After a brief hiatus, thecloud2030 group is back and deep in tech, talking about things that we think are going to come on the tech front, sans AI.
In this episode, we take some time to go through Kubernetes, hardware, software, bill of materials, and some governance. This includes a smattering of predictions to get your year started off with a bang.
From there, we are going to be moving into our tech-ops series. Find more details about that in today’s outro!
What is innovation? Today we continue this discussion, specifically drilling into the three horizons model for creating growth and value.
We spend a lot of time talking about how companies innovate using that model, what it means and what are examples of it? How does that spark take place? We bridge you further down the innovation learning process in this meeting.
Transcript: otter.ai/u/He9h2NVxazKMDN9a13…?utm_source=copy_url Image by Dall-E prompt “please create a close up picture of a flock of birds navigating between three different horizons. the birds are smart and know which why they need to go”
We dive deep into the technical subject of governance and policy enforcement, including the tools, techniques and processes that you need to be aware of to do a good job with policy and governance enforcement.
We cover how to get started, what to think about, what to be aware of, and chip away at your governance and policy challenges including developer development portals, infrastructure pipelines and DevSecOps.
Rob Hirschfeld, CEO and co-founder of RackN and host of the Cloud 2030 Podcast, discusses the October 19th conversation about limiting large language models (LLMs) and AI. The discussion focused on creating legal limitations for artificial intelligence and technology, highlighting the potential impact of regulations such as Section 230, which governs internet service providers’ moderation of content. Hirschfeld suggests that changes to Section 230 could be a critical component in controlling emerging technologies, inviting listeners to explore the insightful conversation at the2030.cloud.
We dive into the dynamics of open source projects and monetization today, specifically starting around the TerraForm and open tofu split. That topic is one that we love to chew over and potentially over analyze, but today’s discussion is different.
We go into how ecosystems are built both in open and proprietary and cloud systems, and look at sort of a historical perspective on what makes a project successful from an ecosystem perspective. We also dive into why some projects work like that, and why some projects don’t.
Today’s episode gives a new take on some of the dynamics going on in the open source communities through the lens of what happened with Open Tofu and TerraForm.
Can large language models effectively supplant developers and DevOps engineers?
Today we go deeper into how the models can be trained, if they can be trusted, and what is the upside or positive use case in which we really turn LLMs into the type of weighing person experts that they have the potential to be versus simply something that turns up the volume on how fast you generate code.
We also talked about the downsides of that type of model and the potential upsides of how powerful using these tools as assistants could emerge to be as a key aspect here to transform and improve the outcome for work.
In the Cloud 2030 Podcast episode from August 31st, Rob Hirschfeld discusses the potential of using large language models to enhance DevOps and development outcomes. The conversation emphasizes the possibilities of leveraging AI to improve codebases, facilitate refactoring, and encourage code reuse by tapping into the knowledge embedded in existing code bases. Hirschfeld envisions a future where AI assists developers in reducing technical debt, maintaining code more efficiently, and consolidating code intelligently, ultimately leading to improved development practices. The episode explores the challenges and investments required for realizing these outcomes, encouraging listeners to delve into the full podcast for a comprehensive understanding. To engage in further discussions, interested individuals can explore the Cloud 2030 podcasts and join the conversations at the2030.cloud.
What’s going on from VMWare to Broadcom to HashiCorp and their license changes. We discuss current topics, even to the sad news about Kris Nova passing during a mountaineering expedition.
If you’d like to catch up on the tech news, then this topic hopefully has aged well and you will enjoy it!
How do Edge and Compute and SaaS and cloud influence everything that we do? We covered topics from VMware explorer and talked a lot about Edge. That led to AI ml, which led to another topic, which led to another topic.
If you enjoy hearing about how interconnected our technology and choices are, everything from Bitcoin to edge, and cloud and government interaction, this is the podcast for you because we cover pretty much all of it and connect it together.
Remember that on September 14, we are having one of our quarterly book club meetings on the death of expertise.
In the Cloud 2030 podcast episode from August 24th, CEO Rob Hirschfeld discusses the shift from the rental/service economy to owning production assets in the context of cloud and SaaS models. He highlights the financial commitment and decoupling of capital expenses associated with service usage, emphasizing the value of owning assets in certain scenarios. Hirschfeld encourages deliberate decision-making regarding asset ownership, stressing the importance of understanding the long-term consequences and skill-building for businesses. He invites listeners to explore these topics further in the complete August 24th Cloud 2030 conversation.
A coming Data Darkage is on its way, where we’re watching Reddit, Twitter and other companies take what used to be publicly available information and put it behind a paywall or gate.
Because of the way large language models are using this data and the value of the data, we are expecting to see that trend accelerate. This will have profound implications for how we think of, share, and use data in the coming years.
This is the second installment of our book group, which is a discussion about Investments Unlimited. We have one of our authors, and a great all around DevOps enthusiast, John Willis, on the call with us.
As you might expect, while we talk about the book and John gives a lot of background and details about the book, we treat it with the classic cloud2030 style, and bring in AI, large language and advanced DevOps.
We take the topics of the book to the next level, and frame it in the moment of the year, looking beyond and into how the concepts of compliance, validation, team coordination and risk assessment are incorporated into the coming AI and how it changes in our landscape.
We use ChatGPT to live create DevOps, automation, Ansible, TerraForm, Python, and interact with different clouds to get advice on how to set up clouds.
This discussion includes a screen share session, so if you’re listening to this audio there will be times when we are talking about something you can’t see but I do make a point of working to explain what we’re doing. There’s also a video of the screen share session if you prefer.
