If your cloud bill feels more like a mortgage payment than an operating expense, you’re not alone. Over the last decade, enterprises rushed into the public cloud for speed and flexibility—only to wake up with a serious cloud hangover: spiraling storage costs, egress fees on every experiment, and compliance teams asking hard questions about where data actually lives.

In today’s episode, we’re unpacking the rise of data repatriation—the move to bring data, applications, and AI workloads back from public cloud into on‑prem and private environments. We’ll look at why AI data gravity makes location a first‑class design decision, why metered, remote object storage is such a bad fit for high‑reuse training datasets, and how on‑prem S3 platforms like Cloudian HyperStore turn “backing out of the cloud” from a painful rollback into a long‑term AI strategy.

So if you’re trying to feed GPUs without paying a gravity tax on every byte, or you’re wondering which workloads truly belong in the cloud versus at home, stay tuned—we’re going to break down the economics, the architecture, and the playbook for bringing your data back where it works best.

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In this episode, we’re talking about data repatriation—why media, healthcare, and financial services organizations are pulling petabytes out of the cloud and landing them on on‑prem S3 object storage to power their next wave of AI.

You’ll meet a global media company that got blindsided by egress fees and latency, a healthcare provider squeezed by compliance and data sovereignty, and a financial services firm that hit an AI cost wall the moment “cheap” cloud storage became “read constantly” AI training fuel

Across all three, the pattern is the same: early cloud enthusiasm, then scale‑driven pain around cost, performance, and governance, and finally a deliberate shift to an on‑prem, cloud‑scale S3 platform sitting right next to their GPUs.

So if you’re planning your AI roadmap and wondering where your “high‑gravity” data should really live, stick around—because these stories might sound a lot like your own.

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Welcome back to the show, everyone! Today, I’m joined by someone whose story truly bridges the worlds of sports, precision, and artistry. Dr. Bobby Lenoir is a partner at Brown, Reynolds, Snow, and Lenoir—a leading dental practice here in Richmond, Virginia—where he’s known for transforming smiles through advanced cosmetic dentistry.

But before he became one of Richmond’s premier cosmetic dentists, Dr. Lenoir was known for something entirely different: playing ball with the Texas Rangers organization. From the baseball diamond to the dental chair, his journey is a fascinating example of how discipline, performance, and passion can shape an exceptional career.

We’ll dive into that transformation—what it takes to go from pro athlete to medical professional, how the mindset of competition translates to cosmetic excellence, and why patient experience is the real game-changer in modern dentistry

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Today’s guest is Kim Guenther, a stage 4 leukemia survivor whose life was forever changed by a groundbreaking medical treatment trial. After facing odds that would stop most of us in our tracks, Kim said yes to an experimental path that not only helped save her life, but completely reshaped her purpose, her faith, and her perspective on what really matters. In this conversation, we’re going to talk about diagnosis, the brutal reality of treatment, the hope and uncertainty of clinical trials, and how Kim has turned her story into a source of strength for others walking through their own battles with cancer. So let’s dive in—this is Kim’s journey from stage 4 leukemia to survivor and advocate.

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Welcome to “Is that how it happened” — in this episode we rip the lid off the bottlenecks holding your AI infrastructure back and get serious about what's actually moving data at the speed your workloads demand.

I'm your host, The Vanimal, and today we're going deep — and I mean deep — on one of the most exciting developments in modern AI data pipelines: S3 RDMA Direct from Cloudian.

If you've ever watched your GPU cluster sit idle while it waits for data to feed through an overloaded CPU, this episode is your prescription. We're talking about Remote Direct Memory Access — RDMA — combined with native S3 object storage, eliminating the CPU as the middleman and putting data exactly where your compute needs it, fast.

And we're not doing this alone. Joining us today is the team from ePlus and their AI Ignite practice — a services framework purpose-built to help organizations design, deploy, and scale AI infrastructure the right way. These are the engineers and architects living on the front lines of AI deployment, and they've got real-world perspective on how S3 RDMA is changing the game for their clients.

Whether you're an infrastructure architect, a data engineer, or just someone trying to figure out how to stop leaving GPU performance on the table — buckle up.

Let's bypass the CPU.

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What if the storage layer your organization already owns could become the most powerful asset in your AI strategy? Not someday — right now.

Welcome to this episode of “Is that how it happened” - Turning S3 Storage into the AI Brain – in the podcast episode we bridge the gap between the data you're already storing and the intelligence you need to unlock.

I'm The Vanimal, a Sr. Solutions Architect who lives at the intersection of object storage and AI. Today, we'll dig into how S3-compatible storage isn't just a place to park your data — it's the foundation, the memory, and the muscle behind modern AI workloads.

From data lakes to vector stores, from on-prem infrastructure to hybrid cloud pipelines — we're going to show you how to stop thinking of storage as a cost center and start treating it as the brain of your AI operation.
Let's get into it.

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Welcome back to the show! I'm the Vanimal, and today we've got a guest who has literally written the playbook on channel sales done right.

Our guest is Gil Lowe — Director of Channel Sales at Veeam Software, where he's been the architect of one of the most powerful partner relationships in North America for over a decade. Gil joined Veeam back in 2014 and has spent more than ten years scaling the Veeam-CDW partnership — Veeam's largest Platinum partner account on the continent — into a true powerhouse go-to-market motion.

And he's not just showing up — he's dominating. Gil has racked up multiple MVP Channel Awards, the CDW Channel Account Manager of the Year Award, and the Veeam Channel Manager of the Year — all in 2022 alone. He's the kind of guy who doesn't just hit quota — he redefines what's possible in a channel relationship.

Before Veeam, Gil honed his craft at ExaGrid, Hewlett Packard Enterprise, and CA Technologies — building a career that spans backup, recovery, data resilience, and the art of making partners wildly successful.

In today's conversation, we're getting into how elite channel relationships actually get built, what separates good partners from great ones, and where the data protection space is headed. Trust me — if you're in sales, storage, or the channel ecosystem, you do NOT want to skip this one.

Gil, welcome to the show — let's get into it!"

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Welcome back to Is That How It Happened?—today’s guest is my friend Dr. Colt W. Knight from the University of Maine Cooperative Extension, an Associate Extension Professor and Maine’s state livestock specialist. He runs the Maine Grazing Behavior Lab, where his team designs and manufactures livestock tracking collars and does applied grazing behavior research to help interpret what animals are telling us through their movement and behavior.
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But Colt’s also an accomplished luthier—building custom guitars that have found their way into the hands of world-class players, including The Kentucky Headhunters. Today we’re talking about craft, science, and the kind of curiosity that connects a lab bench to a workbench—so let’s get into it.

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