Building a Mission-Critical Integration Blind, Part II: 100,000 Requests Later

Part 2 of 2. Part 1 covers building the service from scratch — including when you have no access to the systems you're integrating with.

The service had been in production for a couple of months. Time to find out what it actually looked like under load.

Not a synthetic benchmark — a realistic test using actual API calls, real request parameters sourced from public business registries, and the full processing pipeline end to end. The goal: understand the behavior at scale, find the bottlenecks, and fix what needs fixing.

The results were not what I expected. Our system wasn't the problem.

Building the Test

💡 LLM Tip: Generate the tooling, not just the tests

I needed a Python script with configurable batch submission, parallel async polling, timing collection (submission latency, end-to-end processing time), parameter verification, and a structured report with status breakdowns and p95 latencies.

I also needed realistic...

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