Question 2

Explanation

The benefits of using AWS SAM to create the serverless application include that it comes built-in with CodeDeploy to provide gradual Lambda deployments. With just a few lines of configuration, AWS SAM can perform the following actions:

• Deploys new versions of the Lambda function, and automatically creates aliases that point to the new version.

• Gradually shifts customer traffic to the new version until you’re satisfied that it's working as expected, or you roll back the update.

• Defines pre-traffic and post-traffic test functions to verify that the newly deployed code is configured correctly, and your application operates as expected.

• Rolls back the deployment if CloudWatch alarms are triggered.

The DevOps engineer can choose the Deployment Preference Type. The following options are available:

• Canary: Traffic is shifted in two increments. You can choose from predefined canary options. The options specify the percentage of traffic that's shifted to your updated Lambda function version in the first increment, and the interval, in minutes, before the remaining traffic is shifted in the second increment.

• Linear: Traffic is shifted in equal increments with an equal number of minutes between each increment. You can choose from predefined linear options that specify the percentage of traffic that's shifted in each increment and the number of minutes between each increment.

• All-at-once: All traffic is shifted from the original Lambda function to the updated Lambda function version at once.

The best option to minimize the impact of failed deployments is to use the canary deployment type. This will ensure that only a small amount of traffic reaches the new Lambda function in the first shift and if any issues occur the deployment can be stopped.

CORRECT: "Use an AWS SAM template to define the serverless application. Use AWS CodeDeploy to deploy the Lambda functions with the Canary10Percent30Minutes deployment type" is the correct answer (as explained above.)

INCORRECT: "Use AWS CloudFormation to deploy the serverless application. Use AWS CodeDeploy to deploy the Lambda functions with the AllAtOnce deployment type. Monitor error rates using Amazon CloudWatch" is incorrect.

The all-at-once deployment preference type would shift all traffic across to the new functions which would increase the impact of failed deployments. Also, CloudFormation is not a continuous deployment tool and is not a suitable substitute for CodePipeline and CodeDeploy.

INCORRECT: "Use AWS CloudFormation to publish a new version on every stack update and use the Routing Config property of the AWS::Lambda::Alias resource to shift traffic to the new version" is incorrect.

As above, CloudFormation is not designed for continuous delivery and should not be used in this scenario. Creating a CodePipeline that leverages CodeDeploy and a source control service such as CodeCommit would be a better solution.

INCORRECT: "Use AWS CloudFormation to publish a new version on each stack update and configure an AWS CodePipeline approval action for a DevOps engineer to test and approve the new version" is incorrect.

This option requires more operational overhead and testing on behalf of the DevOps team. The better solution is an automated pipeline that shifts some traffic across to the new functions so actual end users are attempting to use the application.

References:

https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/automating-updates-to-serverless-apps.html

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