cloud2030

Rich Miller and I debrief our experiences at the AI Infrastructure and Edge Summit in Santa Clara. This show was interesting in the way it combined a lot of different pieces together related to AI. We share our thoughts and critiques on the event's sales-oriented focus, which overshadowed meaningful discussions on AI applications and data governance. Transcript: https://otter.ai/u/5zn42OkdumP-HXIdi5YlicUmYRc?utm_source=copy_url

Dive into the intriguing world of the Model Context Protocol (MCP), where chatbots learn to bridge the gap between user queries and backend systems. Discover how natural language processing refines complex interactions and why manual function mapping has its drawbacks. Explore live updates and the challenge of managing query parameters with token limits. Learn about using MCP for both autonomous tasks and educational guidance, along with innovative strategies for capturing institutional knowledge and enhancing developer workflows.

In this episode, we talk about scale and the hard realities of system failure in large tech operations. We explore why rare failures become common at scale, and what it takes to build systems that can handle that pressure. From predictive diagnostics to component redundancy, we share practical insights on keeping high-performance and AI infrastructure resilient. This is not theory, it is grounded in real-world lessons from managing complex environments and learning how to plan, isolate, and adapt when things go wrong. Transcript: https://otter.ai/u/X8JYiADfPPLEfQ-ggexAP5P_jGc?utm_source=copy_url

Rich, an infrastructure strategist, dives into the pressing issue of OpenShift virtualization adoption. He discusses the challenges enterprises face when migrating from traditional VM infrastructure to a Kubernetes-managed environment. The conversation highlights the strategic importance of OpenShift as a replacement for VMware amid rising costs. Rich and the host unpack the trade-offs of lower-cost licensing and the operational hurdles enterprises encounter. They emphasize the need for a phased adoption strategy, illustrating how effective migrations can showcase significant business value.

In this episode we dive into the practice of recapturing gear from data centers and how it can be used in the secondary market and the ramifications for that market. What started off as a tangent ended up as a rabbit hole rewarding conversation! Transcript: https://otter.ai/u/QR43ePMfKLNrxH1bZo0Ik8YyKo0?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

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 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

Today we riff on vibe coding, and we talk about the human and economic impacts. Can this agentic coding paradigm the use of AI and how will it impact people just starting their careers or building real applications? What is the trajectory for AI, generated systems and code and what is the risk of AI slop? Transcript: https://otter.ai/u/5G4AnR858BJnYVZiPV7w5tgAh0Y?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