Updating a server after creation.

Not updating a server after creation.

The inability to change server counts.

The ability to change server counts.

Use the Blue-Green deployment method to enable the fastest possible rollback if needed. Create a full second stack of instances and cut the DNS over to the new stack of instances, and change the DNS back if a rollback is needed.

Create a second ELB, Auto Scaling Launch Configuration, and Auto Scaling Group using the Launch Configuration. Create AMIs with all code pre-installed. Assign the new AMI to the second Auto Scaling Launch Configuration. Use Route53 Weighted Round Robin Records to adjust the proportion of traffic hitting the two ELBs.

Create AMIs with all code pre-installed. Assign the new AMI to the Auto Scaling Launch Configuration, to replace the old one. Gradually terminate instances running the old code (launched with the old Launch Configuration) and allow the new AMIs to boot to adjust the traffic balance to the new code. On rollback, reverse the process by doing the same thing, but changing the AMI on the Launch Config back to the original code.

Migrate to use AWS Elastic Beanstalk. Use the established and well-tested Rolling Deployment setting AWS provides on the new Application Environment, publishing a zip bundle of the new code and adjusting the wait period to spread the deployment over time. Re-deploy the old code bundle to rollback if needed.

Canary Deployments

Immutable Rolling Deployments

Mutable Rolling Deployments

Blue-Green Deployments

Model the stack in AWS Elastic Beanstalk as a single Application with multiple Environments. Use Elastic Beanstalk’s Rolling Deploy option to progressively roll out application code changes when promoting across environments.

Model the stack in 1 CloudFormation template, to ensure consistency and dependency graph resolution. Write deployment and integration testing automation following Rolling Deployment methodologies.

Model the stack in 3 CloudFormation templates: Data layer, compute layer, and networking layer. Write stack deployment and integration testing automation following Blue-Green methodologies.

Model the stack in AWS OpsWorks as a single Stack, with 1 compute layer and its associated ELB. Use Chef and App Deployments to automate Rolling Deployment.

Create a Dockerfile when preparing to deploy a new version to production and publish it to S3. Use UserData in the Auto Scaling Launch configuration to pull down the Dockerfile from S3 and run it when new instances launch.

SSH into new instances those come online, and deploy new code onto the system by pulling it from an S3 bucket, which is populated by code that you refresh from source control on new pushes.

Bake an AMI when deploying new versions of code, and use that AMI for the Auto Scaling Launch Configuration.

Create a new Auto Scaling Launch Configuration with UserData scripts configured to pull the latest code at all times.

Add new instances with the latest Amazon Linux AMI specified as a custom AMI to all AWS OpsWorks layers of your stack, and terminate the old ones.

Create a new stack and layers with identical configuration, add instances with the latest Amazon Linux AMI specified as a custom AMI to the new layer, switch DNS to the new stack, and tear down the old stack.

Assign a custom recipe to each layer, which replaces the underlying AMI. Use AWS OpsWorks life-cycle events to incrementally execute this custom recipe and update the instances with the new AMI.

Specify the latest Amazon Linux AMI as a custom AMI at the stack level, terminate instances of the stack and let AWS OpsWorks launch new instances with the new AMI.

Identify all Amazon Elastic Compute Cloud (EC2) instances of your AWS OpsWorks stack, stop each instance, replace the AMI ID property with the ID of the latest Amazon Linux AMI ID, and restart the instance. To avoid downtime, make sure not more than one instance is stopped at the same time.

Run “aws autoscaling detach-load-balancers” before updating your application.

Use AWS CodeDeploy. Create an application and a deployment targeting the Auto Scaling group. Use CodeDeploy to deploy and update the application in the future.

Use the AWS Console to enable termination protection for the current instances.

Run “aws autoscaling suspend-processes” before updating your application.

Use the zero downtime feature of Elastic Beanstalk to deploy new software releases to your existing instances.