How can we understand agility and adaptability? In this discussion, we get very concrete about the differences between agility and adaptability and why that’s important for you as you go on your own innovation journey.
This includes looking for places where standards can be applied and accelerate your team, where it’s too early, and learning iterations that we would call agile processes more appropriate. We also discuss how teams get caught in the middle between standardization and agility.Transcript: otter.ai/u/vsWqEiJpssWnyqlOCm…?utm_source=copy_urlImage by DALL-E
What does it take to make a good decision? We discuss an interesting take on this as we integrate the topic of how to sell into situations, and selling is the ultimate drive in a decision.
Our conversation mixes the challenges of making decisions as a leader with the challenges of selling into organizations where people have to make a decision to choose your product. It also includes tips on how to frame decisions, how to position decisions, and more.
If you engage in projects and selling them to your boss, supervisor, company, peers, reports, etc – you need to be able to understand why it is important to move forward and make a decision or change. If you’re not able to sell, you’re not well equipped for being a leader.
Today we look at what it takes to have much more collaborative building of automation, templates and shared components that are necessary to really drive platform engineering, and not just between teams at the same company.
We make components for infrastructure automation that bridges the industry because they can be shared much more broadly, similar to the way we share modules in coding languages. We dug into what it takes to make that type of environment work in automation, and what are the prerequisites of the environment?
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.
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.
We discussed the implications of chat GPT for it and the industry.
In today’s episode, we spend a lot of time figuring out how data provenance governance, bias, and ownership will impact chat GPT in IT and technology and cloud contexts. This discussion really looks into how chat GPT can be used in disruptive ways, but also in protective ways as what we describe as guardrails for how these systems are going to get built.
In the Cloud 2030 podcast’s January fifth episode, CEO Rob Hirschfeld explores the complexities of data provenance in ChatGPT, questioning ownership and control of the generated content. He emphasizes the need to understand the sources of data, pondering whether the output belongs to users, the algorithm, or no one, highlighting the challenges of systems that belong to nobody. Hirschfeld also connects this issue with Software Bill of Materials, emphasizing the importance of knowing the components of systems for accuracy and confidence. He encourages listeners to delve into the full episode for valuable insights and invites them to engage further in discussions at 2030.Cloud.
What is platform engineering? And why is it necessary and how to make it work compared to DevOps.
In this conversation, we really hit on the challenges of creating automation teams for building automation in scalable ways. Frustratingly, we never really came up with a particularly good answer to “what is a platform team” and why you should care. Strangely, your organization is probably building one.
Rob Hirschfeld, CEO and co-founder of RackN and host of the Cloud 2030 Podcast, reflects on the November 9th DevOps Lunch and Learn session focused on platform engineering. He highlights the challenge of executing platform engineering initiatives despite the straightforward concept of improving automation and tooling at an architectural level. Hirschfeld emphasizes the importance of defining success metrics, empowering teams to enforce standards, and adopting consistent, repeatable patterns and practices to advance the industry’s maturity. He encourages listeners to explore the insightful discussion at the2030.cloud for a deeper understanding of platform engineering’s significance.
