We dive into data operations in today’s episode! We cover the idea that with all of the work we're doing in AI and ML data analytics analysis, you actually have to steward your data. We also cover processes controls, like what we have with DevOps in infrastructure, but with similar types of concepts (governance controls automation) around how your data is flowing in your system. Transcript: https://otter.ai/u/pesotDnHCCD5lyPVx795EZIhTlA?utm_source=copy_url Image by DALL-E

We dive into the chaos created by Broadcom’s acquisition of VMware. In this episode, we discuss what Broadcom is doing, why it's a problem, how enterprises are reacting, and what alternatives are on the market. We cover the whole mess in all its glory, and even provide some love for Broadcom. Resources: https://www.thestack.technology/vmware-is-killing-off-56-products-including-vsphere-hypervisor-and-nsx/ https://www.siderolabs.com/platform/saas-for-kubernetes/ Transcript: https://otter.ai/u/SO8PD-p8AHwwsKfGsNqolSoYTlk?utm_source=copy_url Image by DALL-E

Join us as we embark on a comprehensive journey to master intermediate and advanced skills crucial for operators, DevOps, and platform engineers. From scripting and service setup to running complex systems, we address the critical gap in training for building, automating, and maintaining resilient and robust systems. Over the coming months, the Cloud 2030 crew will delve into the core skill sets required in this rapidly evolving field. Our series will cover an array of topics, including tools, processes, and methodologies essential for excelling in tech operations. We plan to explore a variety of subjects, aiming to equip you with the knowledge to automate effectively and build resilient systems. This kickoff meeting sets the stage for a year-long exploration into the depths of tech operations, inviting you to contribute your expertise and curiosity. Prepare for an enlightening journey as we lay out our comprehensive Tech Ops agenda. Agenda: https://docs.google.com/document/d/1Yvr8loVNfkxKmaQN5XWEaskzrV9-OsJ4oeKnUcnQ90s/edit?usp=sharing Transcript: https://otter.ai/u/FP_1Ose_jJ7qLezuAVZjFovSyVE?utm_source=copy_url Photo by Bence Szemerey: https://www.pexels.com/photo/brown-wooden-frame-with-brown-metal-pipe-6804254/

Departing from our typical podcast format, today’s episode is part of a presentation that I've been preparing about comparing 125 year old house building architecture to modern DevOps. We also analyze as things that work and don't work. There are a lot of home maintenance stories and comparison notes. Particularly in the back half of the episode we get into how this type of challenge relates to Operations Management. Refereces: https://nationalpost.com/news/canada/after-the-second-world-war-canada-thought-it-would-be-a-good-idea-to-install-cardboard-sewer-pipes Transcript: https://otter.ai/u/jf8at50nf0KKQG7DrlQAAbCdqH4?utm_source=copy_url Image by DALLE: Victorian house with the second floor redesigned in a modern style, featuring extensive use of glass. Each image also includes the porch with rockers and a poodle.

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! Resources: https://www.theregister.com/2023/12/27/bruce_perens_post_open https://developersalliance.org/open-source-liability-is-coming/ Transcript: https://otter.ai/u/UQyqHKJ9oNd1SquAWWNqGp6oAcE?utm_source=copy_url Image by DALLE: cartoon images of a robot reviewing a long bill of materials on a scroll of paper.

How can companies, enterprises and individuals become more innovative? We investigate the idea of innovation and disruption and continue past where we were with the three horizons model in our previous discussions. Today’s podcast focuses on breaking this apart into adapting an agile disruption, the use of standardization and the cognitive dissonance of innovation, even digging down into distinguishing between inventions and applications. Transcript: https://otter.ai/u/XCidE-0xG7zNmIC7FKEwRrJsPi4?utm_source=copy_url DALL-E Prompt: a factor of rubber chickens getting stretching and upgraded into cybertoys

Let's celebrate the work that we've done as a community in the Cloud2030 group this year, and talk about some really exciting things we have planned for next year for 2024. It's remarkable to look back on how this podcast has evolved from a meeting place during COVID, as a place where we could have those hallway tracks that we had been missing, into something that is really discussing technology at the forefront. The forefront of not just tech, but actually of the human and business implications of that technology. Transcript: https://otter.ai/u/d4Rq_a_tdyihTp5EyzOsnRbQ8jg?utm_source=copy_url Image by DALL-E

This is our annual year review and prediction episode and it is a doozy. We talk through what has been an incredibly busy year in Open Source, cloud repre, repatriation, AI, ML, chatGPT. We laid down some really interesting insights and then looked forward not just into 2024 but two years of predictions and trends that we see happening. We cover what we think will be shaking, shaping and shaking the market. References https://basecamp.com/cloud-exit https://world.hey.com/dhh/the-big-cloud-exit-faq-20274010 Transcript: https://otter.ai/u/13Wdve1WQVCPjXtsf8QnJtg6r0M?utm_source=copy_url DALL-E Prompt: futeristic graphic of a hall of mirrors with 2023 turning into 2024 and the cast of the wizard of oz

How do we apply the principles of lean to data science and data engineering? We discuss this broadly into using AI and machine learning more generally. This is a topic that we had discussed over the summer and wanted to come back to six months later because so much has changed and transformed in the industry. What does agile lean process control look like in an infrastructure automation platform? How can we make these very difficult and challenging components of data and data management, more agile, more lean? I think you will get a lot out of this conversation considering our current hypercharged AI ml and LM environment. Transcript: https://otter.ai/u/1ZuALgSXcPw-bIf2GOumDFZH0UU?utm_source=copy_url DALL-E Prompt: please create a picture of a very large truck stuck under a low bridge. please label the truck as ai and the bridge as lean

If you haven’t had a chance to join in on our book groups, I strongly recommend you take a look at the upcoming books we are reading! Today we discussed Data Science and Context, which is a relatively academic book by a series of doctors, PhDs, Specter, Norvig, Wiggins and Wing. The book gets into some really fascinating analysis techniques, addressing both the practical and ethical implications of data science applications. We discuss the biases inherent in the book, the things that are missing and potentially disruptive to the core assumptions of the book. So even if you haven't read this book, I think you will find the discussion fascinating. This week I'm keeping our warm up discussion about open AI in the podcast. So you will get about 10 minutes of bonus content before the book group discussion as a warm up and it is very related. Our conversations about what has been going on with open AI, their board and Q* are directly related to the concluding ideas in our discussion about Data Science and Context. Transcript: https://otter.ai/u/qYBKNhDBKqaghEaxE-I-mz6xDvg?utm_source=copy_url Image: Data Science In Context cover