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The latest News and Information on API Development, Management, Monitoring, and related technologies.

The Infrastructure Puzzle: How AI-Enabled Event Management Software Powers Complex Event Programs

When registration, attendee data, check-in, communications, and reporting stop working in concert, complex programs break. A connected online event management software setup gives teams one operating layer, not yet another stack of tools that complicates work.

Holiday readiness: run your first load test with skills

Before you can answer whether checkout will survive Black Friday, you need a test you can rerun. In this demo, we used a coding agent and the Speedscale skills to record a Node app, mock its downstream API, and run a 30-second load test with 10 virtual users. That’s a small first step in holiday readiness. It gives you a working test and a result to inspect, with time left to fix what you find before a code freeze.

Load Test PostgreSQL Instantly using Production Recordings

The first PostgreSQL post ran on a laptop: a demo app, a Docker container, and the proxymock CLI. That is the fastest way to see the idea. It is also not where your database problems live. Your real query mix lives in the cluster, where a Java service with a connection pool, an ORM and a schema migration tool sends the statements nobody wrote by hand. This post deploys an open source banking app to Kubernetes and records the queries one of its services sends to PostgreSQL.

Judgment, not generation: rebuilding our AI API Classifier on Jev

Rebuild AI API classification with Jev to cut costs, reduce latency, improve calibration, and make production decisions more efficient without sacrificing accuracy. Replacing the judgment step in a production classification pipeline with a purpose-built decision model changes the economics of the problem entirely.

FastAPI 0.142 Turns On OpenTelemetry by Default. Here's What It Records.

FastAPI 0.142.0 ships with OpenTelemetry built in. Install fastapi, set one environment variable, and every request produces a trace, metrics, and error logs. No middleware, no instrumentation package, no code. That’s a big change for a framework most Python teams instrument by hand. It’s also easy to misread. The defaults record more than some teams expect in one place, and less than others assume in another. Here’s what you actually get.