1. Canary Deployment

  • Definition: A small subset of users receives the new version of the application while the majority continue using the old version.
  • Purpose: To test the new version in a real-world environment with minimal risk.
  • Process:
    • Deploy the new version to a small percentage of users.
    • Monitor performance and issues.
    • Gradually increase the user base if no significant problems arise.
  • Advantages:
    • Reduces risk by limiting exposure.
    • Allows for quick rollback if issues are detected.

2. Blue-Green Deployment

  • Definition: Two identical environments (Blue and Green) are maintained. One runs the current version, while the other runs the new version.
  • Purpose: To ensure zero downtime during deployment.
  • Process:
    • Deploy the new version to the inactive environment (e.g., Green).
    • Switch traffic from the active environment (e.g., Blue) to the Green environment.
    • If issues arise, switch back to Blue.
  • Advantages:
    • Quick rollback capabilities.
    • Complete isolation of the new version until it is fully tested.

3. Rolling Update

  • Definition: Gradually replaces instances of the previous version with the new version, one or a few at a time.
  • Purpose: To update the application without downtime.
  • Process:
    • Update a small number of instances at a time (e.g., 10%).
    • Monitor the updated instances before proceeding with more updates.
  • Advantages:
    • Reduces the risk of complete failure.
    • Continuous availability of the application.

Understand with examples:

🔄 Rolling Update

In a rolling update, Kubernetes gradually replaces old versions of pods with new ones. For example, if you have 4 replicas of a pod and you update the container image:

  1. Kubernetes will update one pod at a time to the new version (e.g., v2).
  2. The remaining 3 pods continue running the old version (v1) to ensure service availability.
  3. If the new pod (v2) starts successfully, Kubernetes proceeds to update the next pod.
  4. If the new version fails, the update stops, and the remaining old pods (v1) continue running.
  5. Once all pods are successfully updated, the rollout is complete—typically within 2–3 minutes.

⚠️ Note: This process is automatic and DevOps engineers have limited control over how traffic is split or tested during the rollout.

🧪 Canary Deployment

Canary deployment offers more control and safety by releasing the new version to a small subset of users first.

  • Suppose you have 100 users. You deploy v2 alongside v1 in production.
  • You configure traffic routing so that 10% of users are sent to v2, and 90% remain on v1.
  • This allows you to test v2 in real-world conditions for a few days or a week.
  • Based on feedback and performance, you can gradually increase the percentage of traffic to v2 (e.g., 25%, 50%, 100%).

✅ DevOps engineers have full control over traffic distribution and rollout speed, making it ideal for minimizing risk and gathering early feedback.

🔵🟢 Blue-Green Deployment

Blue-green deployment is the safest but most resource-intensive strategy.

  • You maintain two identical environments:
    • Blue (current version, e.g., v1)
    • Green (new version, e.g., v2)
  • Both versions run with the same number of replicas (e.g., 4 each), but only one is live.
  • Initially, traffic is routed to Blue (v1) via a load balancer or ingress.
  • Once Green (v2) is ready and tested, you switch the traffic to it instantly by updating the ingress or load balancer.
  • If something goes wrong, you can quickly roll back by pointing traffic back to Blue.

💰 This method requires double the resources, making it more expensive, but it offers zero-downtime and instant rollback.