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Why EXANTE rejected AI to migrate its critical tests

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Why EXANTE rejected AI to migrate its critical tests

Breaking a monolith into microservices is often treated as a simple engineering exercise. For broker EXANTE, a single migration became a full audit of its testing practices. It uncovered false positives, missing coverage and outdated documentation, and it cut regression time from an hour to two minutes.

Grigorii Sedelnikov, automation QA engineer at EXANTE, explained how his team moved the firm’s order risk assessment service, known as Pre-margin, out of its Core monolith and migrated about 200 automated tests along the way.

Core works as a vast calculation engine. It serves hundreds of thousands of clients across more than three million instruments, including shares, bonds, futures and options. Pre-margin checks whether a client has enough funds to open a position, and it runs whenever a trader hovers over the Buy or Sell button. Because these requests far outnumber actual orders, the service needed to scale on its own rather than alongside the entire monolith.

Testing inside Core had become a bottleneck. The framework holds more than 3,500 Python tests split across 16 nightly jobs, and even a small Pre-margin change set off an hour-long regression. Engineers then had to investigate failures in unrelated functionality before any release could proceed. Duty engineers spent four hours a day analysing those failures.

The team first used Claude to catalogue every test that touched the pre-order evaluation endpoints, along with each test’s preconditions and assertions. The job took a couple of hours. Architecture planning stayed largely in human hands, with AI used only to stress-test ideas.


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