cloud2030

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500

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Oct 2026

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About the show

An excellent source for industry thought leadership in Edge Computing, Cloud Computing, DevOps, Open Source base on discussions at.the2030.cloud

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60 recent

October 23, 202652 min

Protecting IP from AI

This week we welcome Michael Turner back to discuss his company’s adoption of AI, including employee attitudes, spending, and usage tracking. We explore agentic tools connected to workplace services and the importance of testing, review, and human judgment when using AI to develop and maintain software. We continue to discuss the challenge of protecting your company's IP and how to guard against AI stealing or inferring it. We close by considering audience reactions to AI-generated presentations and whether speakers should make their use of AI visible. Transcript here: https://otter.ai/u/XCEBjRg1xG7nB5be24mviMImvts?utm_source=copy_url

September 25, 202648 min

Harness AI Governance

In this episode, we continue our discussion of governed execution for agentic AI and how to prevent agents from taking actions they should not take. We use a maintenance example to examine access, approvals, revocation, rollback, and human checkpoints across systems such as ERP, inventory, HRIS, planning, procurement, and maintenance tools. We also talk about the difference between the agent and the harness around it, and why deterministic workflows are often preferable to direct model action. Transcript: https://otter.ai/u/QNu4NYGzk7xe1Knv3bzVdXBo7ZE?utm_source=copy_url

September 18, 202637 min

Harnesses Pt 1

This week we discuss the role of a harness in AI systems and why it matters for infrastructure, tool use, rules, and operational constraints when an AI acts on behalf of a person or organization. We also distinguish agency, delegation, authorization, authentication, and accountability, and explain why keeping them separate matters for policy and responsibility. Transcript here: https://otter.ai/u/vSVbzrW3Eih3mLdT6OsCGRJ2WPY?utm_source=copy_url

September 11, 202658 min

Whats Up with VMware?

In this episode, we are joined by guest Byron Dill from Summit for a great deep dive into virtualization. We talk about virtualization from an enterprise and infrastructure perspective, with a focus on VMware, its recent announcements, and how the market is responding to changes in virtualization strategy. We also discuss VMware’s expanded VCF platform, including Kubernetes and AI-related features, and the contrast between AI marketing and the practical realities of GPU-based workloads. Really great episode! Transcript here: https://otter.ai/u/wYYQZyzPxrzNF_3MSU4NnPf8zS4?utm_source=copy_url

September 4, 202639 min

Token Cost Optimization

In this episode, we focus on token cost and token optimization in generative AI, and we discuss why token use needs budgets and controls rather than being treated as unlimited. We also talk about how repeated prompting, testing, and downstream work can quickly increase token consumption. We also talk about where AI agents make sense and where cheaper models or existing data should be used instead, including a bug triage example where systems should gather history and reproduce issues before escalating. We close by discussing responsibility, accuracy, and governance, including marking unverified claims clearly and using strict prompts and review passes. We also note the need for better expectations around safety and liability in AI systems. Transcript here: https://otter.ai/u/0Y-EBKoKsN7UWxC6YzMkb44ZN6w?utm_source=copy_url

August 28, 202655 min

Vibing vs Buying

In this episode, we get into current market news, including pending IPOs, hardware investment, and IBM’s AI-related announcement with Red Hat, and what this may mean for open weights models and hybrid AI. We also talk about hyper-compressed and ultra-quantized models, specialized hardware, and how memory, compute, and power limits are shaping what can run on device and at the edge. We examine the enterprise software implications and the economics of AI pipelines, including token budgeting, guardrails, human supervision, and the need for validation, governance, and operational control. Transcript: https://otter.ai/u/z-PbDS6v8w_4n2EeeyDPndqkJD8?utm_source=copy_url

August 14, 202657 min

AI Harnesses and Hosting

This week we have an exciting conversation about harnesses, neoclouds, open weights models, and the current AI infrastructure landscape. We discuss bare metal automation, agent-friendly APIs, CPU compute, GPU economics, and why some providers are moving up the stack toward models and APIs. We also look at the harness as an execution, optimization, and governance layer, including tools, sub-agents, routing, and safety controls. The conversation covers smaller and fine-tuned models, continuous validation, model drift, governance, security, compliance, and AI sovereignty, as well as sandboxing and air-gapped execution for agentic systems.

August 14, 202652 min

Innovations in Agentic Pipelines

In this episode, we discuss Red Hat’s enterprise AI work, including OpenShift AI, safety guardrails, and router-based model selection. We also talk about smaller AI systems, long-term memory, and the limits of frontier models in enterprise workflows. We cover governance, forensic traceability, and human review for regulated AI systems. Transcript: https://otter.ai/u/aJ7q0qOyhhhiDRkdaJcLrOY6R7Y?utm_source=copy_url

August 7, 20261 hr 4 min

Mirantis IREN Acquisition

We discuss the acquisition of Mirantis by the neocloud company IREN, and use it to examine the current market for infrastructure and AI deployment. We look at Mirantis’ consulting business, Kubernetes distribution, and its earlier acquisition of parts of Docker, including the registry and enterprise components. We also consider whether trusted registries could play a role in distributing agents and tools for AI systems, and we compare this idea to package management. We get into an interesting discussion on neoclouds and managed agent providers as part of the operational layer for running AI workloads, including GPU capacity, model hosting, and repeatable deployment. Transcript: https://otter.ai/u/ZBtX6hwwHIqqOBbLDiJwM66wFuM?utm_source=copy_url

July 31, 202637 min

Did AI Kill OpenSource

In this episode we discuss whether AI and LLMs are changing the role of open source, including the pressure on maintainer review queues and the growing appeal of private forks and internal maintenance. We also talk about the security tradeoffs of those forks, especially around visibility, dependency tracking, and audits. We also get into how domain expertise, documentation, interfaces, and operational knowledge may become more important than the code itself, and why documenting archival knowledge and provenance matters. Transcript: https://otter.ai/u/h61DNW_fV-5QrNBepX7NZvq8dCU?utm_source=copy_url