A developer wants the ability to roll back to a previous version of an AWS Lambda function in the event of errors caused by a new deployment.
How can the developer achieve this with MINIMAL impact on users?
A.
Change the application to use an alias that points to the current version. Deploy the new version of the code. Update the alias to use the newly deployed version. If too many errors are encountered, point the alias back to the previous version.
B.
Change the application to use an alias that points to the current version. Deploy the new version of the code. Update the alias to direct 10% of users to the newly deployed version. If too many errors are encountered, send 100% of traffic to the previous version.
C.
Do not make any changes to the application. Deploy the new version of the code. If too many errors are encountered, point the application back to the previous version using the version number in the Amazon Resource Name (ARN).
D.
Create three aliases: new, existing, and router. Point the existing alias to the current version. Have the router alias direct 100% of users to the existing alias. Update the application to use the router alias. Deploy the new version of the code. Point the new alias to this version. Update the router alias to direct 10% of users to the new alias. If too many errors are encountered, send 100% of traffic to the existing alias.
Option B is the best choice for achieving the objective with minimal impact on users. It uses a canary deployment strategy, which allows for testing the new version on a smaller scale before a full rollout. This method provides a balance between risk management and operational simplicity, ensuring that any potential negative impacts of the new deployment are contained and easily reversible.
For people voting A: you have no idea what is the traffic load to the application. Using the method described on A will affect 100% of all users all at once until you are able to rollback. B divertes 10% of traffic only than can be easly switched back and would impact only 10% of users
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