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| 🔗 Stories, Tutorials & Articles |
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| VMware Cloud Foundation – what’s actually going on? |
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| Broadcom underwent significant changes post-VMware acquisition, with emphasis on subscription-based pricing and portfolio simplification. Prashant Shenoy claims VCF lowered prices by 50%, challenging industry norms about AI workloads on bare metal versus virtualized environments. Integration pointedly shows improved clarity and strategic continuity. |
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| The State of OCI Artifacts for AI/ML |
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OCI artifacts quietly leveled up. Over the last 18 months, they’ve gone from a niche hack to production muscle for AI/ML workloads on Kubernetes.
The signs? Clear enough:
KitOps and ModelPack landed in the CNCF Sandbox.
Kubernetes 1.31 got native support for Image Volume Source.
Docker pushed Model Runner to GA—with out-of-the-box support for GGUF models.
Bigger picture: OCI registries are becoming the default nerve center for model packaging, provenance, and deployment in K8s-native ML stacks. The ecosystem’s converging there - and fast. |
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| Helm 4 Overview |
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Helm 4 ditches the old plugin model for a sharper, plugin-first architecture powered by WebAssembly. That means isolation/control, and deeper customization - if you're ready to adapt!
Post-renderers are now plugins. That breaks compatibility with earlier exec-based setups, so expect some rewiring. On the plus side, new plugin types give you more hooks into Helm's guts.
Other changes: digest-based chart installs (think immutability), support for multi-document values files, and cleaner deployment feedback thanks to better kstatus signals.
Big picture: Helm 4 redraws the plugin boundary. WASM runs the show. The CI/CD pipeline just got way more composable. |
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| AWS to Bare Metal Two Years Later: Answering Your Toughest Questions About Leaving AWS |
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OneUptime ditched the cloud bill and rolled their own dual-site setup. Think bare metal, orchestrated with MicroK8s, booted by Tinkerbell, patched together with Ceph, Flux, and Terraform. Result? 99.993% uptime and $1.2M/year saved—76% cheaper than even well-optimized AWS.
They run it all with just ~14 engineer-hours/month. Thanks, Talos. The cloud's still in play, but only where it helps: archival, CDN, and burst capacity. |
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| Building a Kubernetes Platform — Think Big, Think in Planes |
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| Thinking in planes, as introduced by the Platform Engineering reference model, helps teams describe their platform in a simple, shared language, turning a collection of tools into a platform. It forces you to think horizontally, connecting teams and technologies instead of adding more layers, creating a meaningful mindset shift for platform engineering success. |
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| How to build highly available Kubernetes applications with Amazon EKS Auto Mode |
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Amazon EKS Auto Mode now runs the cluster for you—handling control plane updates, add-on management, and node rotation. It sticks to Kubernetes best practices so your apps stay up through node drains, pod failures, AZ outages, and rolling upgrades.
It also respects Pod Disruption Budgets, Readiness Gates, and topology constraints every step of the way. How? It's been hammered with resilience tests and came through steady. |
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| eBPF Beginner Skill Path |
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| This hands-on path drops devs straight into writing, loading, and poking at basic eBPF programs with libbpf, maps, and those all-important kernel safety checks. It starts simple - with a beginner-friendly challenge - then dives deeper into the verifier and tools for runtime introspection. |
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