How to Add LLM Drift Monitoring to Your CI/CD Pipeline in 10 Minutes

LLM drift breaks production. Most teams don't notice until users report bugs. Here's how to catch it automatically. Why CI/CD for LLMs? If you have unit tests for code, you should have drift tests for LLMs. The principle is the same: catch regressions before they reach production. The Setup (10 Minutes) Step 1: Create a drift test file # tests/test_llm_drift.py import pytest from driftwatch import Monitor @pytest.fixture def monitor (): return Monitor ( model = " gpt-4o " , baseline = " tests/baseline_outputs.json " ) def test_json_format_drift ( monitor ): score = monitor . check_prompt ( " Give me a JSON object with user data " ) assert score < 0.1 , f " Drift detected: { score } " def test_classification_drift ( monitor ): score = monitor . check_prompt ( " Classify this email as spam or not spam " ) assert score < 0.1 Step 2: Add to GitHub Actions # .github/workflows/llm-drift.yml name : LLM Drift Check on : [ push , pull_request ] jobs : drift-test : runs-on : ubuntu-latest steps