How to structure scoring live traffic

📰 Reddit r/devops

Learn to structure scoring for live traffic to improve model evaluation and catch production input drifts

intermediate Published 6 Jul 2026

Action Steps

Implement live traffic scoring to catch production input drifts
Configure metrics to track output quality and detect degradation
Run A/B tests to compare model performance on live traffic vs offline evals
Apply machine learning techniques to identify and adapt to changing user behavior
Test and refine the live traffic scoring system to improve model reliability

Who Needs to Know This

DevOps and data science teams can benefit from this approach to ensure model performance and reliability in production environments

Key Insight

💡 Offline evals are not enough, live traffic scoring can help catch production input drifts and improve model performance

Key Takeaways

Learn to structure scoring for live traffic to improve model evaluation and catch production input drifts

Full Article

We've had offline evals as part of our CI for a while now, but last month we got hit with something that none of our CI runs flagged. Our production inputs had drifted and users were asking things our test set just didn't cover, and output quality on that section of things had degraded for weeks. So unfortunately, our existing evals gave me a false sense of safety because they can only ever test what I thought to put in them. So now I'm trying to figure o

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