Why enterprises are exiting the public cloud
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Why enterprises are exiting the public cloud
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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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