Tag Archives: Cloud2030

CoDev With LLMs?

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.

Transcript: otter.ai/u/u3bArfIvx40oUXnRLt…?utm_source=copy_url
Photo by Pixabay: www.pexels.com/photo/aeroplane-a…e-aviation-33224/

Rob’s Hot Take:

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.

VMware Explore, Hashicorp & Industry Update

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!

Transcript: otter.ai/u/J18ecRKKwc8As_TLyC…?utm_source=copy_url
Photo by Oziel Gómez: www.pexels.com/photo/man-wearing…-mountain-925263/

Edge (and Beyond) Industry Update

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.

Resources:
www.fiercewireless.com/wireless/telc…promised-land

Transcript: otter.ai/u/wf2OahZkgp9tzF7eJu…?utm_source=copy_url
Photo by Aksonsat Uanthoeng: www.pexels.com/photo/close-up-ph…s-on-map-1078850/

Rob’s Hot Take:

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.

Can we regulate LLMs? Should we?

How do you regulate large language models? We look at the challenges of regulating these AI approaches and how governments and companies can approach it. We untangle how these models work, and dive into the mechanics of what information is controllable. We walk through concrete information that is a benefit to you here as our listener, and incentive for you to join us in future conversations as we continue to unravel it.

In addition, John Willis was on the panel today, and he started us off with a story about API’s, Amazon, Jeff Bezos, and O’Reilly from the warmup. So you’ll get a short bonus story by John Willis before we start.

References
ised-isde.canada.ca/site/innovation…panion-document
www.europarl.europa.eu/news/en/headl…xt=Parliament‘s%20 priority%20is%20to%20make,automation%2C%20to%20prevent%20harmful%20outcomes
www.trade.gov/market-intelligenc…i-regulations-2023
content.naic.org/cipr-topics/arti…ial-intelligence

Transcript: otter.ai/u/dBRQBFNz8d01taQ-iM…?utm_source=copy_url
Image: www.pexels.com/photo/measuring-g…tar-pick-3988555/

Rob’s Hot Take:

In a Cloud 2030 podcast episode, Rob Hirschfeld, CEO and co-founder of RackN, discussed the complexities of regulating large language models. He highlighted the stark differences in approaches between the US, focusing on model risks, and the EU, emphasizing user rights protection. Hirschfeld expressed concern about reconciling these varying perspectives, especially regarding data rights preservation and understanding the risks associated with using such models, particularly when algorithms cannot be fully validated. He invited listeners to engage in the ongoing conversation at the 2030.cloud.

LLMs adding to Technical Debt? Maintenance?

What is technical debt, and how does it apply to large language models? We dive into a really interesting conversation that goes from technical debt into system and code maintenance, which is probably a much better way to think about the challenges we have in maintaining the infrastructure systems, code, data and data lakes that we have to deal with on an everyday basis.

How do we maintain, store, track and update the LLMs themselves? How do we know and manage which model is being used when we retire a model?

References:
www.linkedin.com/pulse/how-google…h-debt-abi-noda/
devops.com/are-llms-leading-de…o-a-tech-debt-trap/

Transcript: otter.ai/u/ngUClgtMmLLKXCFalD…?utm_source=copy_url
Image: www.pexels.com/photo/anonymous-w…y-gloves-3846440/

Cloud2030LLMsChatGPTTechnical DebtMaintenanceCoding

Rob’s Hot Take:

In the Cloud 2030 podcast episode on August 17th, Rob Hirschfeld discusses the distinction between technical debt and system maintenance costs, emphasizing the importance of understanding the ongoing effort needed to maintain and improve systems. He points out that overlooking the maintenance costs while building a system leads to technical debt. Hirschfeld raises the question of whether large language models and AI can change the equation of system maintenance, a topic yet to be explored fully in the podcast.

Data Darkages – do LLMs drive paywalls?

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.

Transcript: otter.ai/u/e1XCyhSa9V81bgMpbo…?utm_source=copy_url
Photo by Pollianna Bonnett: www.pexels.com/photo/young-brune…e-chair-17687131/

Hashicorp BSL vs OSS License Discussion

Hashicorp made a license change into a BSL, a business license which is not open source that allows or makes code available, but instead restricts the use of Hashicorp products to people who are effectively paying customers or enterprise customers.

If you’re embedding or repackaging the software or competing with Hashicorp, you are prohibited from using it. We spent this podcast looking into why, how, and what implications there were, as well as historical precedents.

References
* www.runtime.news/hashicorp-closes-a-door/
* opentf.org
* blog.gruntwork.io/the-future-of-te…pen-ab0b9ba65bca
* spacelift.io/blog/spacelift-lat…t-on-hashicorp-bsl
* ir.hashicorp.com/news-releases/ne…results-fiscal-0
* www.hashicorp.com/license-faq#comp…uct-bsl-coverage
* www.linkedin.com/posts/rhirschfel…7665233920-MxcP/

Photo by BİLAL KARADAĞ: www.pexels.com/photo/yk-1-17939409/
Transcript: otter.ai/u/ZjTzZZiYh_dXri3rSk…?utm_source=copy_url

Data + Operations = DataOps

We talk about DataOps, but if you’re expecting this to be DevOps for data – you are mistaken. Today we talk about engineering data through the idea of data stewardship or how you manage and control the data.

Beyond permissions and access into the costs and how things are stewarded, how logs are handled, who controls how much access and how quickly people have access, where you’re putting the data to improve its effectiveness, and more. There is so much going on above the infrastructure, but below that actual analytics, this conversation will open your mind to a whole layer of challenges related to governing and managing data.

Transcript: otter.ai/u/SDaRomv41JtQYM7a6C…?utm_source=copy_url
Photo by Taryn Elliott: www.pexels.com/photo/person-hold…g-on-top-4099125/

Book Discussion: Investments Unlimited

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.

Sources
Book www.amazon.com/Investments-Unlim…tal/dp/1950508536
techstrong.ai/aiops/the-rise-of-shadow-ai/
guidehouse.com/insights/financia…-lines-of-defense

Transcript: otter.ai/u/uC9c3xJS4oATQx7BrY…?utm_source=copy_url

Kubernetes Portability

Is Kubernetes actually creating the amount of cloud portability of infrastructure agnosticism that we hope it will? If we’re using the same platform across multiple clouds, multiple infrastructures, multiple management teams, does that actually create portability?

It’s a key question for us in building cloud architectures, making decisions about the architect and about how we build architect applications, and even how we structure our teams. In this conversation, we get to the heart of answering that question, but our answers might surprise you.

Transcript: otter.ai/u/ASE9dLnP8qo2jednZB…?utm_source=copy_url
Image: www.pexels.com/photo/black-and-w…n-bucket-3908821/