The Cloudcast (@cloudcastpod) is the industry's #1 Cloud Computing podcast, and the place where Cloud meets AI. Co-hosts Aaron Delp (@aarondelp) & Brian Gracely (@bgracely) speak with technology and business leaders that are shaping the future of business. Topics will include Cloud Computing | AI | AGI | ChatGPT | Open Source | AWS | Azure | GCP | Platform Engineering | DevOps | Big Data | ML | Security | Kubernetes | AppDev | SaaS | PaaS .
Aaron and Brian review the Year in Cloud, hand out Cloud awards, and discuss the biggest cloud trends from 2025. Maybe a few predictions will be made as well.
SHOW: 985
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2025 CLOUD YEAR IN REVIEW
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How difficult will it be to train and build an AI Agent that has expertise in a given domain? Will it happen in the next year, or 3 years or 10 years? And who will benefit in the marketplace from his evolution?
SHOW: 984
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WHAT WOULD BE THE STAGES OF AN EXPERT AGENT?
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Dan McConnell (Senior VP Product Management at @HitachiVantara) talks about how Enterprise infrastructure is having to evolve to keep up with the data challenges of AI.
SHOW: 983
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Topic 1 - Welcome to the show. Tell us about your background.
Topic 2 - How is AI changing the way enterprises need to think about infrastructure?
Topic 3 - What makes AI workloads so different from traditional workloads? How is AI exposing the limitations of broken cloud environments?
Topic 4 - Where are organizations feeling the most pressure? What are the biggest misconceptions enterprises have about preparing for AI?
Topic 5 - What problems come from managing separate systems? What is the biggest driving factor toward unified data platforms?
Topic 6 - How is Hitachi Vantara helping customers handle the growing infrastructure demands created by AI?
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The PaaS of the future probably doesn't look anything like the PaaS of the past. AI should help bring in an era where we can abstract much more than just infrastructure to align technology and business.
SHOW: 982
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IS PAAS READY TO TAKE THE NEXT STEP?
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Brian Gracely (@bgracely) and Brandon Whichard (@bwhichard, @SoftwareDefTalk) discuss the top stories in Cloud and AI from November 2025.
SHOW: 981
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As the Thanksgiving weekend passes, let's look at some technology things that we're thankful for and excited about.
SHOW: 980
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THINGS TO BE THANKFUL FOR:
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Evan Kaplan (@EvanKaplan, CEO @InfluxDB) talks about Physical AI and the evolving and emerging technologies required to bring AI to physical locations and activities.
SHOW: 979
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Topic 1 - Welcome back to the show, Evan. Give everyone a brief introduction.
Topic 2 - We last spoke in 2019, and our goal with that show was to give everyone an introduction to time series databases. There’s a link in the show notes for those who want to go back and get a refresher. But, if folks aren’t up to speed, give everyone a quick definition of time series and its impacts in recent years
Topic 3 - First, we need to discuss Physical AI. What is Physical AI, and how is it different from, say, GenAI or Agentic AI? It seems that AI in the mainstream equates LLMs with AI, but that isn’t correct. We are talking about deterministic AI, not probabilistic solutions. Can you explain to everyone the difference and why it matters?
Topic 4 - Why is the concept of time series so crucial to Physical AI? Additionally, you provided a great analogy comparing time series data collection to low-resolution and high-resolution images. Can you explain to everyone why this is so important?
Topic 5 - Let’s talk about some use cases. How and where does this intersection of Physical AI and time series impact organizations the most? Is this specific to certain industries (robotics, aerospace, IoT, etc.) or specific collection mechanisms (telemetry, sensor data, etc.)
Topic 6 - Are we shifting with AI to a state that is less reactive and more proactive with an active intelligence?
Topic 7 - What kind of demands do real-time, modern workflows and data streaming place on the infrastructure? When I think of time series, I think of real-time data, which means ultra-low latency and processing near the source, among other things.
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Once again NVIDIA had a record earnings quarter (Q3FY26), but the strength of their on-going success will be dependent on many factors that may or may not be within their control. Let's explore those broader factors.
SHOW: 978
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WHAT WILL BE THE NEW METRICS AND MILESTONES TO TRACK?
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SHOW: 977
Rohan Sathe (@rssathe, CEO @NightfallAI) discusses the rise of Shadow AI, where employees unknowingly leak sensitive corporate data through generative AI tools like ChatGPT.
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Topic 1 - Welcome to the show, Rohan. Give everyone a brief introduction, including your time at Uber Eats.
Topic 2 - How do you define Shadow AI? We hear Shadow AI compared to Shadow IT back at the start of cloud. However, this looks different because everyone's learning curve is much smaller. For Shadow IT to happen, you had to know IT (servers, storage, etc.). Is this the correct way to think about the problem?
Topic 3 - How big is the Shadow AI problem today?
Topic 4 - Normally, data leaks would be discovered by traditional DLP (data loss prevention) tools. In my experience, those tools have been cumbersome and clunky, and you often face the classic trade-off between user productivity and security, as well as the need to lock down access. How has this mindset evolved in the era of AI?
Topic 5 - What happens when AI-powered attacks meet AI-powered defense?
Topic 6 - Let's talk about the technical architecture. How does Nightfall actually work across SaaS apps, endpoints, browsers, and AI tools?
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Is the current level of AI funding and investment rational or irrational? Is it possible that it’s both at the same time? Let’s look at some numbers and the thought process behind them.
SHOW: 976
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DO WE HAVE ANY IDEA HOW TO MEASURE THE IMPACT OF AI?
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James Higginbotham (@launchany) discusses the evolution of API usage across developers, modern applications and APIs.
SHOW: 975
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Topic 1 - Welcome back to the show James. It’s hard to believe it’s been 11 years since we last spoke on the show! Give everyone a brief introduction.
Topic 2 - To say we’ve come a long way with APIs as an industry is an understatement. But let’s set the table for everyone. In your interactions with Enterprise customers, what trends or standards are currently top of mind?
Topic 3 - You wrote an article (link in show notes) titled Lessons after a Decade of API Strategy. What struck me from the article was the combination of technology, business, and even culture, all of which have to come together. When talking to Enterprises these days, have we moved past understanding what APIs are and straight to solving problems with APIs?
Topic 4 - What are the most common use cases you see today? API transformation? API sprawl and consolidation/documentation? Integration of SaaS/3rd party services?
Topic 5 - No conversation would be complete without a discussion about AI and AI’s impact on API’s. I view this in several different ways. AI is creating APIs, and AI is being consumed through APIs. How do you think about AI and its impact? What’s changed and what has stayed the same?
Topic 6 - Second aspect to the AI topic, where and how does security fit into this intersection of AI and APIs?
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