MLOps Starts with the Lifecycle, Not the Tool
Explain the six lifecycle stages that must be explicit before an ML workflow can be operationalized.
The deployment question is usually a lifecycle question in disguise. The Six-Stage Loop CRISP-DM gives MLOps teams a neutral way to talk about the work before choosing infrastructure. Business understanding asks what decision changes. Data understanding asks whether the available data can support that decision. Data preparation asks whether transformations are repeatable. Modeling asks which candidates deserve evaluation. Evaluation asks whether performance is good enough for the operating context. Deployment asks how the prediction becomes a maintained service, batch job, dashboard, or human workflow. Why It Works The framework forces evidence to move with the model. A production team cannot…
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