boraoren/microservice-nodejs

Udagram Image Filtering Microservice

1. Description
2. Prerequisites
3. Project Modules
   1. Frontend
   2. Feed Service
   3. User Service
4. Run Project
   1. Locally
   2. On Aws
5. Delete project from AWS

Prerequisites

The following tools need to be installed on your local machine

• Docker
• AWS CLI
• Kubectl
• KubeOne
• Terraform
• Amazon Web Services account
• DockerHub account

Description

Udagram is a simple cloud application developed alongside the Udacity Cloud Engineering Nanodegree. It allows users to register and log into a web client, post photos to the feed, and process photos using an image filtering microservice.

Project Modules

The project is split into three parts:

Frontend

A basic Ionic client web application which consumes the RestAPI Backend.

Feed Service

User Service

Run Project

clone the repository
git clone git@github.com:boraoren/microservice-nodejs.git

Locally

1. touch ~/.profile
2. add texts below to ~/.profile

POSTGRESS_USERNAME=udagram
POSTGRESS_PASSWORD=password
POSTGRESS_DB=udagram
POSTGRESS_HOST=postgresql

1. go to udacity-c3-deployment/docker directory
   1. run docker-compose up command

On Aws

The application is running in a Kubernetes Cluster on AWS.

1. AWS S3

   1. Create an AWS/S3 bucket which name is {YOUR_NAME}-udacity-microservice-bucket
   2. give permission

      {
      	"Version": "2012-10-17",
      	"Id": "Policy1565786082197",
      	"Statement": [{
      		"Sid": "Stmt1565786073670",
      		"Effect": "Allow",
      		"Principal": {
      			"AWS": "__YOUR_USER_ARN__"
      		},
      		"Action": [
      			"s3:GetObject",
      			"s3:PutObject"
      		],
      		"Resource": "__YOUR_BUCKET_ARN__/*"
      	}]
      }
   

   1. CORS configuration

        <?xml version="1.0" encoding="UTF-8"?>
         <CORSConfiguration xmlns="http://s3.amazonaws.com/doc/2006-03-01/">
             <CORSRule>
                 <AllowedOrigin>*</AllowedOrigin>
                 <AllowedMethod>GET</AllowedMethod>
                 <AllowedMethod>POST</AllowedMethod>
                 <AllowedMethod>DELETE</AllowedMethod>
                 <AllowedMethod>PUT</AllowedMethod>
                 <MaxAgeSeconds>3000</MaxAgeSeconds>
                 <AllowedHeader>Authorization</AllowedHeader>
                 <AllowedHeader>Content-Type</AllowedHeader>
             </CORSRule>
        </CORSConfiguration>
   

2. Kubernetes Cluster

   1. add texts below to ~/.profile

      AWS_REGION=${YOUR_AWS_REGION}
      AWS_PROFILE=${YOUR_AWS_PROFILE}
      AWS_BUCKET=${__YOUR_NAME-udacity-microservice-bucket}
      URL=http://localhost:8100
      JWT_SECRET=${YOUR_JWT_SECRET}
   

   1. terraform
      1. go to terraform/aws directory
      2. run terraform init command
      3. set values
         1. variables.tf line 59 default to your AWS region
         2. variables.tf line 33 default to your SSH public key file path
      4. run terraform plan command to confirm
         1. enter a value: udagram
      5. run terraform apply command to execute for AWS
         1. enter a value: udagram
         2. enter yes after running the command.
      6. run terraform output -json > tf.json to create state that will be used by kubeone
   2. kubernetes
      1. go to terraform/aws directory
      2. run in terminal export AWS_ACCESS_KEY_ID=${YOUR_AWS_ACCESS_KEY_ID}"
      3. run in terminal export AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}"
      4. run kubeone install config.yml --tfjson tf.json command
         1. if Error: failed to install prerequisites: at least one of the tasks has encountered an error occurs,
      5. set environment for kubeone KUBECONFIG=$PWD/udagram-kubeconfig

3. Postgresql Database

   1. Create AWS/RDS/Postgresql instance which name is udagram
   2. Terraform step created security group automatically so you should add udagram_common security group to your Postgresql database instance to let services access to your database.

4. Deploy Application

   1. replace .profile file POSTGRESS_HOST key
      with Endpoint (you can find endpoint from AWS Web Dashboard RDS Panel Connectivity & Security Tab)
   2. go to udacity-c3-deployment/docker directory
   3. find and replace borasmus container image names at below by your own docker hub name;
      1. backend-user-deployment.yaml
      2. backend-feed-deployment.yaml
      3. frontend-deployment.yaml
      4. reverseproxy-deployment.yaml
      5. docker-compose-build.yaml
      6. docker-compose.yaml
   4. login to your dockerhub docker login --username=__YOUR_USER_NAME__ --email=__YOUR_EMAIL__
   5. build your images docker-compose -f docker-compose-build.yaml build --parallel
   6. push your builded images to dockerhub docker-compose -f docker-compose-build.yaml push
   7. go to udacity-c3-deployment/k8s directory
   8. run deploy_services.sh command
   9. run deploy.sh command
   10. add CloudWatch agent
       1. go to udacity-c3-deployment/k8s/fluentd directory
       2. run deploy_fluentd.shcommand

Delete Project from AWS

Delete Kubernetes Cluster

1. go to terraform/aws directory
2. run kubeone reset config.yml command
3. run terraform destroy