Deployment Strategy Comparison
Side-by-side comparison of all major deployment strategies. Use this reference to choose the right approach based on your requirements for downtime tolerance, resource budget, rollback needs, and team expertise.
Strategy Overview
| Strategy | Downtime Risk | Resource Overhead | Rollback Speed | Complexity | Best Use Case |
|---|---|---|---|---|---|
| Blue-Green | None (instant switch) | High (2x infrastructure) | Instant (<5s) | Medium | Critical services requiring instant rollback and zero downtime |
| Canary | Very low (limited blast radius) | Low-Medium (few extra pods) | Fast (seconds to scale down canary) | High | High-traffic services needing metric-driven validation before full rollout |
| Rolling Update | None (with proper health checks) | Low (25% surge default) | Minutes (rolling back is another rolling update) | Low | Standard workloads on Kubernetes. Good default for most services. |
| Feature Flags | None (code already deployed) | None (no extra infrastructure) | Instant (toggle flag) | Medium (flag management overhead) | Decoupling deploy from release. Gradual feature rollout. A/B testing. |
| Recreate | Yes (full downtime during swap) | None | Minutes (redeploy previous version) | Very low | Dev/staging environments, batch jobs, or services that cannot run two versions simultaneously |
Detailed Comparison by Dimension
Infrastructure Cost
| Strategy | Steady-State Cost | During-Deployment Cost | Notes |
|---|---|---|---|
| Blue-Green | 2x (both environments always running) | 2x | Can scale down idle environment to save cost (but lose instant rollback) |
| Canary | 1x | 1.01x-1.5x (canary pods) | Minimal overhead; canary is a small slice |
| Rolling | 1x | 1.25x (default maxSurge 25%) | Brief surge only during active rollout |
| Feature Flags | 1x | 1x | Cost is in flag service subscription, not infrastructure |
| Recreate | 1x | 0-1x (gap during swap) | Cheapest option but has downtime |
Version Coexistence
| Strategy | Two Versions Run Simultaneously? | Duration of Coexistence | Implication |
|---|---|---|---|
| Blue-Green | Yes (in parallel, but only one serves traffic) | Stabilization window (hours) | DB must be compatible with both versions |
| Canary | Yes (both serve traffic) | Minutes to hours (progressive) | Must handle mixed-version traffic (session affinity or stateless) |
| Rolling | Yes (both serve traffic) | Minutes (during rollout) | Must handle mixed-version traffic briefly |
| Feature Flags | Same version, different code paths | Until flag is removed (days to permanent) | Technical debt if flags are not cleaned up |
| Recreate | No | None | Simplest model but causes downtime |
Decision Guide: When to Use Each Strategy
Use Rolling Updates when...
You need a simple, low-overhead strategy for stateless services on Kubernetes. This is the right default for most workloads. No additional tooling required.
Use Blue-Green when...
Instant rollback is a hard requirement and you can afford double the infrastructure. Ideal for services with strict SLAs or regulatory requirements that mandate near-zero recovery time.
Use Canary when...
You have high traffic volume (enough to get statistically significant metrics from a small sample), good observability, and the engineering maturity to set up automated analysis. Best for large-scale services where a bad deploy could affect millions of users.
Use Feature Flags when...
You want to decouple deployment from release. Ideal for long-running feature development, A/B testing, and teams that practice trunk-based development. Combine with any other strategy for defense in depth.
Use Recreate when...
The application cannot run two versions simultaneously (e.g., holds exclusive locks, single-instance batch processors), or for development/staging environments where downtime is acceptable.