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Day: April 24, 2026

Training, Serving, and Deploying Scikit-Learn Models via FastAPI

Abid Ali Awan serves a model:

In this article, you will learn how to train a Scikit-learn classification model, serve it with FastAPI, and deploy it to FastAPI Cloud.

Topics we will cover include:

  • How to structure a simple project and train a Scikit-learn model for inference.
  • How to build and test a FastAPI inference API locally.
  • How to deploy the API to FastAPI Cloud and prepare it for more production-ready usage.

Click through for the process.

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Cross-Workspace MLflow Logging Available in Microsoft Fabric

Ruixin Xu announces a feature now generally available:

Cross-workspace logging works through the synapseml-mlflow package, which provides a Fabric-compatible MLflow tracking plugin. The core idea is simple: set the MLFLOW_TRACKING_URI* to point at your target workspace and use standard MLflow commands. Your experiments, metrics, parameters, and registered models land in the workspace you choose — not just the one you’re running in.

Read on for the full announcement.

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Filtered Indexes and Computed Columns

Greg Low has a public service announcement:

On a client site some years back, I came across a situation (unfortunately too common) where a column in a table was being used for two purposes. It could either hold an integer value or a string. Only about 100 rows out of many millions had the integer value. Some of the client code needed to calculate the maximum value when it was an integer. First step I tried was to add a persisted calculated column like so:

After that, Greg tried to create a filtered index. Read on to see how that worked.

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Testing Your SQL Server Backups

Vlad Drumea stresses the need to test:

Folks think that if they just take backups regularly, and their backup intervals match their recovery point objectives, then they can rest assured knowing (more like falsely thinking) they have backups from which to restore in case something bad happens to a database or to the entire instance.

Yeah, there are several things that can go wrong, even beyond the solid answers Vlad provides. Think about developers taking one-off backups that break the log chain, overly-aggressive purge processes that delete backups before they’re fully moved to long-term storage, etc.

Definitely check out Vlad’s post. If you’re interested, I also have a video series on YouTube that covers SQL Server backup and restore.

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Postgres Performance on Linux 7.0 and Benchmark Artifacts

Christophe Pettus digs into a finding:

A benchmark came out of AWS earlier this month showing PostgreSQL throughput on Linux 7.0 dropping to 0.51x what the same workload produced on Linux 6.x. The Phoronix headline wrote itself. Hacker News did what Hacker News does. By the end of the week, I had been asked by three separate clients whether they needed to hold their kernel upgrades.

They don’t. Almost nobody does.

Read on for the answer, including a dive into the nature of the problem and a quick-and-easy fix for most cases.

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