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What is Blue/Green deplyoment

# Blue/Green deplyoment

## create IAM role

* in the main navigation choose _Roles_
* click _create Role_
* choose **CodeDeploy** as AWS service
* choose **CodeDeploy – ECS** as UseCase to add and click _Next::Permissions_
* ensure that on _attach permissions policies_ page the policy **AWSCodeDeployRoleForECS** is listed, otherwise add this policy
* click _Next:Tags_
* click _Next:Review_
* save the role as **CodeDeployServiceRole**

## extend Loadbalancer listeners

Open AWS mgm console, sectin _EC2_ ==> _Loadbalancer_
create two new listeners, one with port **8080** and one with port **8088** , for testing

## create ECS service

create new service _simplehttp-bluegreen_

* EC2 based
* task definition _td-simplehttp-ec2_
* deployment type _Blue/green deployment (powered by AWS CodeDeploy)_
* deployment config: Canary10Percent5Minutes
* service role: CodeDeployServiceRole (the one which you created in the first step)
* Task placement: binpack
* disable _service discovery_
* enable Loadbalancing
* choose existing loadbalancer
* container to load balance: _simplehttp-container:0:8000 ==> click _Add to load balancer_
* production listener port: 8080
* enable _Test listener_
* Test listener port: 8088
* additional configuration ==> create two targetgroups: **bluegreen-1** and **bluegreen-2**

==> check CodeDeploy section in DeveloperTools category within AWS mgm console

## update CodePipeline

* Open your CodePipeline pipeline
* update the _Build_ step
* add missing artifacts to buildspec.yaml. Open buildspec.yml and replace the the existing _artifacts_ section by the following:

– printf ‘{“ImageURI”:”%s”}’ $REPOSITORY_URI:$IMAGE_TAG > imageDetail.json
– ‘image*.json’
– ‘appspec.yaml’
– ‘taskdef.json’
– appspec.yaml
– taskdef.json
– imageDetail.json

* set output artifacts to _DefinitionArtifact_ and _ImageArtifact_ as listed in the buildspec.yml
* update the _Deploy_ step
* change from _Deploy to ECS_ to use _Deploy to ECS (Blue/Green)_ as “Action provider”
* choose the correct region your ECS is up and running
* as “Input Artifacts” choose _ImageArtifact_ and _DefinitionArtifact_ (which are created at the build step, ref buildspec.yml )
* Select the app and deployment group which have been created in the previous step (ECS service creation)
* at “Amazon ECS task definition” choose _DefinitionArtifact_ and enter filename _taskdef.json_
* at “AWS CodeDeploy AppSpec file” choose _DefinitionArtifact_ and enter filename _appspec.yaml_
* enable “Dynamically update task definition image”
* choose _ImageArtifact_ as Input artifact
* enter _IMAGE1\_NAME_ as Placeholder text in the task definition
* click _Done_

* add appspec.yaml to CodeCommit repository (in root directory)

version: 0.0

– TargetService:
Type: AWS::ECS::Service
ContainerName: “simplehttp-container”
ContainerPort: 8000

* add taskdef.json to CodeCommit repository
* grab content from the task definition _td-simplehttp-ec2_ within ECS section, tab _JSON_ directly
* property **image:** ==> replace the image name by the placeholder , including brackets
* save file as taskdef.json add push it to _simplehttp_ CodeCommit repository

## trigger the pipeline

* edit simplehttp.go and change the output
* commit and push to CodeCommit
* CodePipeline will be triggered

About Abhay Singh

7 + years of expertise of Cloud Platform(AWS) with Amazon EC2, Amazon S3, Amazon RDS, VPC, IAM, Amazon ELB, Scaling, CloudFront, CDN, CloudWatch, SNS, SQS, SES and other vital AWS services. Understand Infrastructure requirements, and propose design, and setup of the scalable and cost effective applications. Implement cost control strategies yet keeping at par performance. Configure High Availability Hadoop big data ecosystem, Teradata, HP Vertica, HDP, Cloudera on AWS, IBM cloud & other cloud services. Infrastructure Automation using Terraform, Ansible and Horton Cloud Break setups. 2+ Years of development experience with Big Data Hadoop cluster, Hive, Pig, Talend ETL Platforms, Apache Nifi. Familiar with data architecture including data ingestion pipeline design, Hadoop information architecture, data modeling, and data mining, machine learning, and advanced data processing. Experience at optimizing ETL workflows. Good knowledge of database concepts including High Availability, Fault Tolerance, Scalability, System, and Software Architecture, Security and IT infrastructure.

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