hardNewDatabricksSalesforceSnowflake

A team wants to fine-tune a model every time their labelled data grows. Build them the pipeline.

The training part is a job. Everything around it is the pipeline: data snapshots that are immutable, an evaluation gate with a threshold set in advance, and adapters versioned so a bad one is a routing change away from gone.

Updated Sep 2026 · Grounded in researched DevOps, SRE and platform engineering interview loops, written to a senior-engineer editorial bar, and never padded to hit a word count.

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Next in this trackHow often should a large training run checkpoint, and what does the answer depend on?Next in this trackA training run from three months ago cannot be reproduced. Same code, same data, different result. Where does the difference come from?Next in this trackAt 512 GPUs something fails every few hours. How does a training run survive that?

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