW, Fujitsu, Lufthansa, Oxford University, and several Dutch organizations.

The conversation explores how modern software engineering practices and cloud-native technologies make it possible to deliver enterprise-grade solutions globally. Kubernetes and container technologies play a key enabling role by providing consistent environments, repeatable deployments, version control, and zero-downtime upgrades for customers running ERP and custom software solutions.

Beyond technology, the episode highlights the Palestinian IT ecosystem, the importance of education, and how software development allows talent to transcend physical and political borders. Yahya explains why the IT sector is one of the fastest-growing contributors to the local economy and why investing in people and skills is the most sustainable path forward.

The discussion also touches on future trends such as AI, blockchain, and programmable digital money, and how companies must continuously evolve to stay relevant. Throughout the episode, one theme remains central: global software scale is no longer defined by geography, but by mindset, tooling, and execution.

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In episode 126 of De Nederlandse Kubernetes Podcast, Ronald and Jan sit down with Chris Noon, Technical Solution Director at Alkira, to talk about one of the most underestimated challenges in cloud-native environments: networking.

Chris shares his journey from traditional telco and enterprise networking, through VMware NSX, to modern cloud and Kubernetes platforms. The conversation dives deep into why networking often becomes more complex—not less—once organizations adopt multi-cloud, hybrid cloud, and Kubernetes at scale.

Key topics include:

• Why IPsec meshes don’t scale in multi-cloud environments
• How “hair-pinning” traffic across regions creates massive latency
• Alkira’s cloud-native approach to connecting AWS, Azure, GCP, and on-prem
• Networking considerations around Kubernetes, CNI’s, and Zero Trust
• DORA compliance, security architecture, and data sovereignty
• Why AI workloads make networking and data placement more critical than ever

A great episode for anyone who realizes that cloud-native doesn’t end at Kubernetes—it starts with solid network architecture.

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In this episode of The Dutch Kubernetes Podcast, Ronald and Jan sit down with Jussi Nummelin, Senior Principal Engineer at Mirantis, to explore the world of lightweight Kubernetes, edge computing, and multi-cluster orchestration.

Jussi introduces k0s, a fully upstream Kubernetes distribution packaged as a single, statically compiled binary with zero dependencies. He explains why simplicity, predictability, and minimal operational overhead are essential for edge and IoT environments such as factory floors, industrial controllers, and remote locations with limited connectivity.

The conversation then moves to K0rdent, Mirantis’ multi-cluster management layer built on top of Cluster API. K0rdent enables organizations to declaratively manage large numbers of clusters while automatically deploying essential “beachhead services” like CNI, storage, and observability across environments.

Finally, Jussi shares his perspective on the future of Kubernetes: why it’s here to stay, how edge and cloud are converging, and why Kubernetes is becoming the standard orchestration layer far beyond the traditional datacenter.

A practical and forward-looking episode packed with real-world use cases, architectural insights, and a clear vision of where Kubernetes is heading.

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In aflevering 124 van De Nederlandse Kubernetes Podcast bespreken Jan Stomphorst en Ronald Kers de nieuwste Kubernetes-release: versie 1.35.
Dit keer geen volledige lijst met alle wijzigingen, maar een bewuste keuze voor impactvolle features die in de praktijk het verschil maken.

Een van de eerste onderwerpen is Image Max Age, een nieuwe kubelet-optie waarmee je expliciet kunt bepalen hoe lang ongebruikte container images op nodes blijven staan. Dit helpt bij het voorkomen van volle disks, onverwachte opruimacties en onnodige image downloads, vooral in grote clusters.

Daarna komt Max Parallel Image Pulls aan bod. Deze feature voorkomt zogeheten image pull storms wanneer veel nodes tegelijkertijd een nieuwe image moeten downloaden. Door het pullgedrag te limiteren, blijven clusters stabieler en worden registries minder zwaar belast.

Ook Dynamic Resource Allocation (DRA) krijgt aandacht. Hiermee kunnen resources buiten CPU en geheugen, zoals GPU’s en andere gespecialiseerde hardware, beter en veiliger worden toegewezen aan workloads. Kubernetes 1.35 voegt bovendien verbeterde foutmeldingen toe, waardoor het veel duidelijker wordt waarom een workload niet start.

Tot slot bespreken Jan en Ronald verbeteringen rond StatefulSets, waaronder meer controle over parallelle updates. Dit maakt updates van databases en andere stateful workloads sneller en beter voorspelbaar.

Kortom: Kubernetes 1.35 laat zien dat de focus steeds meer ligt op stabiliteit, schaalbaarheid en real-world operaties, in plaats van alleen nieuwe features toevoegen.

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In this episode of The Dutch Kubernetes Podcast, Ronald and Jan talk with Andrea Giardini, cloud native consultant and trainer, live from Dutch Cloud Native Day. Andrea shares his journey into cloud and Kubernetes and dives deep into a real-world use case where Kubernetes, data engineering, and AI are used to help prevent wildfires.

Andrea explains how his client Overstory uses satellite and aerial imagery to monitor vegetation near power lines. By combining geospatial data, machine learning models, and infrastructure data from energy providers, they can calculate risk profiles and alert operators before vegetation causes sparks or fires. Instead of reacting to disasters, the platform focuses on prevention.

From a technical perspective, Kubernetes plays a critical role. The workloads vary massively, ranging from small CPU-based tasks to extremely heavy jobs requiring dozens of CPUs, large amounts of memory, or GPUs. Kubernetes provides the flexibility to dynamically scale these workloads, spin resources up and down when needed, and keep costs under control.

The conversation also covers the data engineering workflow. JupyterHub is used extensively for data exploration, but Andrea explains why notebooks alone are not reliable for long-term, repeatable processing. Once experiments are validated, workflows are moved into reproducible Python pipelines using a cloud-native workflow orchestrator (Dagster), fully integrated with Kubernetes.

They further discuss handling large datasets in object storage, running different pipeline steps with different resource profiles, GPU scheduling, and improving developer experience with pull-request-based preview environments. The episode highlights how cloud native technologies are not just about infrastructure efficiency, but can have real-world impact on safety, sustainability, and climate-related challenges.

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In deze aflevering spreken Ronald en Jan met Giorgia Fiscaletti, Cloud Reliability Engineer bij Adobe. Giorgia vertelt hoe ze vanuit een creatieve achtergrond — kunst en digital design — uiteindelijk in de wereld van cloud engineering en Kubernetes terechtkwam.

Bij Adobe werkt Giorgia aan Adobe Experience Manager, een enorm platform dat draait op tientallen Kubernetes-clusters met honderden namespaces per cluster. Ze deelt hoe Adobe Helm inzet voor het managen van applicaties op schaal en welke uitdagingen daarbij komen kijken.

Belangrijkste inzichten uit het gesprek:

Van creatieve roots naar cloud engineering: Een onverwachte maar krachtige overgang van artistieke studies naar high-scale cloudplatforms.

Helm op massale schaal: Adobe gebruikte aanvankelijk per namespace een eigen helm-controller en source-controller, maar bij clusters met 200–300 namespaces leidde dit tot overbelasting van de API-server.

Sharding als oplossing: Door controllers te centraliseren en te sharden over labels werd de druk op de API-server drastisch verlaagd.

Etcd-problemen: Helm release secrets stapelden zich op, wat clusters richting read-only situaties duwde. Giorgia legt uit hoe dit werd geïdentificeerd en verholpen.

Complexe customization-lagen: Adobe combineert Helm met meerdere configuratielagen voor klantomgevingen, interne features en experimentele patches.

Real-world scale: 50+ clusters, ~200 namespaces per cluster, Argo CD pipelines, Flux controllers en zeer diverse klantconfiguraties — allemaal parallel draaiend.

Werken bij Adobe: Giorgia geeft een uniek inkijkje in de tooling, architectuur en cultuur achter een platform waar duizenden engineers op bouwen.

Deze aflevering biedt een zeldzaam kijkje in de schaalproblemen, designkeuzes en technische creativiteit die nodig zijn om Kubernetes in enterprise-omgeving zoals Adobe soepel te laten functioneren.

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In this episode of The Dutch Kubernetes Podcast, Ronald and Jan sit down with Soroosh Khodami to explore one of the most urgent questions in modern software engineering: are we truly ready for the next Log4Shell-level cyber crisis?

Soroosh, a hands-on solution architect currently supporting security platform services at Rabobank, takes us deep into the evolving threat landscape. From classic vulnerabilities like SQL injection to modern supply-chain attacks and the infamous XZ backdoor, he explains how seemingly small weaknesses can cascade into full-cluster compromise — especially in cloud-native and Kubernetes environments.

The conversation covers:

• How a simple SQL injection can escalate into full Kubernetes root access, thanks to lateral movement and unpatched dependencies
• What supply-chain attacks really are, and why they’re becoming the attackers' favorite weapon
• Low-effort, high-impact practices to secure your CI/CD pipeline
• Shift-Left Security & DevSecOps — what’s hype, what’s real, and how teams need to evolve
• Why SBOMs are becoming mandatory, and how they help organizations prepare for future zero-days
• Essential tooling for SBOM generation, scanning and continuous monitoring
• How new EU regulations (DORA & CRA) will impact developers, architects and enterprises in the coming years

Soroosh also shares practical stories from the field, including real-world examples of dependency attacks, insecure pipelines, and security mistakes that happen even in mature organizations.

This episode is a must-listen for developers, architects, platform engineers, and anyone building or deploying software in 2025 and beyond.

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In this episode, we sit down with Luca Berton and Grzegorz (Greg) Stencel, authors of the brand-new book Kubernetes Recipes — a 400+ page cookbook packed with real, practical solutions for everyday Kubernetes challenges.

Luca and Greg explain how the idea for the book started: most Kubernetes books do a great job explaining theory, but very few show how to solve the messy, real-world issues engineers actually face.
 So instead of writing “yet another reference manual,” they chose the cookbook format:
👉 a problem,
👉 a clear solution,
👉 and deeper explanations when needed.

We discuss:

• How they co-wrote the book late at night while balancing work, family life, and open source contributions.
• Why enterprise Kubernetes, especially in heavily regulated environments like finance, is a completely different beast.
• How their recipes cover everything from beginner topics to advanced CRDs, operators, networking, storage, NFS, stateful apps, and multi-cloud clusters.
• The tools that actually help developers — from KubeLens to vCluster.
• Why writing a book forces more accuracy and consistency than video tutorials.
• How they used real questions (including many from Stack Overflow) to choose the most relevant scenarios.

We also talk about the future of Kubernetes:

• Luca sees AI workloads, better observability, and complexity-reducing tooling as the next big wave.
• Greg stresses that developer experience must improve — especially for developers suddenly expected to “learn Kubernetes” overnight. And yes, cluster upgrades remain painful.

A fun and insightful conversation about practical Kubernetes knowledge, open source culture, and what engineers actually need today.

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In this episode, we talk with Abdel Sghiouar and Mofi Rahman, Developer Advocates at Google and (guest) hosts of the Kubernetes Podcast from Google.
Together, we dive into one central question: can you truly run LLMs reliably and at scale on Kubernetes?

It quickly becomes clear that LLM workloads behave nothing like traditional web applications:

• GPUs are scarce, expensive, and difficult to schedule.
• Models are massive — some reaching 700GB — making load times, storage throughput, and caching critical.
• Containers become huge, making “build small containers” nearly impossible.
• Autoscaling on CPU or RAM doesn’t work; new signals like GPU cache pressure, queue depth, and model latency take over.
• LLMs don’t run in parallel, so batching and routing through the Inference Gateway API become essential.
• Device Management and Dynamic Resource Allocation (DRA) are forming the new foundation for GPU/TPU orchestration.
• Security shifts as rootless containers often no longer work with hardware accelerators.
• Guardrails (input/output filtering) become a built-in part of the inference path.

And then there’s the occasional request from customers who want deterministic LLM output —
 to which Mofi dryly responds:
 “You don’t need a model — you need a database.”

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In this episode of De Nederlandse Kubernetes Podcast, we talk with Travis Nielsen, one of the original creators of the Rook project, about the evolution of cloud-native storage and how Rook and Ceph make reliable, distributed storage accessible to Kubernetes users.

Travis shares the story of how Rook started back in 2016 when Kubernetes was still young and how it became the bridge that made Ceph, a powerful but complex storage system, usable in the cloud-native era.

We discuss:

• What Ceph actually is and why it remains one of the most trusted open-source storage platforms.
• How Rook simplifies Ceph deployment and management inside Kubernetes clusters.
• The difference between NFS and CephFS, and when to use each.
• The best ways to run databases on Ceph and how to balance performance, consistency, and replication.
• Multi-tenancy, scaling, and failure domains  how Ceph handles massive distributed systems.
• Common mistakes people make when setting up Ceph and how to avoid them.
• The future of storage in the Kubernetes ecosystem and why Ceph remains essential for stateful workloads.

A deep dive into the intersection of data durability, Kubernetes, and open source innovation  from someone who helped build it all.

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In this episode of De Nederlandse Kubernetes Podcast, we talk with Jim Bugwadia, founder and CEO of Nirmata, and Shuting Zhao, Staff Engineer and one of the maintainers of Kyverno — the CNCF project for Kubernetes policy management.

Jim and Shuting share how Kyverno was born from Nirmata’s commercial work and has since become one of the most widely adopted open source projects in Kubernetes governance, with over 3.4 billion image pulls.

We explore the real question: Why does Kubernetes need policies if it’s already declarative?
 Jim explains how policy as code helps developers, operators, and security teams collaborate on cluster configuration at scale — from pod security to resource quotas, network policies, and automation.

Shuting dives deeper into how Kyverno enables granular control, policy exceptions, and flexible enforcement modes — from audit to enforce. They discuss how large organizations use policy automation to improve compliance, security, and even cost efficiency, citing use cases like Adidas saving 50% in dev/test environments using policy-driven resource management.

We also touch on:

• 🧠 The evolution of policy as code and its parallels with infrastructure as code (like Terraform)
• 🧩 The role of AI in simplifying policy authoring (“I don’t want to run as root — just write the policy for me”)
• ⚙️ Nirmata’s Control Hub, a collaboration layer for DevSecOps teams
• 🔒 Shift-down security, where platform teams integrate security directly into Kubernetes itself

A deep-dive episode into how Kyverno and Nirmata are shaping the future of secure, automated Kubernetes governance — blending open source, AI, and DevSecOps collaboration.

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In this episode of De Nederlandse Kubernetes Podcast, we talk with Carlos Santana, Principal Partner Solution Architect at AWS and long-time contributor to the Kubernetes and AI communities.

Carlos joins us to explore what it really takes to run AI workloads on Kubernetes, from GPU scheduling to scaling inference and training efficiently across clusters. We discuss how AI and machine learning are transforming the cloud-native ecosystem — and why orchestration is becoming just as important as the models themselves.

He shares insights into:

• 💡 The challenges of scheduling and sharing GPUs in multi-tenant Kubernetes clusters
• ⚙️ Why Kubernetes Resource Orchestrator (CRO) could be the next big abstraction layer
• 🚀 The balance between performance, cost efficiency, and developer experience
• 🧠 His hands-on experiments with Jetson devices, edge computing, and model optimization
• 🌐 How open source projects and cloud providers are shaping the future of AI infrastructure

A forward-looking conversation about where AI, Kubernetes, and cloud-native engineering are heading — from someone building that future at scale.

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In this episode of De Nederlandse Kubernetes Podcast, we talk with Mustafa Hadadian, PhD researcher at the University of Groningen and founder of startup CAIDEL.
Mustafa shares his journey from video game development to big data and Kubernetes innovation, and how his latest work explores a powerful concept: bringing inheritance into Kubernetes Custom Resource Definitions (CRDs).

We dive into his poster presentation at KubeCon, titled “Extensible Kubernetes CRDs via Inheritance for Modularity and Reuse”, and discuss:

🔧 How CRDs can be extended — just like classes in Java — to reduce duplication and improve reusability.

🧩 Why inheritance could make Kubernetes development more modular and flexible.

🚀 How this helps developers define what they need (e.g., “a message queue”) while platform engineers decide how it’s implemented (Kafka, RabbitMQ, etc.).

💡 The proof of concept he built with his student Nick — showing how inheritance could work in practice through annotations and controllers.

🤖 And how his broader PhD project explores AI-driven data pipelines that assemble themselves automatically based on goals and inputs.

A fascinating deep dive into what’s next for CRDs, extensibility, and how academia and open source innovation intersect in the Kubernetes world.

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In this episode, we sit down with Nicolas Fränkel, Developer Advocate at Loft Labs, to talk about two things every Cloud Native engineer should know in 2025:
🪵 OpenTelemetry Tracing and 🌀 vCluster.

Nicolas helps us unpack why tracing is often the missing pillar of observability — and whether it might one day make traditional logs obsolete. We dive into:

• How traces, spans and sampling actually work under the hood.
• Why post-sampling may save your storage bill.
• What happens when you combine tracing with frameworks like Java, Go and Rust.
• And yes… how to finally understand those span IDs 😅

Then we switch gears to vCluster — Loft Labs’ open-source project that lets you run full virtual Kubernetes clusters inside another cluster. Think of it as:
👉 faster developer environments
👉 lightweight isolation for CI/CD
👉 no more waiting 15 minutes for test clusters to spin up

Whether you care about observability, cost-efficient clusters, or simply love smart engineering, this one’s packed with insights and stories from the field.

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In this episode we sit down with James Strong, Solutions Architect at Isovalent (the team behind Cilium), to talk about one of the biggest evolutions in Kubernetes networking: the shift from Ingress-NGINX to the Gateway API.

James, who is also a maintainer of Ingress-NGINX, explains why the project is being phased out and how the community is building its successor — in-gate, a new implementation designed around the Gateway API. We dive into:

• Why the Gateway API is the next-generation replacement for Ingress.
• The challenges of migrating existing workloads and dealing with technical debt.
• How the new API improves security, RBAC separation, and flexibility.
• The importance of community contribution, not just through code, but by joining discussions, testing, and providing feedback.

We also discuss common misconceptions, unusual use cases (like people trying to load balance VPNs and SFTP!), and what the future looks like for networking projects in the CNCF ecosystem.

An honest, behind-the-scenes look at the future of Kubernetes networking — from someone helping to build it.

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In this episode, we talk with Rodrigo Kuntzer and Andre Mocke from Miro. Their platform enables large-scale, real-time collaboration for thousands of users – and that comes with unique challenges when running on Kubernetes.

We cover topics such as:

• Why stateful workloads and WebSockets are tricky to run in Kubernetes.
• How Miro tackles scalability and reliability for long-lived connections.
• The lessons learned while building their own solutions for load balancing and graceful shutdowns.
• How Kubernetes’ flexibility helps them continue to grow their product.

An episode full of practical experiences, technical takeaways, and inspiration for anyone working with real-time applications or Kubernetes at scale.

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In this 11th episode of the 100th-episode series, we speak with Chris Aniszczyk, CTO at the Cloud Native Computing Foundation and the Linux Foundation. He reflects on ten years of CNCF and explains how the community has continually adapted to the needs of its users: from the arrival of Prometheus and containerd, to GitOps tools like Flux and Argo, and the rise of OpenTelemetry as the standard for observability.

Chris explains that Kubernetes is much more than just a container orchestrator. Thanks to extensions and CRDs, it is increasingly seen as the “Linux of the cloud” — a generic infrastructure layer on which you can run not only containers but also VMs, databases, and even AI workloads.

We discuss the challenges around stateful workloads, the role of projects like Vitess and CloudNativePG, and how Kubernetes is maturing in supporting complex scenarios. We also touch on the future: serverless patterns, better resource optimization, and the growing interconnection between cloud native and AI.

---------

In deze 11e aflevering in de 100e aflevering-reeks spreken we met Chris Aniszczyk, CTO bij de Cloud Native Computing Foundation en de Linux Foundation. Hij blikt terug op tien jaar CNCF en vertelt hoe de community zich steeds opnieuw heeft aangepast aan de behoeften van gebruikers: van de komst van Prometheus en containerd, tot GitOps-tools als Flux en Argo, en de opmars van OpenTelemetry als dé standaard voor observability.

Chris legt uit dat Kubernetes veel meer is dan een container orchestrator. Dankzij extensies en CRD’s wordt het steeds vaker gezien als de “Linux van de cloud” – een generieke infrastructuurlaag waarop je naast containers ook VM’s, databases en zelfs AI-workloads kunt draaien.

We bespreken de uitdagingen rond stateful workloads, de rol van projecten als Vitess en CloudNativePG, en hoe Kubernetes volwassen wordt in het ondersteunen van complexe scenario’s. Ook komt de toekomst aan bod: serverless patronen, betere resource-optimalisatie en de steeds hechtere verwevenheid tussen cloud native en AI.

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In deze aflevering spreken we opnieuw met Tim Stoop, Senior Solutions Architect bij ACC ICT BV

Tim legt uit hoe je Cluster API technologie het opzetten en beheren van Kubernetes-clusters sterk vereenvoudigt door alles te abstraheren en te automatiseren. Vanuit een zogeheten management cluster kun je eenvoudig workload clusters uitrollen, ongeacht of dat nu op hardware, VMware, of een cloudprovider is.

We bespreken de verschillen met tools als kubeadm en Terraform, hoe auto-scaling en providers werken, en wat de grootste lessen zijn bij het toepassen van Cluster API: de onderliggende complexiteit verdwijnt niet, maar wordt wél beter beheersbaar.

Tot slot blikken we vooruit: Tim ziet een belangrijke rol voor Cluster API in de opkomst van soevereine clouds, waarbij organisaties onafhankelijk blijven van één leverancier en workloads over meerdere partijen en locaties kunnen verdelen.

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In aflevering 109 van de Nederlandse Kubernetes Podcast spreken we met Miel Donkers, founding engineer bij Dash0. Dash0 biedt een observability- en monitoringplatform dat volledig draait op OpenTelemetry. Miel legt uit hoe zij zich onderscheiden van andere aanbieders: volledig open, gebruiksvriendelijk, en direct inzetbaar met bestaande standaarden zoals Prometheus API’s.

We bespreken hoe OpenTelemetry werkt met metrics, logs en traces, en hoe Dash0 ontwikkelaars helpt om overzicht te houden zonder complexe configuraties. Miel gaat ook in op AI-ondersteunde logclassificatie, filtering van data (aan klant- of serverzijde), en integratie met Kubernetes autoscalers.

Daarnaast vertelt hij over de uitdagingen rond data-opslag, filtering en privacy, en geeft hij praktijkvoorbeelden waarbij Dash0 cruciaal was in het opsporen van incidenten. Tot slot kijken we vooruit: Miel ziet een toekomst waarin OpenTelemetry de standaard wordt en steeds meer talen en libraries dit “by default” ondersteunen.

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