Today we tackle the generational infrastructure shift that’s keeping IT leaders awake at night: OpenShift virtualization adoption. We dig deep into why organizations are struggling to migrate from traditional VM-focused infrastructure to Kubernetes-managed infrastructure. We explore the real hurdles blocking this transition and unpack the strategic positioning that matters when you’re moving to container-orchestrated infrastructure. This isn’t about dumping everything into Kubernetes and calling it done, we examine what it really takes to use Kubernetes as your infrastructure abstraction layer while navigating the operational realities that make or break these migrations.
We dive deep into the current state of the venture capital (VC) market, exploring the significant shifts and challenges faced by entrepreneurs and investors alike in the post-COVID landscape. Key topics discussed include:
The decline in the allure of VC funding and the impact of “pump and flip” models
The market volatility and caution among venture firms due to economic factors
The changing focus of VCs towards sectors like healthcare, fintech, and deep tech
The challenges in building sustainable, billion-dollar companies
The rise of corporate venture capital and strategic investments
The potential for rational valuation adjustments and market consolidation
The importance of clearly articulating the problem being solved and achieving product-market fit
The conversation provides valuable insights for founders navigating the evolving VC ecosystem, as well as investors seeking to adapt their strategies to the changing market dynamics. Join Rob and Rich as they explore the future of VC and the strategies needed to succeed in this dynamic landscape.
A dense and thoughtful book, it is straight up the alley of the type of conversations of the2030.cloud has. Our analysis of the book and the challenges it provides – the data compliance governance, the legality, the threat, and broader implications of what Dr. Lambda lays out – are all really important.
Today’s podcast is understandable and interesting without having had to go through and read the book, but I still recommend that you do.
How do we sustain open source? Today we discussed how the commercial models and sustaining models around open source are changing and evolving.
We also included some conversations about whether or not generative AI might actually change the economics around that part of open source. We hit on top projects, open source hardware, open source, operating systems platforms, a whole gambit, and how it fits together into a sustainable model for the users, companies, enterprises, and really everybody. We all use open source to one extent or another.
We have our book club coming up on data cartels, we’re going to be discussing it on May 4th and I hope you take the time to read and come join us.
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.
In a discussion on the DevOps Lunch and Learn podcast, Rob Hirschfeld, CEO of RackN, explores the complexities of generative AI and its impact on coding and automation. Hirschfeld raises questions about trust in generative AI models, emphasizing the need to understand how they are trained, updated, and refined to eliminate errors. He highlights the importance of creating reliable training sets to ensure the technology’s applications, focusing on enhancing system resilience and maintainability.
We talk about understanding analyst reports and engaging with analysts. How do analysts shape the industry and the industry shapes the analysts?
Today we discuss how every part of this ecosystem has to work together in order for us to build serviceable technology, because fundamentally, we count on the analysts to help understand what’s ready, what the problems are, and what’s working or not working in the enterprise.
It’s easy to pitch stuff, it’s much harder to use stuff and sell tech, and the analysts are a reasonable filter for that, and we break down how and why.
In the September 27th Cloud 2030 Podcast, Rob Hirschfeld provides insights into the dynamics of reading analyst reports. The discussion highlights the bi-directional nature of communication between analysts and enterprise customers, emphasizing a feedback loop where analysts absorb insights from the market while customers are influenced by market buzz and marketing efforts. Hirschfeld encourages participation in these conversations at the2030.cloud, urging listeners to join roundtable discussions and make their voices heard in this collaborative space.
How do we help junior people build the right skills to do advanced automation system administration, and actually build systems that are resilient and robust? Then, after understanding that that is a learned skill that’s predominantly learned by doing the work, troubleshooting.
We started the conversation talking through how to teach troubleshooting and find opportunities for that. But we transformed the discussion into the challenge of teaching people skills that they then walk away with, that, as you’re mentoring people, you’re increasing their value, and potentially giving them the keys to leave and find a better job.
We talked about this as an industry trend, and some expectations on what you can do about it, and how you can approach that situation. Overall a very robust conversation about building great teams, through junior engineers, and what it takes to be thorough and complete in a process like that. Both from what you can do, and what you have to watch out for.
In the September 13th Cloud2030 Podcast, Rob Hirschfeld shares insights on mentoring junior DevOps engineers, emphasizing the importance of troubleshooting for their learning process. He highlights the hands-on nature of operations and admin work, where individuals encounter challenging problems, learn on the job, and understand solutions by fixing issues. Hirschfeld stresses the need for a supportive environment that allows junior team members to learn without time pressure, fostering a culture that encourages experimentation and learning through doing.
This discussion is about the infrastructure behind augmented reality. We really dive into how augmented reality will take place in our environment. And the spoiler is it AR is already here!
We are actually building augmented reality systems everywhere and they’re showing up in our daily lives. The group believes very strongly that the automotive space is already leading AR for a whole bunch of reasons, including ease, progress so far, and profit motives.
We also talked about why it’s so hard to build the networks of infrastructure that need to be consumed or make augmented reality so much easier.
Hello, I’m Rob Hirschfeld, CEO and co-founder of RackN, hosting the Cloud 2030 Podcast. In the February 8th episode, we explored augmented reality infrastructure, emphasizing the need for embedded sensors and beacons rather than traditional server and network components. The discussion highlighted challenges in creating ubiquitous sensor networks for augmented systems, especially in municipal settings. The conversation delved into the complexities of building such networks, crucial for the future of augmented reality interactions. Explore this topic and more on the2030.cloud; join the conversations shaping the future.
We seem to be very worried about complexity in technology, but how bad is it really? Do we have a way of measuring complexity? Figuring out how to actually quantify it could help eliminate and manage it.
We started by discussing mathematical concepts to capture the systemic nature of complexity. That turns out to be really hard, so we got into some really interesting thoughts about what it takes to manage and understand complexity. Is it even possible to measure complexity? The group is mixed.
We know that humans have trouble keeping systems updated, but… how can we address the challenge of knowing which updates are required and, critically, if the updates with break other systems? Even knowing if they worked is a really thorny problem!
In this episode, we focus on actions about what’s going on and why this problem has persisted in industry for so long. Starting from the news of the day about CentOS 8 mirrors being taken down. That’s exactly the type of challenge we are facing when we think about where updates and repos are coming from.
Rob Hirschfeld, CEO and co-founder of RackN, discusses the challenges of system maintenance and lifecycle in the Cloud 2030 podcast. He emphasizes the difficulty of keeping systems up to date and understanding dependencies, leading to a lack of confidence in system updates due to the fear of breaking or degrading them. Hirschfeld advocates for a change in the industry to prioritize test and verification practices, enabling more effective and confident system updates.
