Screaming in the Cloud

What happens when cloud economics meets the messy reality of business, AI, and human behavior?Corey and J.R. Storment unpack why cloud cost management is less about math and more about psychology, the real difference between FinOps for AI vs. AI for FinOps, and why automation still struggles with edge cases (despite all the hype). Along the way, they explore multi-cloud complexity, the rise of consumption-based pricing, and how businesses are navigating massive, unpredictable spend across cloud, SaaS, and AI platforms.If you’ve ever wondered why your cloud bill feels like chaos, or how to actually get value from it, this episode pulls back the curtain.Show Highlights:(00:00) FinOps Royalty Reunion(03:06) Origin Stories and Naming FinOps(06:32) AI for FinOps vs FinOps for AI(11:05) Automation Hype and Human Psychology(22:16) Contracts Multi Cloud and Commitments(24:26) Context Beats Optimization(26:06) Trust and Billing Clarity(28:14) Focus Standard Flywheel(30:11) SaaS Coverage and Conformance(34:06) Contracts Multi-cloud and Wrap UpLinks: FinOps: https://www.finops.org/Sponsored by: duckbillhq.com

Roi Lipman, CTO and co-founder of FalcoDB and former RedisGraph builder, shares his passion for graph databases and systems programming. He discusses why graphs shine on pathfinding and access problems. They cover vector search becoming a feature, the move from RedisGraph to FalcoDB, Rust rewrites, open source tensions, and AI’s messy impact on development.

Chris Hill, founder of HumblePod and podcast lecturer, joins to unpack AI’s real role in media. They recount a stealthy voice-clone ad and debate where automation helps versus when human judgment matters. Conversation covers studio builds, why “good enough” production often wins, gear and on-camera tips, and podcasting’s move toward video-first short clips.

Eric Anderson, a VC partner at Scale and former product lead at AWS and Google, explains why coding agents rewrote software's rulebook. He discusses agents doing code review and workflow automation. They debate how startups can pick the right front to compete with frontier labs, and why an AI bubble and pricing shakeouts feel inevitable.

Chase Douglas, CEO of Archodex and former AWS principal/CTO-level engineer, builds AI governance and compliance tools for enterprises. He talks about Shadow AI risks and why centralized pipelines matter. He describes running isolated accounts for experiments, chaotic model availability and pricing, and why re:Invent felt stranger this year. He ends upbeat about spec-driven AI coding workflows.

Alyss Noland, a cloud developer ecosystem problem-solver at NVIDIA who helps startups access GPUs, talks about building software with AI and enabling nontraditional developers. Conversation covers using AI as a curator and writing assistant, DGX Cloud Innovation Lab for startups, orchestration and safety of agents, and the weird social dynamics people form with chatbots.

Mike McQuaid, project leader of Homebrew and steward of the macOS/Linux package manager. He recounts Homebrew’s pub-born origin, the rise of Brew Bundle for one-command Mac setups, casks for GUI apps, auto-update tradeoffs that support millions of users, maintainer stipends and review-based security, and why Homebrew enforces strict open source rules.

Omri Sass, Director of Product Management at Datadog, delves into the innovative updog.ai, a tool revolutionizing outage detection using real-time data. He explains the significance of distinguishing between local issues and global outages at crucial times, like 3 AM. Omri discusses the challenges of synthetic testing and the importance of aggregate telemetry in spotting provider problems. He also shares insights on industry reactions to outage trackers and the engineering hurdles faced while building updog.ai, illustrating the ongoing evolution of cloud service monitoring.

Hunter Leath, CEO of Archil and former Amazon EFS engineer, shares revolutionary insights into cloud storage. He reveals the 20-year struggle of making S3 act like traditional file systems and how Archil bridges this gap. Discussing fast SSDs as a cache layer and seamless integration with existing S3 buckets, Hunter also dives into pricing strategies that can beat Amazon’s services. He emphasizes the resurgence of file systems in the AI age and explains how they can enhance model performance. Prepare for a gamechanger in storage solutions!

When AWS has a major outage, what actually happens behind the scenes? Ben Hartshorne, a principal engineer at Honeycomb, joins Corey Quinn to discuss a recent AWS outage and how they kept customer data safe even when their systems couldn't fully work. Ben explains why building services that expect things to break is the only way to survive these outages. Ben also shares how Honeycomb used its own tools to cut their AWS Lambda costs in half by tracking five different things in a spreadsheet and making small changes to all of them.About Ben Hartshorne: Ben has spent much of his career setting up monitoring systems for startups and now is thrilled to help the industry see a better way. He is always eager to find the right graph to understand a service and will look for every excuse to include a whiteboard in the discussion.Show highlights: (02:41)Two Stories About Cost Optimization(04:20) Cutting Lambda Costs by 50%(08:01) Surviving the AWS Outage(09:20) Preserving Customer Data During the Outage(13:08) Should You Leave AWS After an Outage?(15:09) Multi-Region Costs 10x More(18:10) Vendor Dependencies(22:06) How LaunchDarkly's SDK Handles Outages(24:40) Rate Limiting Yourself(29:00) How Much Instrumentation Is Too Much?(34:28) Where to Find BenLinks: Linkedin: https://www.linkedin.com/in/benhartshorne/GitHub: https://github.com/maplebedSponsored by: duckbillhq.com