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Question 14 of 256
SDLC AutomationhardMultiple ChoiceObjective-mapped

Blue/Green Deployment Strategy for High Availability

A company runs a critical e-commerce application on AWS. They use AWS CodePipeline to manage deployments. The pipeline has a source stage (CodeCommit), a build stage (CodeBuild), and a deploy stage (CodeDeploy to an Auto Scaling group). Recently, a deployment caused a 5-minute outage because the new application version had a bug that caused the health checks to fail. The Auto Scaling group marked instances as unhealthy and replaced them, but during the replacement, traffic was routed to the remaining instances, which also failed health checks, causing a full outage. The company wants to implement a deployment strategy that prevents any traffic from being routed to unhealthy instances and automatically rolls back if the deployment fails. They also want to minimize deployment time and cost. Which solution should the DevOps team implement?

Quick Answer

The answer is to use CodeDeploy blue/green deployment with automatic rollback enabled. This strategy creates a separate green Auto Scaling group alongside the existing blue group, routing traffic only after health checks pass on the new instances, which prevents any traffic from being sent to unhealthy instances and eliminates the outage risk seen with in-place updates. On the AWS Certified DevOps Engineer Professional DOP-C02 exam, this scenario tests your understanding of how blue/green deployment achieves high availability by isolating new code from production traffic until verified, and it’s a common trap to confuse it with in-place deployments or manual approvals that don’t automate rollback. Remember the memory tip: “Blue stays safe while green gets the test; if green fails, blue stays best.”

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Use CodeDeploy blue/green deployment with automatic rollback enabled

The correct solution is to use a blue/green deployment with CodeDeploy and automatic rollback enabled. In a blue/green deployment, a new Auto Scaling group (green) is created alongside the existing one (blue). Traffic is shifted to the green group only after all health checks pass. If health checks fail, the deployment is automatically rolled back by terminating the green group, ensuring no traffic is routed to unhealthy instances. This prevents any outage. Option B (in-place deployment with rollback) updates instances in place, which can cause downtime if instances fail health checks, as the Auto Scaling group replaces them sequentially, potentially routing traffic to unhealthy instances. Option A (manual approval) slows down deployment and does not automate rollback based on health checks. Option D (increasing health check grace period) only delays detection of failures and does not prevent traffic from being routed to unhealthy instances.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Add a manual approval step in CodePipeline before deploy

    Why it's wrong here

    Manual approval adds delay but doesn't automate rollback or prevent outage

  • Use CodeDeploy in-place deployment with automatic rollback enabled

    Why it's wrong here

    In-place deployment still replaces instances one by one, causing potential downtime

  • Use CodeDeploy blue/green deployment with automatic rollback enabled

    Why this is correct

    Blue/green creates a new environment, tests it, and shifts traffic only if healthy; rollback is automatic

  • Increase the health check grace period in the Auto Scaling group

    Why it's wrong here

    Longer grace period delays detection but doesn't prevent failure propagation

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Same concept, more angles

1 more way this is tested on DOP-C02

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. A DevOps engineer is designing a CI/CD pipeline for a Python application using AWS CodeBuild and AWS CodeDeploy. The application is deployed to an Auto Scaling group of EC2 instances. The engineer wants to ensure that the deployment does not impact availability. Which TWO strategies can be used? (Choose 2.)

medium
  • A.In-place deployment with a large batch size.
  • B.Rolling deployment with a small batch size.
  • C.Immutable deployment.
  • D.Blue/green deployment.
  • E.Canary deployment.

Why B: Rolling deployment with a small batch size (Option B) updates a limited number of instances at a time, ensuring that the majority of the Auto Scaling group remains available throughout the deployment. Blue/green deployment (Option D) creates a separate, fully-provisioned environment (green) and switches traffic to it only after validation, which eliminates downtime during the cutover. Both strategies directly preserve application availability by avoiding full-scale disruption.

Last reviewed: Jun 20, 2026

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