Blue-Green Deployment
A release strategy that runs two identical production environments, switching traffic from the current version (blue) to the new version (green) once it passes validation, enabling instant rollback.
Blue-green deployment eliminates downtime during releases by maintaining two parallel production environments. The blue environment serves live traffic while the green environment is updated with the new release. Once the green environment passes smoke tests and health checks, a load balancer or DNS switch routes all traffic from blue to green instantly.
The primary advantage is risk reduction. If the new release has issues, you can route traffic back to the blue environment in seconds rather than performing a full rollback. This is particularly valuable for AI features where model behavior can be unpredictable under real production load patterns.
The trade-off is cost: you need double the infrastructure capacity during deployments. Many teams mitigate this by using cloud auto-scaling and only spinning up the green environment during releases. Database migrations require careful coordination since both environments share the same data layer, making backward-compatible schema changes essential.
Related Terms
A/B Testing
A controlled experiment comparing two or more variants to determine which performs better on a defined metric, using statistical methods to ensure reliable results.
Feature Flag
A software mechanism that enables or disables features at runtime without deploying new code, used for gradual rollouts, A/B testing, and targeting specific user segments.
MLOps
The set of practices combining machine learning, DevOps, and data engineering to reliably deploy, monitor, and maintain ML models in production.
Model Serving
The infrastructure and systems that host trained ML models and handle inference requests in production, optimizing for latency, throughput, and cost.
Semantic Search
Search that understands the meaning and intent behind a query rather than just matching keywords, typically powered by embedding-based similarity comparison.
CI/CD (Continuous Integration / Continuous Deployment)
An automated software practice where code changes are continuously integrated into a shared repository, tested, and deployed to production, reducing manual intervention and accelerating delivery cycles.