cloud2030

In this episode, we debrief several industry events I went to last year, including Supercomputing, KubeCon, Stack, the AI Infrastructure Show, and the Red Hat AI Infrastructure Summit. We dive deep into some observations from the shows and what they tell us about the gaps and fractures in how we are working to build AI infrastructure. We focus on how observability is being used for evaluation, tuning, performance issues, GPU dropouts, and cluster management, while anomaly detection and root cause analysis remain less common, and we note that networking is still underserved. We also get into the shift from building clusters to observing and fixing them after deployment, especially for agentic systems, and we end by highlighting the need for observability across application, identity, networking, and infrastructure layers. Transcript: https://otter.ai/u/y6FNvERJRe_8qnmAgVlmvd6kwb8?utm_source=copy_url

In this episode, we discuss the rising cost of using AI and how usage-based pricing, model changes, and capacity limits are affecting daily work as AI moves from experimentation into operational use. We also talk about multi-model workflows, hybrid infrastructure, and examples of using hosted models alongside open models locally for tasks such as writing and named entity resolution. We get into the need for enterprises to run their own AI infrastructure, including questions around GPU pooling, routing, reservation, data sovereignty, and service levels. Transcript: https://otter.ai/u/pihJkUzDWWcqBnWyM24CIyxX4Qs?utm_source=copy_url

In this episode, we continue our Vibe Coding experiment. Now that we’ve figured out how to interface with MaaS, this time we wrestle with mapping and how different systems interact with each other. We’re joined by Greg Althaus, RackN CTO, who reviews the project and asks some really great questions. We talk about our decision to restart the experiment, taking the lessons we’ve learned to the newer software available. Enjoy! Video available at the2030.cloud Transcript: https://otter.ai/u/NohM8_D7DfbUu9iZc1MSpxi00kg?utm_source=copy_url

In this episode, we do some live vibe coding– using AI to write code. We share tips and tricks on having the best vibe coding experience and avoiding some common pitfalls. You'll get to hear what we do, how we discover what the steps are, just how easy it is to interact with the system, to set up a basic environment. We also start to explore the limitations of vibe coding. We encourage you to listen along and try on your own! Transcript: https://otter.ai/u/CqKdtWZWYb3AdPtcb-Ra_kU8HAU?utm_source=copy_url Video available the2030.cloud

Today we continue our exploration of vibe coding by digging into the Model Context Protocol, or MCP. We look at how MCPs connect chatbots to backend systems, why natural language matters for complex queries, and what it takes to build smarter, more adaptable interfaces. The discussion covers practical strategies for refining and automating these systems using API docs, making this a solid deep dive into the future of human-to-machine interaction. Transcript: https://otter.ai/u/5zn42OkdumP-HXIdi5YlicUmYRc?utm_source=copy_url

Today we tackle the generational infrastructure shift that's keeping IT leaders awake at night: OpenShift virtualization adoption. We dig deep into why organizations are struggling to migrate from traditional VM-focused infrastructure to Kubernetes-managed infrastructure. We explore the real hurdles blocking this transition and unpack the strategic positioning that matters when you're moving to container-orchestrated infrastructure. This isn't about dumping everything into Kubernetes and calling it done, we examine what it really takes to use Kubernetes as your infrastructure abstraction layer while navigating the operational realities that make or break these migrations. Transcript: https://otter.ai/u/IY2Y0a4aFN99ILg9daArE1nwe-c?utm_source=copy_url

Today we dive deep into the mystery of Kubernetes installation, specifically OpenShift installation. We help explain why Kubernetes installs look so weird compared to traditional operations, install processes, and where are the playbooks? Where are the scripts? Are the runbooks describing all the steps you need to take? All of it seems to be missing, and in this podcast, we explain why. Transcript: https://otter.ai/u/J802BlcVs3K_OU8B5K5pnQ9fAq8?utm_source=copy_url

In this episode, we talk about how to use AI and agentic AI specifically to rethink log collection and analysis, and find and solve really difficult problems generally. There's a bit of a build up and understanding how we got there will help you appreciate the conversation. Resources: https://www.usenix.org/conference/srecon24americas/presentation/cruz Transcript: https://otter.ai/u/P-p1tfjPhD4lbX8cy6pjRb_icQ0?utm_source=copy_url

NOTE: It appears that the Trump administration decided to allow nVidia chips... even so, this is a very interesting discussion. We discuss whether or not AI export controls work, but we take a really interesting twist because what we talk about is manufacturing. What we talk about is innovation, and it's not whether or not you can control AI chips, but what does it actually take to build innovative product? That's where we really have challenges on export and controls. There's military manufacturing and goods, and that's part of what this AI embargo is about. We really talk about how challenging it is to actually build truly innovative manufacturing and what the barriers are. Transcript: https://otter.ai/u/k6Thp-TOfwKc_RjXHCnTd7tdepc?utm_source=copy_url

In this episode, we continue our dive into the changing architecture of IT infrastructure and look at how containers and container platforms are changing. We also look at the fundamental nature of what people want to buy, accelerated by VMware Broadcom, making virtualization platforms much less attractive, and the shifting landscape here. This is work that is based on a presentation that I've been giving around the shift towards open shift virtualization and Kubernetes in general. Transcript: https://otter.ai/u/BnYKzI0zzOLqqWi45vck9gMwsDk?utm_source=copy_url

We review 2025 predictions today and dig into why I think this year is going to be both boring and terrifying for a lot of enterprise IT leaders. That, of course, spans Amazon, Reinvent storage, VMware, AI, and Agentic AI - we run the gamut on what is coming and why this is actually going to be a very challenging year. Transcript: https://otter.ai/u/H6UvLC-r2zmBO9A5jffUkhnjr5o?utm_source=copy_url Reference: https://zenoh.io by ZettaScale

We step back in this episode of our Tech Ops series and talk about cloud self managed infrastructure and how you balance the competing concerns. We started from a report that RackN had commissioned talking about on premises Kubernetes, and mixing that into your IT infrastructure. Can you have a cloud broker? Can you do multi cloud, some sort of tried and true topics for cloud consideration, but through a new filter and through this repatriation idea of mixing and matching your IT Infrastructure? Transcript: https://otter.ai/u/FKGuQpV-5bQFVASAYDhNQJtuoKM?utm_source=copy_url Resources: https://store.repebble.com/ https://rackn.com/2025/03/18/ready-for-kubernetes-on-bare-metal/ https://www.reuters.com/technology/cybersecurity/google-agrees-buy-cybersecurity-startup-wiz-32-bln-ft-reports-2025-03-18/ https://gabrielsimmer.com/blog/kubernetes-plus-oneplus