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Shadow Traffic for Safe Model Rollouts

Learn how to implement shadow traffic techniques for safely rolling out new models without impacting user experience.

11 min read

model rolloutshadow trafficsafety
Updated todayInformation score 5

Key insights

Concrete technical or product signals.

  • Shadow traffic allows for real-world testing without user impact.
  • Careful monitoring can prevent potential failures during full rollouts.

Use cases

Where this shines in production.

  • Deploying new machine learning models in production.
  • Testing algorithm updates in live environments.

Limitations & trade-offs

What to watch for.

  • Requires robust infrastructure to handle dual traffic streams.
  • Monitoring and analysis can be resource-intensive.

What is Shadow Traffic?

Shadow traffic involves routing a portion of live traffic to a new model while keeping it invisible to users.

Implementation Steps

  • Set up monitoring to compare performance metrics between old and new models.
  • Gradually increase the traffic percentage to the new model.

Key Metrics to Monitor

  1. Latency should not exceed 100ms.
  2. Error rates must remain below 1%.