Canary, Blue/Green, Rolling, Rolling with Additional Batch, Immutable, and All-at-Once are deployment strategies in AWS, particularly used with services like CodeDeploy, Elastic Beanstalk, ECS, and Lambda. These strategies provide different approaches to releasing new application versions, balancing factors such as speed, risk, availability, and rollback options. Understanding the strengths and use cases of each strategy is critical for choosing the right deployment method based on application requirements.
1. Blue/Green Deployment:
Definition: Creates a completely separate environment (Green) alongside the existing one (Blue).
Switch: Traffic is rerouted from Blue to Green upon successful testing.
Rollback: If there are issues, switch back to Blue instantly.
Use Case: Deploying a new version of an e-commerce platform where any error could cause a major loss. Immediate rollback is essential.
2. Canary Deployment:
Definition: Gradually deploys a new version to a small subset of users first (canary), then progressively increases the audience if no issues are detected.
Use Case: Deploying a new feature for a web application to 10% of users initially, monitoring for errors, and then expanding to 100% if successful.
3. All at Once:
All instances are updated simultaneously.
Fastest, but highest risk of failure or downtime.
Use Case: Deploying a static website where a brief downtime is acceptable. Suitable for non-critical applications.
4. Immutable:
A completely new environment is created for the new version.
After successful deployment, traffic switches to the new environment.
Use Case: Deploying a critical banking application with high security and zero-risk tolerance. The old environment is untouched until the new one is confirmed.
5. Rolling:
Updates occur in batches, one group of instances at a time.
No downtime, but slower.
Use Case: Deploying a web application with multiple EC2 instances where continuous availability is crucial. Slight performance impact may occur during updates, but capacity is maintained.
6. Rolling with Additional Batch:
Similar to Rolling, but an extra batch of instances is added temporarily.
Minimizes downtime without affecting capacity.
Use Case: Deploying a new version of an API without impacting current traffic. Full capacity is maintained at all times due to the additional batch.