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Automating Blue/Green Deployments with CodePipeline and CDK
You are part of the platform engineering team at Globomantics and are responsible for safely deploying a customer facing APIs. Currently the team is facing challenges during production releases that's causing outages and downtime resulting in manual rollback. There is a need to modernize the deployment pipeline by implementing approval controls, zero-downtime and to reduce reliance on manual interventions. In this lab, you will model a multi-stage deployment pipeline using AWS CDK, configure a production deployment with gradual traffic shifting, approval gates before changes are deployed to production and validate that the system can automatically roll back when a deployment health check fails.
Lab Info
Table of Contents
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Challenge
Orchestrate Multi-Stage Deployment Pipeline Using CDK
- Review the CDK project structure, pipeline structure and bootstrap the environment.
- Define a codePipeline dev and production deployment stages.
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Challenge
Introduce Approval Gates Between Dev and Production
- Add a manual approval action such that the production deployments are validated and approved and do not start automatically.
- Define an error threshold using CloudWatch alarms to rollback the changes when deployment experiences error.
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Challenge
Configure a Production Blue/Green Deployment with Traffic Shifting
- Configure Lambda function to publish versions and alias during deployment.
- Leverage CodeDeploy to perform traffic shifting into production.
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