Skip to content

Latest commit

 

History

History
230 lines (152 loc) · 9.46 KB

README.md

File metadata and controls

230 lines (152 loc) · 9.46 KB
Raw

Deploy-Docker-App-AWS-EB

Custom CLI to deploy a dockerized Spring Boot application to AWS Elastic Beanstalk.

AWS Elastic Beanstalk + Docker

Application

This folder contains the sample code for a Spring boot application. See the instructions below for how to deploy and run this application.

ci-badge

Dependencies

  • PostgreSQL => Version 9.6 or higher is required. For development environment a docker-compose is provided within this project.
  • Java 8

Run application

Dev environment

  1. Go to the application directory.

  2. Deploy BBDD dependencies:

    docker-compose up

  3. Run the application:

    ./gradlew run

Prod environment

  1. Build the application:

    ./gradlew build

    This command will generated the following jar: build/libs/helloworld-0.0.1-SNAPSHOT.jar

  2. Run the application:

    java -jar helloworld-0.0.1-SNAPSHOT.jar --spring.profiles.active=pro

In both cases, application will run in the 8000 port.

Note: In deploy time a script initializing the Database will be executed, this script could take more than 3 minutes.

REST API

This application provides a REST API for get users info.

Get User

  • URL: /users/{userId}

  • Method: GET

  • Response:

    {"id":104,"name":"user104","surname":"surname104","type":3}

Get Users by type

Gets the users of the given type.

  • URL: /users?userType={userTypeId}

  • Method: GET

  • Response:

    [
  {"id":23,"name":"user23","surname":"surname23","type":6},
  {"id":32,"name":"user32","surname":"surname32","type":6},
  {"id":38,"name":"user38","surname":"surname38","type":6}
]

Possible values of userType are between 1 and 10.

Note:

Application and access logs will be generated in the following folder: /var/log/helloworld

Deployment

How does it work?

The deploy.py CLI deploys the Spring boot example application to AWS Elastic Beanstalk performing the following tasks:

  1. Create a boto3 session to store the AWS credentials and the region to use for the deployment. If there is any configuration defined through environment variables or stored in AWS CLI ~/.aws folder, the AWS credentials and the region are directly retrieved from there (it is possible to specify the profile to use as optional argument). Otherwise, the CLI asks for these parameters interactively.
  2. Check if the Elastic Beanstalk application is already created, and if not, create it.
  3. Build the Spring boot example application.
  4. Create the ZIP package (source bundle) for the new application version.
  5. Upload the application version package to a source bundle S3 bucket.
  6. Create the new application version for the Elastic Beanstalk application.
  7. Create the environment if it does not exist or has been previously terminated, or update it if it is already created. The CLI check if there is an operation in progress in the environment and wait for it to be completed before updating or recreating it.

Dependencies

  • Python 3.3+
  • Boto3

Prerequisites

  • The aws-elasticbeanstalk-ec2-role instance profile (AWS IAM EC2 Role) created in the AWS account:

    Managing Elastic Beanstalk instance profiles

  • The aws-elasticbeanstalk-service-role service role (AWS IAM Elastic Beanstalk Role) created in the AWS account:

    Managing Elastic Beanstalk service roles

  • An IAM User or an AWS IAM Role attached to the EC2 instance (only for executions from EC2 instances) with the following IAM Managed Policy attached:

    AWSElasticBeanstalkFullAccess

  • Pip tool for Python packages management. Installation:

    # From Linux
$ curl -O https://bootstrap.pypa.io/get-pip.py
$ sudo python3 get-pip.py

# From macOS
$ brew install python

  • AWS SDK for Python. Installation:

    # From Linux
$ sudo pip3 install boto3

# From macOS
$ pip3 install boto3

Execution Method

Here you have the message that you will get if you request help to the deploy.py CLI:

$ ./deploy.py --help
usage: deploy.py [-h] -a APPLICATION_NAME -e ENVIRONMENT_NAME [-p PROFILE]

Custom CLI to deploy an application to AWS Elastic Beanstalk

optional arguments:
  -h, --help            show this help message and exit

Options:
  -a APPLICATION_NAME, --application-name APPLICATION_NAME
                        Name of the Elastic Beanstalk application
  -e ENVIRONMENT_NAME, --environment-name ENVIRONMENT_NAME
                        Name of the environment for the Elastic Beanstalk
                        application
  -p PROFILE, --profile PROFILE
                        Use a specific profile from AWS CLI stored
                        configurations

Provided Configuration Profiles

This project provides the following configuration profiles:

  • env.yaml.staging => Configuration profile intended for staging environments deployed for development, test, QA or demo purposes (lower cost and performance). This profile allows to deploy a single-instance type environment (henceforth SingleInstance) made up of one EC2 instance with an Elastic IP address to serve the application, and a Single-AZ RDS instance to host the databases.
  • env.yaml.production => Configuration profile intended for environments with productive loads. This profile allows to deploy a load-balancing, autoscaling type environment (henceforth LoadBalanced) made up of an Auto Scaling group of EC2 instances with an ELB to serve the application, and a Multi-AZ RDS instance to host the databases.

Execution Examples

# Deployment of a staging environment
$ ln -sf env.yaml.staging env.yaml
$ ./deploy.py --application-name helloworld --environment-name test [--profile <aws_cli_profile>]

# Deployment of a productive environment
$ ln -sf env.yaml.production env.yaml
$ ./deploy.py --application-name helloworld --environment-name live [--profile <aws_cli_profile>]

Environment Customization

If you need to modify any settings provided in this project or add new ones, feel free to fork or import this repository and apply the changes you need to fulfil your use case.

Here are some common customizations that you might want to add to an environment:

  • To deploy a SingleInstance type environment in a existing custom VPC, add the following configuration block to the env.yaml.staging file:

      aws:ec2:vpc:
    VPCId: <vpc_id>
    Subnets: <subnet_1a_id>,<subnet_1b_id>,...      # Subnet IDs for EC2 instance
    DBSubnets: <subnet_2a_id>,<subnet_2b_id>,...    # Subnet IDs for RDS instance
    AssociatePublicIpAddress: true                  # True required for immutable deployments/updates

  • To deploy a LoadBalanced type environment in a existing custom VPC, add the following settings to the existing aws:ec2:vpc namespace in env.yaml.production file:

      aws:ec2:vpc:
    ELBScheme: public                               # This setting is already defined
    VPCId: <vpc_id>
    ELBSubnets: <subnet_3a_id>,<subnet_3b_id>,...   # Subnet IDs for ELB
    Subnets: <subnet_1a_id>,<subnet_1b_id>,...      # Subnet IDs for Auto Scaling group
    DBSubnets: <subnet_2a_id>,<subnet_2b_id>,...    # Subnet IDs for RDS instance
    AssociatePublicIpAddress: true                  # Review this option in https://amzn.to/2Vhgt5B

  • To configure HTTPS in a LoadBalanced type environment for a custom domain using an ACM issued certificate, add the following configuration block to the env.yaml.production file:

      aws:elb:listener:443:
    ListenerProtocol: HTTPS
    InstancePort: '80'
    InstanceProtocol: HTTP
    ListenerEnabled: true
    SSLCertificateId: <acm_certificate_arn>

    Then modify the InstancePort setting belonging to the aws:elb:listener:80 namespace replacing the port 80 by 81.

  • To configure a SSH key pair to securely log into the EC2 instance/s belonging to an environment, add the following setting to the existing aws:autoscaling:launchconfiguration namespace in any of the env.yaml.<config_profile> files:

      aws:autoscaling:launchconfiguration:
    . . .
    . . .
    EC2KeyName: <key_pair_name>

Related Links