cloud2030

Emily Friedman's DevOpsDays Ukraine presentation about rethinking the software development lifecycle or SDLC sparks our conversation today. She describes looking at it as a multi-dimensional cross functional discipline, that actually accounts for six different vectors of capabilities that need to be factored in - a resilient and robust look at the SDLC. Watch her YouTube: We found that the model does not cover all of the things that we've been discussing as important things to consider in building, deploying, and making software resilient and reliable, most specifically software, build materials, or s bombs. Transcript: https://otter.ai/u/zp0uAu_xis_1fb66sSZlywN0QRo?utm_source=copy_url Image: https://www.pexels.com/photo/photo-of-orange-pinwheels-3580452/

What are the human and management factors that go into building great platform engineering? And what are the efforts of control having too much control or too much flexibility, not enough collaboration, not creating space for innovation, and changing inside what's inside these platform engineering efforts? Today, we discuss centralized versus decentralized platform engineering, or as came up in the conversation about platform engineering, it's the opposite of Java Enterprise, version and platform. As you're doing this type of work interacting with platform teams should influence how you design and authorize the effort to make that work. What type of slack you need to put in the system and what type of authority needs to be given to the platform engineering team. Transcript: https://otter.ai/u/ySGeMTU_qFeeBbENz4-L7FFG-Yo?utm_source=copy_url Image: https://www.pexels.com/photo/keyboard-keys-lot-373072/

We check in on data gravity to see how generative AI and conversations about metadata and thinking on data lakes impacts data gravity thinking in general. Data gravity is a concept that has been propagated by David McCrory, a friend of mine, who defined this idea that data itself, the aggregation of data, the use and transit of data has a gravitational effect. That it pulls more data to it as well as workloads towards it. We jumped right into impacts of data gravity in this conversation. Transcript: https://otter.ai/u/qKf75W8OvZHkMtVQRM1M2vi5_qE?utm_source=copy_url Image: https://www.pexels.com/photo/action-animal-bronco-bucking-33251/

Is hardware going to be innovative and change? Brian Cantrell brings up oxide computing and some of their design motivation. Today we discuss our skepticism about some of his points, as well as the impacts for cloud distributed Compute hardware design mainframes, cloud, repatriation, and a whole bunch of topics about next generation thinking in Compute infrastructure management and applications. We are officially starting our cloud2030 book group and I hope you will join us - we are going to be reading Data Cartels by Sara Landon, followed by Investments Unlimited by John Willis and crew. Book Clubs Links: May 4 > Data Cartels https://www.amazon.com/Data-Cartels-Companies-Monopolize-Information/dp/1503633713 Early July > https://www.amazon.com/Investments-Unlimited-Compliance-Thriving-Digital/dp/1950508536 Transcript: https://otter.ai/u/S7CRv2J9fmOjAc8HM_TG9PM3eUw?utm_source=copy_url Image: https://www.pexels.com/photo/a-man-standing-on-gray-hot-air-balloon-9128460/

How does AI chat and generative AI have the potential to disrupt everything we know about social media? Today we talk Twitter versus mastodon. We spend most of our time talking about the power, influence and simple use cases for generative AI. Is this going to break Mastodon, Twitter and other forms of social media? We have a pretty compelling conversation about that, too. If you're a fan of Mastodon and Twitter, jump forward to about 30 minutes in when we really start getting down to that topic. Stay tuned for our agenda as a bonus extra in the back half of the podcast. Discussed Links: https://jounce.ai/ https://techcrunch.com/2023/02/28/jack-dorsey-backed-twitter-alternative-bluesky-hits-the-app-store-as-an-invite-only-app/ https://www.primal.com/about-us/ https://techcrunch.com/2023/03/01/addressing-criticism-openai-will-no-longer-use-customer-data-to-train-its-models-by-default/ Transcript: https://otter.ai/u/cVUTxHkYrJ_BhfZetm91mvxlstI?utm_source=copy_url Image: https://www.pexels.com/photo/bird-sitting-on-top-of-an-elephant-12118214/

What is generative AI and what are people now just generically calling ChatGPT? We put these things in a technical frame, meaning can we use generative AI to improve our programming, testing or automation? What does it take to use these concepts in ways that iteratively improve IT infrastructures. We review the state of chat, ChatGPT, AI infrastructure and things like that. Transcript: https://otter.ai/u/nFCSMPFyUVHO50I0jGP2HXCas7c?utm_source=copy_url Image: https://www.pexels.com/photo/woman-leaning-on-washing-machine-15625100/

Is platform engineering effective at hiding complexity from developers? Today we tear apart what platform engineering is doing, how it came about and what it's trying to be. We discuss what companies are trying to accomplish with platform engineering - how can successful efforts improve outcomes for development teams and operations teams by improving collaboration in contracts? Why and how is that important, and what do those efforts entail? Transcript: https://otter.ai/u/bVd1_IwEqFD-uEYxsyuffhNTeG4?utm_source=copy_url Image: https://www.pexels.com/photo/woman-posing-with-mirror-underwater-15674505/

How can the intersection of generative AI machine learning and artificial intelligence be applied to environments using digital twins? Today we discuss digital twins and artificial intelligence. How can we improve the simulations, the systems, the interactions that we build? How can we correctly model complex components of everything from cars to pumps in ways that allow us to then build on top and build more intelligent systems. We come up with some grounded examples. Mentioned: https://projectarrow.ca/ Transcript: https://otter.ai/u/A79s08jpJ4-UPyT3132EfU-5DaY?utm_source=copy_url Image:https://www.pexels.com/photo/two-bernese-mountain-dogs-lying-on-floor-9040438/

Platform engineering is quite buzzy and has a lot of hype at the moment. Today we dug behind the hype to acknowledge how the term is being used and misused. We cover why this is a topic of interest, how it’s driving customer thinking around operations and development teams, how it's working to establish standard operating procedure around infrastructure and operations to support a business, and how those needs drive the evolution of our technology, infrastructure and design thinking. Transcript: https://otter.ai/u/GksMnMIZV0cyM6iwWj_sAd8yNhU?utm_source=copy_url Image:https://www.pexels.com/photo/person-in-black-vest-holding-fan-of-cards-6255293/

We break down the edge compute cluster by the Chick-fil-A team, and we talk about how they use Kubernetes, specifically K3s in 2500 of their restaurants to build an IoT and restaurant management system. This system uses Intel Knucks, a commodity commercial residential grade hardware. It’s an update on a four year old Kubernetes story with a lot of buzz, and they show how they have been successful building this system. If you're interested in Kubernetes, Edge DevOps and distributed systems, this episode has a lot to enjoy. Transcript: https://otter.ai/u/i0lBYq9PNQevn0AIvXNX9BpnpbM?utm_source=copy_url Image: https://www.pexels.com/photo/person-in-black-vest-holding-fan-of-cards-6255293/