Talking the Future of Tech
We dive into data operations in today’s episode! We cover the idea that with all of the work we’re doing in AI and ML data analytics analysis, you actually have to steward your data.
We also cover processes controls, like what we have with DevOps in infrastructure, but with similar types of concepts (governance controls automation) around how your data is flowing in your system.
Transcript: otter.ai/u/pesotDnHCCD5lyPVx7…?utm_source=copy_url
Image by DALL-E
Departing from our typical podcast format, today’s episode is part of a presentation that I’ve been preparing about comparing 125 year old house building architecture to modern DevOps. We also analyze as things that work and don’t work.
There are a lot of home maintenance stories and comparison notes. Particularly in the back half of the episode we get into how this type of challenge relates to Operations Management.
Refereces: nationalpost.com/news/canada/afte…oard-sewer-pipes
Transcript: otter.ai/u/jf8at50nf0KKQG7Drl…?utm_source=copy_url
Image by DALLE: Victorian house with the second floor redesigned in a modern style, featuring extensive use of glass. Each image also includes the porch with rockers and a poodle.
What does it take to implement governance and compliance, because they are process controls much more than individual technologies. Today we discuss that a lot of the talks seem to be about governance and compliance, and we have a fascinating discussion about governance compliance and Kubernetes.
The idea that Kubernetes is maturing, losing the drama that is a hallmark of its first decade now and moving into a focus on managing how to control and have security, compliance and normality. Yet all of those things have a degree of tension with the vendors and users, which puts single choice compliance and governance
in direct conflict with open source competitive ecosystems.
This makes for a fascinating conversation where we touch on some really important issues for the industry.
Transcript: otter.ai/u/mAkvsYgMYMp_W8Bizk…?utm_source=copy_url
Image: Generated by Dall-E
What’s going on from VMWare to Broadcom to HashiCorp and their license changes. We discuss current topics, even to the sad news about Kris Nova passing during a mountaineering expedition.
If you’d like to catch up on the tech news, then this topic hopefully has aged well and you will enjoy it!
Transcript: otter.ai/u/J18ecRKKwc8As_TLyC…?utm_source=copy_url
Photo by Oziel Gómez: www.pexels.com/photo/man-wearing…-mountain-925263/
We talk about DataOps, but if you’re expecting this to be DevOps for data – you are mistaken. Today we talk about engineering data through the idea of data stewardship or how you manage and control the data.
Beyond permissions and access into the costs and how things are stewarded, how logs are handled, who controls how much access and how quickly people have access, where you’re putting the data to improve its effectiveness, and more. There is so much going on above the infrastructure, but below that actual analytics, this conversation will open your mind to a whole layer of challenges related to governing and managing data.
Transcript: otter.ai/u/SDaRomv41JtQYM7a6C…?utm_source=copy_url
Photo by Taryn Elliott: www.pexels.com/photo/person-hold…g-on-top-4099125/
This is the second installment of our book group, which is a discussion about Investments Unlimited. We have one of our authors, and a great all around DevOps enthusiast, John Willis, on the call with us.
As you might expect, while we talk about the book and John gives a lot of background and details about the book, we treat it with the classic cloud2030 style, and bring in AI, large language and advanced DevOps.
We take the topics of the book to the next level, and frame it in the moment of the year, looking beyond and into how the concepts of compliance, validation, team coordination and risk assessment are incorporated into the coming AI and how it changes in our landscape.
Sources
Book www.amazon.com/Investments-Unlim…tal/dp/1950508536
techstrong.ai/aiops/the-rise-of-shadow-ai/
guidehouse.com/insights/financia…-lines-of-defense
Transcript: otter.ai/u/uC9c3xJS4oATQx7BrY…?utm_source=copy_url
We use ChatGPT to live create DevOps, automation, Ansible, TerraForm, Python, and interact with different clouds to get advice on how to set up clouds.
This discussion includes a screen share session, so if you’re listening to this audio there will be times when we are talking about something you can’t see but I do make a point of working to explain what we’re doing. There’s also a video of the screen share session if you prefer.
Video: youtu.be/hU7pUDfliGk
Transcript: otter.ai/u/MPvT7SP0FCSe02asm8…?utm_source=copy_url
Image: www.pexels.com/photo/pink-backgr…ch-bubble-1111369
What can we expect generative AI to generate and is it going to produce good code? Today we talk about Gluecon and generative DevOps and the different concepts and capabilities around it. What impact is it going to have on developers? How do we control that?
Today’s discussion was in preparation for our session on June 13, where we’re going to group program GPT to see what type of DevOps coding skills we can prompt. We talked about the necessity of prompting in this session and covered some tips to help you think about how to be a better prompt engineer, a skill set that everybody’s going to need to have in the next months if not years.
Transcript: otter.ai/u/lsye_htH0-wksAOrqg…?utm_source=copy_url
Image: www.pexels.com/photo/man-welding…ow-frame-2965260/
NOTE: This is Rob’s Gluecon topic on 5/24. Save $300 if you register with speaker300 at www.gluecon.com
We dive into the question of whether or not generative AI can be used to productively change DevOps automation and the control of infrastructure.
We’ve discussed the closed loop side of using AI to manage infrastructure in the past, but this episode we really dive into the idea of creating automation and using generative AI.
Transcript: otter.ai/u/VtnznHgydT3_6QSJpk…?utm_source=copy_url
Image: www.pexels.com/photo/tossing-fri…ying-pan-6937457/
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?
How do we structure automation?
Transcript: otter.ai/u/IPyFDG19OCH-UekM7P…?utm_source=copy_url
Image: www.pexels.com/photo/doctor-oper…-patient-4421494/