Deployment Strategies Simulator - Learn Blue-Green, Canary, Rolling Updates
Deployment Strategies
Stop all old pods, then start new ones. Simple but causes downtime.
Step 1: Initial State
Users
LB
v1 100%
v2
All traffic goes to v1
Pros
- + Simple
- + Clean state
- + Low cost
Cons
- - Downtime
- - No rollback
- - Risky
Understanding Deployment Strategies
What You'll Learn
- How different deployment strategies minimize risk and downtime
- Trade-offs between deployment speed, safety, and resource cost
- When to use each strategy based on your application needs
- How traffic routing changes during deployments
- The role of feature toggles in modern deployment practices
Deployment Strategies Compared
Recreate: Simple but causes downtime - terminate all, then deploy all
Rolling Update: Kubernetes default - gradual replacement, zero downtime
Blue-Green: Two environments, instant switch, instant rollback
Canary: Gradual traffic shift, real-user testing, data-driven rollout
Feature Toggles: Decouple deployment from release, per-user targeting
💡 Real-World Implementations
- • Kubernetes: Native support for Rolling Updates and Recreate via Deployment spec
- • Argo Rollouts: Advanced Blue-Green and Canary with automated analysis
- • Istio/Linkerd: Service mesh traffic splitting for Canary deployments
- • LaunchDarkly/Unleash: Feature flag platforms for toggle-based releases
- • AWS CodeDeploy: Managed deployment service supporting multiple strategies
🎯 Best Practices
- • Always have a rollback plan before deploying to production
- • Use health checks and readiness probes to verify new versions
- • Implement proper monitoring and alerting during deployments
- • Consider database migrations carefully - they often need special handling
- • Start with smaller blast radius (Canary) for critical services
- • Clean up feature flags after features are fully rolled out