ModelRefs / Blue-Green Deployment — AI Glossary
Blue-Green Deployment — AI Glossary
A deployment strategy maintaining two identical production environments, switching traffic from blue (current) to green (new) atomically.
Overview
Blue-green deployments eliminate deployment downtime: green is fully provisioned and tested, then a DNS/load-balancer switch flips all traffic instantly. Rollback is instant (flip back to blue). For LLM serving: both environments serve the same model initially; deploy new model to green, validate, then switch. Guarantees zero-downtime model updates.
Reference details
| Topic | ecosystem |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
How it works
- Two complete environments exist; one serves all traffic while the other is idle at full capacity.
- The new version is deployed to the idle environment and validated there, with no production traffic at risk.
- Traffic is switched atomically at the router or DNS, so every request moves at once rather than progressively.
- The previous environment is kept warm, which is what makes rollback a switch back rather than a redeploy.
- Because the cutover is total, validation has to happen before it — there is no fraction of traffic to learn from.
Example: What double capacity buys
Running two full environments costs 2x capacity during the change window. In exchange, rollback is a routing change — seconds — rather than a redeploy measured in minutes. A canary needs only about 1.05x capacity but exposes 5% of users to the new version and needs enough traffic for that 5% to be statistically readable. The choice is paying in capacity or paying in exposure, and for a change that cannot be partially applied, only one of the two is available.
Commonly confused with
The counterpart to a canary: two complete environments, traffic switched atomically, and rollback is switching back. It costs double capacity during the change and gives the fastest possible reversal. A canary is cheaper and slower to fully release. Neither is a substitute for evaluating the new model before either — both control exposure, not correctness.
When to use it
Reach for it when:
- The change cannot be partially applied — a schema or contract change where mixed versions would break.
- Rollback must be as close to instantaneous as possible.
- Pre-cutover validation in a production-identical environment is feasible.
Reach for something else when:
- Double capacity is unaffordable for the change window.
- The regression you fear only appears under real traffic, which a canary surfaces and this does not.
- Validating in the idle environment is impossible, leaving the cutover unprotected.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Blue-Green Deployment — AI Glossary.
Frequently asked questions
What is Blue-Green Deployment?
A deployment strategy maintaining two identical production environments, switching traffic from blue (current) to green (new) atomically.
What concepts are related to Blue-Green Deployment?
Closely related concepts include canary deployment, a b testing llm, model routing.