Deployment

Canary Deployment

Definition

A progressive rollout strategy that routes a small percentage of production traffic to a new model version while the remainder continues to receive the old version. Canary deployments limit blast radius if the new model underperforms or causes regressions.

Related Terms

A/B Testing (ML)

A controlled experiment that compares the performance of two or more model versions by routing live traffic between them and measuring business and technical metrics. A/B testing is essential for validating that a new model version improves outcomes before full rollout.

Shadow Mode

A deployment technique where a new model processes production traffic in parallel with the existing system but its predictions are logged rather than served to users. Shadow mode enables risk-free validation of model behaviour on real-world data before cutover.

Model Serving

The process of deploying trained ML models to production environments where they can receive inputs and return predictions at scale. Model serving infrastructure must address throughput, latency, versioning, and cost while meeting SLAs.

Knowing the Terms Is Step One. Applying Them Is Step Two.

Book a 30-minute call to discuss how these AI concepts translate to your specific industry and business challenges.