Azure Softness + AI Capex = The Public Cloud's New Problem

Azure Softness + AI Capex = The Public Cloud's New Problem

Why did Microsoft stock drop even after a headline beat? In this episode, cloud analyst David Linthicum breaks down the market's "beat-and-drop" reaction to Microsoft's latest earnings and what it signals about Azure, AI, and hyperscaler spending. He explains how expectations for a clear cloud re-acceleration collided with guidance that sounded more like "we're investing ahead of demand," raising concerns about capital intensity and near-term margins. Linthicum walks through the optics around Azure growth, capacity build-outs for AI training and inference, and why investors are increasingly sensitive to capex without fast operating leverage.

The conversation also explores a structural shift in enterprise cloud choices—hybrid, private and sovereign cloud, colocation, and managed service providers—and how workload economics (egress, governance, and consumption creep) can make public cloud less attractive for steady-state compute. Finally, he balances the bear case with the bull case: Microsoft's distribution advantage across Microsoft 365, security, and developer tools, and the possibility that today's spend is strategic moat-building. If you want a clearer framework for reading cloud earnings, this video delivers. You'll learn what metrics to watch next quarter, how to interpret "capacity constraints" versus demand, and where AI monetization may show up first in pricing, usage, and margins.

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AI Workloads Are Breaking Cloud Budgets. Does Managed Cloud Fix That?

AI Workloads Are Breaking Cloud Budgets. Does Managed Cloud Fix That?

Try InMotion Cloud free for up to 30 days: https://inmotioncloud.com/david-linthicum Sponsored by InMotion Cloud. AI is reshaping the economics of cloud computing. It is not just adding more workloads...

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The AI Data Center Lie Is Falling Apart

The AI Data Center Lie Is Falling Apart

The AI infrastructure story was always bigger than GPUs, bigger than cloud announcements, and bigger than vendor promises. The real issue was power. For the last few years, hyperscalers, analysts, and...

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The Hidden Career Trap Holding Women in Tech Back

After decades of working in cloud computing, enterprise architecture, AI, and digital transformation, I've seen one thing clearly: technical success is not just about who knows the newest platform, to...

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Edge Computing Does Not Always Need the Cloud…Duh!

Edge Computing Does Not Always Need the Cloud…Duh!

Edge computing does not always need cloud-based back-ends, and pretending otherwise is one of the most expensive architectural mistakes in enterprise IT. Too many teams still assume that every edge de...

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From Automation to Automated Automation: The Next AI Revolution

From Automation to Automated Automation: The Next AI Revolution

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Why Enterprises Keep Getting Multicloud Wrong

Why Enterprises Keep Getting Multicloud Wrong

For the past decade, enterprises have treated multicloud as the logical next step in cloud computing evolution. The promise was simple: more flexibility, less vendor lock-in, better resilience, and th...

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We Were Lied to About Cloud Costs — And I Have the Videos to Prove It

We Were Lied to About Cloud Costs — And I Have the Videos to Prove It

This video looks back at how cloud computing costs were discussed roughly 10 to 15 years ago, during the period when public cloud platforms such as Amazon Web Services, Microsoft Azure, and Google App...

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Why Some Cloud Tech Workers Have To Pay To Quit

Why Some Cloud Tech Workers Have To Pay To Quit

If you think quitting a job is a simple matter of giving notice and moving on, this story may change the way you see work entirely. Across the tech and cloud computing world, more employees are findin...

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