How to deploy with Gitlab-Ci to EC2 using AWS CodeDeploy/CodePipeline/S3

autronix's answer is awesome, although in my case I had to gave up the CodePipeline part due to the following error : The deployment failed because a specified file already exists at this location : /path/to/file. This is because I already have files at the location since I'm using an existing instance with a server running already on it.

Here is my workaround :

In the .gitlab-ci.yml here is what I changed :

deploy:
  stage: deploy
  script:
    - curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip" # Downloading and installing awscli
    - unzip awscliv2.zip
    - ./aws/install
    - aws deploy push --application-name App-Name --s3-location s3://app-deployment/app.zip # Adding revision to s3 bucket
    - aws deploy create-deployment --application-name App-Name --s3-location bucket=app-deployment,key=app.zip,bundleType=zip --deployment-group-name App-Name-Fleet --deployment-config-name CodeDeployDefault.OneAtATime --file-exists-behavior OVERWRITE # Ordering the deployment of the new revision
  when: on_success
  only:
    refs:
      - dev

The important part is the aws deploy create-deployment line with it's flag --file-exists-behavior. There are three options available, OVERWRITE was the one I needed and I couldn't manage to set this flag with CodePipeline so I went with the cli option.

I've also changed a bit the part for the upload of the .zip. Instead of creating the .zip myself I'm using aws deploy push command which will create a .zip for me on the s3 bucket.

There is really nothing else to modify.

I have created a set of sample files to go with the Guide provided below. These files are available at the following link: https://gitlab.com/autronix/gitlabci-ec2-deployment-samples-guide/

Scope

This guide assumes the following

Gitlab EE hosted project - may work on private CE/EE instances (not tested)
Gitlab as the GIT versioning repository
Gitlab-CI as the Continuous Integration Engine
Existing AWS account
AWS EC2 as the target production or staging system for the deployment
AWS EC2 Instance running Amazon Linux AMI
AWS S3 as the storage facility for deployment files
AWS CodeDeploy as the Deployment engine for the project
AWS CodePipeline as the Pipeline for deployment

The provided .gitlab-ci.yml sample is based on a Java/Scala + Gradle project. The script is provided as a generic example and will need to be adapted to your specific needs when implementing Continuous Delivery through this method.

The guide will assume that the user has basic knowledge about AWS services and how to perform the necessary tasks.

Note: The guide provided in this sample uses the AWS console to perform tasks. While there are likely CLI equivalent for the tasks performed here, these will not be covered throughout the guide.

Motivation

The motivation for creating these scripts and deployment guide came from the lack of availability of a proper tutorial showing how to implement Continuous Delivery using Gitlab and AWS EC2. Gitlab introduced their freely available CI engine by partnering with Digital Ocean, which enables user repositories to benefit from good quality CI for free.

One of the main advantages of using Gitlab is that they provide built-in Continuous Integration containers for running through the various steps and validate a build. Unfortunately, Gitblab nor AWS provide an integration that would allow to perform Continuous Deliver following passing builds.

This Guide and Scripts (https://gitlab.com/autronix/gitlabci-ec2-deployment-samples-guide/) provide a simplified version of the steps that I've undertaken in order to have a successful CI and CD using both Gitlab and AWS EC2 that can help anyone else get started with this type of implementation.

Setting up the environment on AWS

The first step in ensuring a successful Continuous Delivery process is to set up the necessary objects on AWS in order to allow the deployment process to succeed.

AWS IAM User

The initial requirement will be to set up an IAM user:

https://console.aws.amazon.com/iam/home#users

Create a user

Attach the following permissions:

CodePipelineFullAccess
AmazonEC2FullAccess
AmazonS3FullAccess
AWSCodeDeployFullAccess

Inline Policy:

  {
    "Version": "2012-10-17",
    "Statement": [
      {
        "Effect": "Allow",
        "Action": [
          "autoscaling:*",
          "codedeploy:*",
          "ec2:*",
          "elasticloadbalancing:*",
          "iam:AddRoleToInstanceProfile",
          "iam:CreateInstanceProfile",
          "iam:CreateRole",
          "iam:DeleteInstanceProfile",
          "iam:DeleteRole",
          "iam:DeleteRolePolicy",
          "iam:GetInstanceProfile",
          "iam:GetRole",
          "iam:GetRolePolicy",
          "iam:ListInstanceProfilesForRole",
          "iam:ListRolePolicies",
          "iam:ListRoles",
          "iam:PassRole",
          "iam:PutRolePolicy",
          "iam:RemoveRoleFromInstanceProfile",
          "s3:*"
        ],
        "Resource": "*"
      }
    ]
  }

Generate security credentials

Note: The policies listed above are very broad in scope. You may adjust to your requirements by creating custom policies that limit access only to certain resources.

Note: Please keep these credentials in a safe location. You will need them in a later step.

AWS EC2 instance & Role

Instance Role for CodeDeploy

https://console.aws.amazon.com/iam/home#roles

Create a new Role that will be assigned to your EC2 Instance in order to access S3,

Set the name according to your naming conventions (ie. MyDeploymentAppRole)
Select Amazon EC2 in order to allow EC2 instances to run other AWS services
Attache the following policies:
- AmazonEC2FullAccess
- AmazonS3FullAccess
- AWSCodeDeployRole

Note: The policies listed above are very broad in scope. You may adjust to your requirements by creating custom policies that limit access only to certain resources.

Launch Instance

https://console.aws.amazon.com/ec2/v2/home

Click on Launch Instance and follow these steps:

Select Amazon Linux AMI 2016.03.3 (HVM), SSD Volume Type
Select the required instance type (t2.micro by default)
- Next
Select IAM Role to be MyDeploymentAppRole (based on the name created in the previous section)
- Next
Select Appropriate Storage
- Next
Tag your instance with an appropriate name (ie. MyApp-Production-Instance)
- add additional tags as required
- Next
Configure Security group as necessary
- Next
Review and Launch your instance

You will be provided with the possibility to either generate or use SSH keys. Please select the appropriate applicable method.

Setting up instance environment

Install CodeDeploy Agent

Log into your newly created EC2 instance and follow the instructions:

http://docs.aws.amazon.com/codedeploy/latest/userguide/how-to-run-agent-install.html

CodeDeploy important paths:

CodeDeploy Deployment base directory: /opt/codedeploy-agent/deployment-root/
CodeDeploy Log file: /var/log/aws/codedeploy-agent/codedeploy-agent.log

Tip: run tail -f /var/log/aws/codedeploy-agent/codedeploy-agent.log to keep track of the deployment in real time.

Install your project prerequisites If your project has any prerequisites to run, make sure that you install those before running the deployment, otherwise your startup script may fail.

AWS S3 repository

https://console.aws.amazon.com/s3/home

In this step, you will need to create an S3 bucket that will be holding your deployment files.

Simply follow these steps:

Choose Create Bucket
- Select a bucket name (ie. my-app-codepipeline-deployment)
- Select a region
In the console for your bucket select Properties
- Expand the Versioning menu
- choose Enable Versioning

AWS CodeDeploy

https://console.aws.amazon.com/codedeploy/home#/applications

Now that the basic elements are set, we are ready to create the Deployment application in CodeDeploy

To create a CodeDeploy deployment application follow these steps:

Select Create New Application
Choose an Application Name (ie. MyApp-Production )
Choose a Deployment Group Name (ie. MyApp-Production-Fleet)
Select the EC2 Instances that will be affected by this deployment - Search by Tags
- Under Key Select Name
- Under Value Select MyApp-Production-Instance
Under Service Role, Select MyDeploymentAppRole
Click on Create Application

Note: You may assign the deployment to any relevant Tag that applied to the desired instances targeted for deployment. For simplicity's sake, only the Name Tag has been used to choose the instance previously defined.

AWS CodePipeline

https://console.aws.amazon.com/codepipeline/home#/dashboard

The next step is to proceed with creating the CodePipeline, which is in charge of performing the connection between the S3 bucket and the CodeDeploy process.

To create a CodePipeline, follow these steps:

Click on Create Pipeline
Name your pipeline (ie. MyAppDeploymentPipeline )
- Next
Set the Source Provider to Amazon S3
- set Amazon S3 location to the address of your bucket and target deployment file (ie. s3://my-app-codepipeline-deployment/myapp.zip )
- Next
Set Build Provider to None - This is already handled by Gitlab-CI as will be covered later
- Next
Set Deployment Provider to AWS CodeDeploy
- set Application Name to the name of your CodeDeploy Application (ie. MyApp-Production)
- set Deployment Group to the name of your CodeDeploy Deployment Group (ie. MyApp-Production-Fleet )
- Next
Create or Choose a Pipeline Service Role
- Next
Review and click Create Pipeline

Setting up the environment on Gitlab

Now that The AWS environment has been prepared to receive the application deployment we can proceed with setting up the CI environment and settings to ensure that the code is built and deployed to an EC2 Instance using S3, CodeDeploy and the CodePipeline.

Gitlab Variables

In order for the deployment to work, we will need to set a few environment variables in the project repository.

In your Gitlab Project, navigate to the Variables area for your project and set the following variables:

AWS_DEFAULT_REGION => your AWS region
AWS_SECRET_ACCESS_KEY => your AWS user credential secret key (obtained when you generated the credentials for the user)
AWS_ACCESS_KEY_ID => your AWS user credential key ID (obtained when you generated the credentials for the user)
AWS_S3_LOCATION => the location of your deployment zip file (ie. s3://my-app-codepipeline-deployment/my_app.zip )

These variables will be accessible by the scripts executed by the Gitlab-CI containers.

Startup script

A simple startup script has been provided (https://gitlab.com/autronix/gitlabci-ec2-deployment-samples-guide/blob/master/deploy/extras/my_app.sh) to allow the deployment to perform the following tasks:

Start the application and create a PID file
Check the status of the application through the PID file
Stop the application

You may find this script under deploy/extras/my_app.sh

Creating gitlab-ci.yml

The gitlab-ci.yml file is in charge of performing the Continuous Integration tasks associated with a given commit. It acts as a simplified group of shell scripts that are organized in stages which correspond to the different phases in your Continuous Integration steps.

For more information on the details and reference, please refer to the following two links:

http://docs.gitlab.com/ce/ci/quick_start/README.html
http://docs.gitlab.com/ce/ci/yaml/README.html

You may validate the syntax of your gitlab-ci.yml file at any time with the following tool: https://gitlab.com/ci/lint

For the purpose of deployment, we will cover only the last piece of the sample provided with this guide:

deploy-job:
  # Script to run for deploying application to AWS
  script:
    - apt-get --quiet install --yes python-pip # AWS CLI requires python-pip, python is installed by default
    - pip install -U pip  # pip update
    - pip install awscli  # AWS CLI installation
    - $G build -x test -x distTar # # Build the project with Gradle
    - $G distZip  # creates distribution zip for deployment
    - aws s3 cp $BUNDLE_SRC $AWS_S3_LOCATION # Uploads the zipfile to S3 and expects the AWS Code Pipeline/Code Deploy to pick up
  # requires previous CI stages to succeed in order to execute
  when: on_success
  stage: deploy
  environment: production
  cache:
    key: "$CI_BUILD_NAME/$CI_BUILD_REF_NAME"
    untracked: true
    paths:
        - build/
  # Applies only to tags matching the regex: ie: v1.0.0-My-App-Release
  only:
    - /^v\d+\.\d+\.\d+-.*$/
  except:
    - branches
    - triggers

This part represents the whole job associated with the deployment following the previous, if any, C.I. stages.

The relevant part associated with the deployment is this:

# Script to run for deploying application to AWS
script:
  - apt-get --quiet install --yes python-pip # AWS CLI requires python-pip, python is installed by default
  - pip install -U pip  # pip update
  - pip install awscli  # AWS CLI installation
  - $G build -x test -x distTar # # Build the project with Gradle
  - $G distZip  # creates distribution zip for deployment
  - aws s3 cp $BUNDLE_SRC $AWS_S3_LOCATION # Uploads the zipfile to S3 and expects the AWS Code Pipeline/Code Deploy to pick up

The first step involves installing the python package management system: pip. pip is required to install AWS CLI, which is necessary to upload the deployment file to AWS S3

In this example, we are using Gradle (defined by the environment variable $G); Gradle provides a module to automatically Zip the deployment files. Depending on the type of project you are deploying this method will be different for generating the distribution zip file my_app.zip.

The aws s3 cp $BUNDLE_SRC $AWS_S3_LOCATION command uploads the distribution zip file to the Amazon S3 location that we defined earlier. This file is then automatically detected by CodePipeline, processed and sent to CodeDeploy. Finally, CodeDeploy performs the necessary tasks through the CodeDeploy agent as specified by the appspec.yml file.

Creating appspec.yml

The appspec.yml defines the behaviour to be followed by CodeDeploy once a deployment file has been received.

A sample file has been provided along with this guide along with sample scripts to be executed during the various phases of the deployment.

Please refer to the specification for the CodeDeploy AppSpec for more information on how to build the appspec.yml file: http://docs.aws.amazon.com/codedeploy/latest/userguide/app-spec-ref.html

Generating the Deployment ZipFile

In order for CodeDeploy to work properly, you must create a properly generated zip file of your application.

The zip file must contain:

Zip root
- appspec.yml => CodeDeploy deployment instructions
- deployment stage scripts
- provided samples would be placed in the scripts directory in the zip file, would require the presence my_app.sh script to be added at the root of your application directory (ie. my_app directory in the zip)
- distribution code - in our example it would be under the my_app directory

Tools such as Gradle and Maven are capable of generating distribution zip files with certain alterations to the zip generation process. If you do not use such a tool, you may have to instruct Gitlab-CI to generate this zip file in a different manner; this method is outside of the scope of this guide.

Deploying your application to EC2

The final step in this guide is actually performing a successful deployment.

The stages of Continuous integration are defined by the rules set in the gitlab-ci.yml. The example provided with this guide will initiate a deploy for any reference matching the following regex: /^v\d+\.\d+\.\d+-.*$/.

In this case, pushing a Tag v1.0.0-My-App-Alpha-Release through git onto your remote Gitlab would initiate the deployment process. You may adjust these rules as applicable to your project requirements.

The gitlab-ci.yml example provided would perform the following jobs when detecting the Tag v1.0.0-My-App-Alpha-Release:

build job - compile the sources
test job - run the unit tests
deploy-job - compile the sources, generate the distribution zip, upload zip to Amazon S3

Once the distribution zip has been uploaded to Amazon S3, the following steps happen:

CodePipeline detects the change in the revision of the S3 zip file
CodePipeline validates the file
CodePipeline sends signal that the bundle for CodeDeploy is ready
CodeDeploy executes the deployment steps
- Start - initialization of the deployment
- Application Stop - Executes defined script for hook
- DownloadBundle - Gets the bundle file from the S3 repository through the CodePipeline
- BeforeInstall - Executes defined script for hook
- Install - Copies the contents to the deployment location as defined by the files section of appspec.yml
- AfterInstall - Executes defined script for hook
- ApplicationStart - Executes defined script for hook
- ValidateService - Executes defined script for hook
- End - Signals the CodePipeline that the deployment has completed successfully

Successful deployment screenshots:

Gitlab Deploy Job

CodePipeline Deploy

CodeDeploy hook script log

References

Gitlab-CI QuickStart: http://docs.gitlab.com/ce/ci/quick_start/README.html
Gitlab-CI .gitlab-ci.yml: http://docs.gitlab.com/ce/ci/yaml/README.html
AWS CodePipeline Walkthrough: http://docs.aws.amazon.com/codepipeline/latest/userguide/getting-started-w.html
Install or Reinstall the AWS CodeDeploy Agent: http://docs.aws.amazon.com/codedeploy/latest/userguide/how-to-run-agent-install.html
AWS CLI Getting Started - Env: http://docs.aws.amazon.com/cli/latest/userguide/cli-chap-getting-started.html#cli-environment
AppSpec Reference: http://docs.aws.amazon.com/codedeploy/latest/userguide/app-spec-ref.html