Tag: model serving

3 entries tagged "model serving" — 1 post, 2 links.

Posts

Jan 31, 2026 — 10 min — Platform & AI

The Preprocessing Boundary Between scikit-learn and PyTorch

A production-friendly pattern for pairing scikit-learn preprocessing graphs with PyTorch models so training and inference use the same feature contract.

Outcome: Defined an artifact contract that keeps column preprocessing, feature order, model weights, metadata, and inference behavior synchronized across batch and serving environments.

machine learning pytorch scikit-learn mlops model serving

Links

Articleblog.christianposta.comMar 20, 2026Permalink

Running NVIDIA NIM on GKE With the Kubernetes NIM Operator

Christian Posta

This is the kind of platform link that turns model serving into an operations conversation. NIM, GKE, and operators are not glamorous pieces, but they are the difference between "we can run a model" and "we can run the model with repeatable infrastructure."

The caution is that Kubernetes can make a simple model deployment expensive in both money and attention. It earns its place when repeatability, policy, and scale matter.

Articlemedium.comMar 19, 2026Permalink

Scaling Inference To Billions of Users And Agents

Federico Iezzi, Google Cloud

This is useful because it connects agent adoption to inference architecture. Agents do not make one call; they fan out across planning, retrieval, tool use, retries, and evaluation, which changes the serving math quickly.

Worth keeping as a scale reference for Google Cloud AI work. The product question is where inference cost becomes a feature constraint rather than a backend detail.

model serving gcp agents inference

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