cloud2030

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

We springboard from DeepThinking AI and have a robust conversation about what impact DeepThink is having on the industry. We also discuss where we see things going into the dilemma of people building AI infrastructure and working to do that quickly, robustly and with strong governance. This is necessary to ensure that they can quickly update and manage that AI infrastructure that they're spending so much money to build, and this leads into a broader conversation about virtualization, containers and open shift. Recorded Jan 30, 2025 Transcript: https://otter.ai/u/79JxdYOiXUoSS44pYP9bnZc4xN0?utm_source=copy_url Reference: https://www.perplexity.ai/search/provide-an-extensive-and-detai-HmRlePfiTQ6LJG_X0SlB5g#8

We deep dive into something seemingly very small, but with a lot of repercussions for how you manage and run a data center, and that is test scripts for servers. As you're going through a production cycle or a provisioning cycle, how do you test? What do you test? This topic was from a Reddit thread that we answered and then had a whole hour conversation about just how important and impactful this type of script is. Transcript: https://otter.ai/u/Cb3yac8JHvlM2yqh72bA_CBPWgs?utm_source=copy_url

Today we dive into RackN high availability technology and what we did to build consensus based raft HA capabilities directly into Digital Rebar. This is one of those episodes where we are talking specifically and only about Digital Rebar, so it is a vendored conversation from that perspective. If you are building HA systems, or are interested in how HA systems work, this is a great session to learn firsthand from our experience! Transcript: https://otter.ai/u/9lA9djczp5GkJbj12k0EzFUXw4g?utm_source=copy_url

The cloud2030 Tech Ops series is an ongoing discussion for us to create what I think of as 200 level content for tech and operations leaders, exploring really complex, deep topics in a thoughtful way to really extend your knowledge base and capabilities in the data center and infrastructure space. Today's episode talks about gitops and immutability, and what we're doing here is connecting together the operational concepts between controls and desired state communications and how that gets executed in infrastructure in an operations sense. Rather than a developer approach, this takes an operations approach. So if you are interested in how to manage immutability and what that means in infrastructure, this discussion is for you.

This is one of those fun conversations where we're really diving not just into the tech but the enterprise consumption of the tech and how people are thinking about it. How does technology like Kubernetes evolve and get used in ways that the community is not thinking about and find a whole new path for adoption and commercialization? If this is going on in your organization, we want to hear from you. We want you to be part of the conversation, because this is a really important transition point for the industry, for people questioning their VMware consumption, and for people looking to expand their Kubernetes footprints. Transcript: https://otter.ai/u/nEzH4t1JDEa51fvQFcWcFzMXmkE?utm_source=copy_url

We talk about current events, the acquisition of data stacks and the closing of the HashiCorp acquisition by IBM. Later, we dive into the productivity of AI and what's going on - are companies really getting the benefits that they expect from AI chat bot integrations and what the challenges are? We touch base on a little bit of something more infrastructure focused, where I give a preview of work I've been doing on separating Kubernetes virtualization from Kubernetes development use cases, which is something that we will be talking about more in the future. References: https://www.windowscentral.com/software-apps/microsoft-just-put-this-controversial-notepad-feature-behind-a-paywall https://www.ibm.com/new/announcements/ibm-to-acquire-datastax-helping-clients-bring-the-power-of-unstructured-data-to-enterprise-ai-applications https://www.youtube.com/watch?v=Ioc3r70HNLM https://www.linkedin.com/posts/dhinchcliffe_major-agentic-ai-news-for-cios-this-week-activity-7303122989498138624-jR2R/ 20250227

In this episode, we dive deeper into the new architectural trends for infrastructure designers in this coming decade, which is a transition from virtualization platforms first like VMware into containerized platforms first. But this time, we talk through the use of virtualization in containerized systems - keeping VMs but with what changes are necessary to make a containerized virtualization platform dominant instead of a virtualized virtualization platform. Reference: https://kubevirt.io/user-guide/architecture/ https://www.redhat.com/en/technologies/cloud-computing/openshift/virtualization

We discuss Symbolic AI via LLMs for advanced reasoning in manufacturing and real-time analytics. Key points included leveraging symbolic representations and algebraic equations, utilizing knowledge graphs to improve model accuracy, and exploring agentic AI frameworks with specialized agents working together using swarm intelligence principles to tackle complex problems like anomaly detection and process optimization. The group also discussed the challenges of building trust in AI systems and the importance of capturing and storing questions and answers to build a knowledge base.

We revisit edge infrastructure and the motivations behind building and managing edge infrastructure with an unusual take. In this case, we ask ourselves if all of these edge devices are becoming more software defined or becoming more standardized, off the shelf component tree. And will that change how we look at managing and running edge infrastructure? Will we shift compute and operations processes into these ever smarter devices? The answer is going to surprise you. Transcript: https://otter.ai/u/tGIcIC1bijvaW4OkJNm9YCEBdOE?utm_source=copy_url