Hachyderm.io Leaves Basement


Hazel walks us through the Hackyderm.io leaving the basement migration. We also talk much more generally about Mastodon fediverse and scaling distributed systems.

This podcast is like a super class in what it takes to scale infrastructure and systems, especially live and under duress. Every minute of this conversation is worth listening to twice.

Check out these resources as well:

Transcript: otter.ai/u/FBIjekCBWcd8tlj1v-…?utm_source=copy_url
Image: www.pexels.com/photo/elephant-cu…ya-savanna-66898/

Retail Edge Kubernetes ala Chick-Fil-A


We get an update for the first time in four years about Chick-fil-A edge Kubernetes clusters that gets to the heart of how building distributed infrastructure works and what the challenges are.

Article: medium.com/chick-fil-atech/ent…ompute-f5e2fd63d20f

We had a fantastic conversation about laying the foundations for this. We came away with two really important thoughts about what edge infrastructure looks like, how you pick it, can Kubernetes be used, what is IoT and integration, and the design considerations that go into building this environment.

Listen to this podcast as a preview for a longer article.

Transcript: otter.ai/u/k3Y7S3Hoa0rPZZ8_L5vTn4SNwGI
Image: www.pexels.com/photo/cows-on-fie…andscape-8899447/

Platform Engineering on API Abstractions


Our mini episode today is a short discussion of API delineation and abstractions for platform engineering.

This was a short intro discussion, and it is especially interesting because platform is a major topic we will be exploring in the coming year. We highlight the challenges of finding the right abstraction points as well as building front end and back end automation.

Transcript: otter.ai/u/5gzoEliQ5H7N5LnGSP6sdOFNjv8
Image: www.pexels.com/photo/white-paper…te-table-7897470/

Stochastic Parrots And Processes


Today is a one on one discussion between me and Rocky Grover about infrastructure, infrastructure patterns, AI, and how all of these systems connect.

We think deeply about what it takes to design great systems and cover a ton of ground to connect it all back together into systems design. Rocky has a lot of depth of experience here.

Transcript: otter.ai/u/EYgaZUm5s36KYrUhDIwcXTkLHcA
Image: www.pexels.com/photo/bird-blue-zoo-large-52549/

ROI from Putting Data In Context


If you love data and data context formats for exchanging data, you will love this conversation.

Today’s episode is a deep conversation about the potential ability to define ways in which we produce, store and share data, providing context using markup languages, and then being able to extend that. It’s a fascinating conversation about how much we could improve our use of data if we were able to provide more context about who wanted to see it and what relevance it had.

We also have some interesting conversations about data migration and how we share information.

Transcript: otter.ai/u/S9_tibMGhkoajG0bP8LaciJ32Ys
Image: www.pexels.com/photo/a-grayscale…is-hand-10839215/

Exploring Backstage.io Integration

Today we talk about backstage.io, and we have that conversation centered around a demo done by one of the RackN and interns, Zander Franks. Check out the demo video here: youtu.be/cAQQOmKz4OI

Zander has been exploring with the backstage to Digital Rebar integration, and the conversation that results explains backstage in some fundamental ways and also what it takes to build good developer portals.

You will find in this episode both the broader information about how to do integrations where you have a developer portal as a front end and the key insights about how backstage works.

To get the most out of the backstage pieces, you will definitely want to see the video on Youtube. Take time to enjoy this whole podcast, both in video and audio format.

Transcript: otter.ai/u/xWx-q_ZvK4oX1sDJS09F1BsaZZI

Chat GPT In IT

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.

We come to some very interesting conclusions.

Transcript: otter.ai/u/aETNeRoDnspFnmPT3KcjBuHQTzE
Image: www.pexels.com/photo/surprised-y…le-phone-3771127/

Balancing Architecture and Ease of Use

What is the architectural balance between learning curve, architecture, building things that can scale while acknowledging overhead, and the attitude of just get it done? Don’t make my tools complex and let me be very productive quickly. If it doesn’t scale, then we see this as an ongoing challenge.

Two engineers from RackN led today’s discussion in which we really talked about the balance that we try to achieve at RackN as we design our product, with the understanding that, ultimately, scale really does matter.

If users have trouble understanding how the product works, at first, that learning curve can push people away, so that they never actually get into the product. That’s where finding the right balance is absolutely essential to success.

Transcript: otter.ai/u/DAfKcHVBAiOY5EuReW1krDYsqso
Image: www.pexels.com/photo/anonymous-w…h-outfit-7148032/