Category Archives: Cloud Computing

AI And Platform Migration

A conversation about platform migration turned into an interesting topic about the end of expertise and the changing of the way we think about expertise in a variety of contexts.

How can platform improvement be radically transformed by the use of AI? We discuss entering a world where the lock that we’ve had in a platform, or the longevity of a platform, is radically transformed by the ability to review, scan, test, correct, and transport the data included in that system. The expertise needed to handle platform migration might be entering a new era in which it’s radically reduced. What are the implications of those transformations?

We address a wide range of the impacts of knowledge, AI, and generative machine learning.

Transcript: otter.ai/u/4nL-a5_7dMhYBsvSFP…?utm_source=copy_url
Image: www.pexels.com/photo/shepherd-do…of-sheep-5384726/

Cloud2030PlatformArchitectureCloudDigital TransformationLift and Shift

Rob’s Hot Take:

In the May 6th episode of the Cloud 2030 podcast, the discussion revolved around the diminishing significance of expertise due to advancements in AI and ML technologies. Rob Hirschfeld, the host, emphasized how various fields, from law to data science, traditionally reliant on specialized knowledge, are being impacted by AI, challenging established barriers of expertise. The episode explored the transformative implications of AI on different sectors, suggesting that this theme will be a focal point in future podcasts and discussions on 2030.cloud.

Ops After Kubernetes

How has Kubernetes changed our industry? Today’s discussion is part of a multi podcast conversation in which we’re going to think about ways in which Kubernetes could go away, or could influence other technologies in such a way to be transformative.

We went down the path of what we have learned from Kubernetes and how it influences other aspects of IT operations, architecture and design, and explored the impact that the expectation for declarative immutable operational constructs will play into other aspects of our system. We also discuss micro LS microkernels and how operations are staged to talk about the need for declarative OS, banking on this idea that what Kubernetes has built extends into other areas.

Chat GPT Summary:
“The conversation is part of a multi-podcast series focused on exploring ways in which Kubernetes could influence other technologies, as well as the potential consequences if it were to disappear.
During the discussion, the group delved into the lessons learned from Kubernetes and its impact on various aspects of IT operations, architecture, and design. One key takeaway was the importance of declarative immutable constructs in managing the complexities of modern IT systems. The group also explored the potential for microkernels to revolutionize system design and emphasized the need for declarative operating systems.
Overall, the discussion highlighted the transformative role that Kubernetes has played in shaping the IT industry and underscored the importance of adopting a declarative, immutable approach to managing complex IT systems.”

Transcript: otter.ai/u/7SMjDGwHTMLmfaCACk…?utm_source=copy_url
Image: www.pexels.com/photo/submarine-m…-harbor-14707646/

Metadata Architecture

Every time we look at data analytics and data systems, the idea of having a way to manage control and explain the data is actually as important as the data itself. This episode is all about metadata, specifically, metadata related to data analytics analysis, Big Data computation, sort of the data lake metadata problem.

Today we discuss the challenges of data management, but also the potential of understanding so much more about how data is used. If you are an IT professional or a data professional, you will find this conversation about how we’re going to draw inferences, manage and control all of that data that were collected fascinating.

Transcript: otter.ai/u/dFF6CfBYOMR3QFydae…?utm_source=copy_url
Image: www.pexels.com/photo/woman-stand…-mirrors-6208385/

The Evolving SDLC

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: otter.ai/u/zp0uAu_xis_1fb66sS…?utm_source=copy_url
Image: www.pexels.com/photo/photo-of-or…inwheels-3580452/

Decentralized Platform Engineering

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: otter.ai/u/ySGeMTU_qFeeBbENz4…?utm_source=copy_url
Image: www.pexels.com/photo/keyboard-keys-lot-373072/

Rob’s Hot Take:

In the Cloud 2030 Podcast episode on March 14th, Rob Hirschfeld discusses the importance of adopting a system-wide view in platform engineering, emphasizing the need to identify over-optimization in certain areas like developer productivity while underestimating other critical aspects such as operations, security, or compliance. Hirschfeld advocates for a holistic approach to platform engineering, focusing on optimizing the entire system, streamlining teams, and making strategic trade-offs rather than just emphasizing technology or developer productivity. He suggests that this mindset can lead to improved efficiency, productivity, and return on investment for platform teams, highlighting the significance of considering the broader organizational context. Hirschfeld encourages listeners to explore the March 14 episode for a deeper understanding of these concepts, available on the 2030.cloud platform.

Data Gravity vs AI and Metadata

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: otter.ai/u/qKf75W8OvZHkMtVQRM…?utm_source=copy_url
Image: www.pexels.com/photo/action-anim…co-bucking-33251/

Deflating Cloud Mythology [+ book club]

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 www.amazon.com/Data-Cartels-Comp…ion/dp/1503633713

Early July >
www.amazon.com/Investments-Unlim…tal/dp/1950508536

Transcript: otter.ai/u/S7CRv2J9fmOjAc8HM_…?utm_source=copy_url
Image: www.pexels.com/photo/a-man-stand…-balloon-9128460/

Digital Twins + AI = WOW

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: projectarrow.ca/
Transcript: otter.ai/u/A79s08jpJ4-UPyT313…?utm_source=copy_url
Image:www.pexels.com/photo/two-bernese…on-floor-9040438/

Rob’s Hot Take:

In the Cloud 2030 podcast episode on digital twins and AI, Rob Hirschfeld discusses the potential of using digital twins in handling real-world disasters, citing the recent train derailment in Ohio as an example. The concept involves quickly creating a digital twin of a disaster space to enable robots to learn, adapt, and efficiently mitigate the situation. Hirschfeld emphasizes the unprecedented opportunities for improving environmental interactions, responding to crises, and highlights the sophistication of ideas discussed in the episode. He encourages listeners to explore the full conversation on digital twins and AI at the2030.cloud.

Chick-Fil-A Edge Kubernetes Deep Dive

https://soundcloud.com/user-410091210/chick-fil-a-edge-kubernetes-deep-dive

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: otter.ai/u/i0lBYq9PNQevn0AIvX…?utm_source=copy_url
Image: www.pexels.com/photo/person-in-b…of-cards-6255293/

Rob’s Hot Take:

In the Cloud 2030 podcast episode on Chick-fil-A’s Kubernetes control plane, Rob Hirschfeld highlights the challenges and benefits of transitioning cloud infrastructure and applications to edge locations using commodity gear. He emphasizes the success of Chick-fil-A’s approach in bringing cloud tools and platforms to non-cloud environments, showcasing the potential for mapping cloud processes back into edge computing. Hirschfeld encourages listeners to explore the detailed discussion on Chick-fil-A’s edge clusters and engage in broader conversations on Cloud 2030 at the2030.cloud.

Improving Time To Decision

https://soundcloud.com/user-410091210/improving-time-to-decision

How do we improve the time to decision for CIOs? Today we talk about general business practice and how we can help.

Technical innovators and architects create value for the teams that they support. This can either be from an automation perspective, which is what RackN does, or from a data perspective, which Tyler describes in the podcast today. These are real challenges.

When we flip the script and talk about the miscommunication between how CIOs see business challenges and translate business challenges into technical delivery, however, we get into a fascinating set of discussions where Joanne brings up some key challenges for 2023. We also discuss mapping those from CIOs into implementation, followed by ultimately trying to find ways that people can make fast, valuable decisions that feel right.

This conversation is rooted in important conceptual executive level thinking. We’ll include the list of points that Joanne talks about below as well as in the show notes, and I highly recommend you check those out.

Joanne Friedman’s Key Challenges for 2023
1. Tackle inflation and margin pressure
2. Migrate supply chain disruption
3. Make sustainability a pillar
4. Calibrate talent management strategy
5, Streamline procurement and sourcing
6. Strengthen digital thread
7. Prioritize innovation initiatives

We try to name these key challenges, but in a lot of cases we are talking about the list or the graphic. You’ll need to refer to the show notes in order to see the complete one.

Transcript: otter.ai/u/sFESW3yziGOolNbiyt…?utm_source=copy_url
Image: www.pexels.com/photo/man-holding…er-board-1117132/

Rob’s Hot Take:

In the Cloud 2030 podcast episode dated February 9, CEO Rob Hirschfeld discusses the challenge of making fast, impactful decisions in a rapidly changing technological landscape. He emphasizes the importance of intuitive understanding and emotional context in decision-making, highlighting the need for clearly articulated goals and consensus building beforehand. Hirschfeld advocates for executives to rely on their intuition, grounded in a solid foundation of groundwork, and invites listeners to engage in ongoing discussions on this topic at 2030.Cloud.