README.md

Django Blog Application deployed on AWS Application Load Balancer with Auto Scaling, S3, Relational Database Service, VPC's Components, Lambda, DynamoDB and CloudFront with Route 53 using Terraform with AWS and GitHub Providers

Description

The Blog Page Application aims to deploy blog application as a web application written Django Framework on AWS Cloud Infrastructure using Terraform with AWS and GitHub Providers to create all resources needed to deploy the architecture. This infrastructure has Application Load Balancer with Auto Scaling Group of Elastic Compute Cloud (EC2) Instances and Relational Database Service (RDS) on defined VPC. Also, The CloudFront and Route 53 services are located in front of the architecture and manage the traffic in secure. User is able to upload pictures and videos on own blog page and these are kept on S3 Bucket.

Project Architecture

Terraform Resources

• Your company has recently ended up a project that aims to serve as Blog web application on isolated VPC environment. You and your colleagues have started to work on the project. Your Developer team has developed the application and you are going to deploy the app in production environment.

• Application is coded by Fullstack development team and given you as DevOps team. App allows users to write their own blog page to whom user registration data should be kept in separate MySQL database in AWS RDS service and pictures or videos should be kept in S3 bucket. The object list of S3 Bucket containing movies and videos is recorded on DynamoDB table.

• The web application will be deployed using Django framework.

• The Web Application should be accessible via web browser from anywhere in secure.

• You are requested to push your program to the project repository on the Github. You are going to pull it into the webservers in the production environment on AWS Cloud.

In the architecture, you can configure your infrastructure using the followings,

• The application stack should be created with new AWS resources.

• Specifications of VPC:

  • VPC has two AZs and every AZ has 1 public and 1 private subnets.

  • VPC has Internet Gateway

  • One of public subnets has NAT Instance.

  • You might create new instance as Bastion host on Public subnet or you can use NAT instance as Bastion host.

  • There should be managed private and public route tables.

  • Route tables should be arranged regarding of routing policies and subnet associations based on public and private subnets.

• You should create Application Load Balancer with Auto Scaling Group of Ubuntu 18.04 EC2 Instances within created VPC.

• You should create RDS instance within one of private subnets on created VPC and configure it on application.

• The Auto Scaling Group should use a Launch Template in order to launch instances needed and should be configured to;

  • use all Availability Zones on created VPC.

  • set desired capacity of instances to 2

  • set minimum size of instances to 2

  • set maximum size of instances to 4

  • set health check grace period to 90 seconds

  • set health check type to ELB

  • Scaling Policy --> Target Tracking Policy

    • Average CPU utilization (set Target Value %80)

    • seconds warm up before including in metric ---> 200

    • Set notification to your email address for launch, terminate, fail to launch, fail to terminate instance situations

• ALB configuration;

  • Application Load Balancer should be placed within a security group which allows HTTP (80) and HTTPS (443) connections from anywhere.

  • Certification should be created for secure connection (HTTPS)

    • To create certificate, AWS Certificate Manager can be utilized.

  • ALB redirects to traffic from HTTP to HTTPS

  • Target Group

    • Health Check Protocol is going to be HTTP

• The Launch Template should be configured to;

  • Prepare Django environment on EC2 instance based on Developer Notes,

  • Deploy the Django application on port 80.

  • Launch Template only allows HTTP (80) and HTTPS (443) ports coming from ALB Security Group and SSH (22) connections from anywhere.

  • EC2 Instances type can be configured as t2.micro.

  • Instance launched should be tagged AWS Capstone Project

  • Since Django App needs to talk with S3, S3 full access role must be attached EC2s.

• For RDS Database Instance;

  • Instance type can be configured as db.t2.micro

  • Database engine can be MySQL with version of 8.0.20.

  • RDS endpoint should be addressed within settings file of blog application that is explained developer notes.

  • Please read carefully "Developer notes" to manage RDS sub settings.

• CloudFront should be set as a cache server which points to Application Load Balance with following configurations;

  • The CloudFront distribution should communicate with ALB securely.

  • Origin Protocol policy can be selected as HTTPS only.

  • Viewer Protocol Policy can be selected as Redirect HTTP to HTTPS

• As cache behavior;

  • GET, HEAD, OPTIONS, PUT, POST, PATCH, DELETE methods should be allowed.

  • Forward Cookies must be selected All.

  • Newly created ACM Certificate should be used for securing connections. (You can use same certificate with ALB)

• Route 53

  • Connection must be secure (HTTPS).

  • Your hostname can be used to publish website.

  • Failover routing policy should be set while publishing application

    • Primary connection is going to be Terraform

    • Secondary connection is going to be a static website placed another S3 bucket. This S3 bucket has just basic static website that has a picture said "the page is under construction" given files within S3_static_Website folder

    • Healthcheck should check If CloudFront is healthy or not.

• As S3 Bucket

  • First S3 Bucket

    • It should be created within the Region that you created VPC

    • Since development team doesn't prefer to expose traffic between S3 and EC2s on internet, Endpoint should be set on created VPC.

    • S3 Bucket name should be addressed within configuration file of blog application that is explained developer notes.

  • Second S3 Bucket

    • This Bucket is going to be used for failover scenario. It has just a basic static website that has a picture said "the page is under construction"

• To write the objects of S3 on DynamoDB table

  • Lambda Function

    • Lambda function is going to be Python 3.8

    • Python Function can be found in github repo

    • S3 event is set as trigger

    • Since Lambda needs to talk S3 and DynamoDB and to run on created VPC, S3, DynamoDB full access policies and NetworkAdministrator policy must be attached it

    • S3 Event must be created first S3 Bucket to trigger Lambda function

  • DynamoDB Table

    • Create a DynamoDB table which has primary key that is id

    • Created DynamoDB table's name should be placed on Lambda function.

Credentials in the Project

You need to have following credentials in .env file under the src folder to deploy the application on AWS Cloud Infrastructure with successfull Database connection.

• Define your Django secret key in SECRET_KEY without any quotes. For more information, please refer to Django documentation.

  SECRET_KEY=<your secret key without spaces and quotes>
  

• When defining your RDS Database password, you set it in the CloudFormation Stack creation step. I used curl to replace content in .env file in Userdata. So you don't need to define it in .env file. Leave it as below.

  PASSWORD='your DB password without any quotes'
  

---

Hi DevOps Team;

• We have coded a blog app. Users can publish their blog pages which have their comments, movie or picture files.

• Movie and picture files are kept in S3 as object.

  • You should create an S3 bucket and write name of it on "/src/cblog/settings.py" file as AWS_STORAGE_BUCKET_NAME variable.

  • In addition, you must assign region of S3 as AWS_S3_REGION_NAME variable.

• Users credentials and blog contents are going to be kept on RDS database. To connect ECs to RDS, following variables must be assigned on "/src/cblog/settings.py" file after you create RDS;

  • a. Database name - "NAME" variable

  • b. Database endpoint - "HOST" variables

  • c. Port - "PORT"

  • d. PASSWORD variable must be written on "/src/.env" file not to be exposed with settings file

• We need to look object list of S3.

  • That's why, we decided to create a DynamoDB table. We have thought to use Lambda function for this purpose and also we have written python code.

  • However, we need help to create Lambda function to manage this serverless process. You can find our python function as lambda_function.py within github repo.

• Since our first aim is to keep our environment in highly secure environment, we want you to establish this infrastructure in our own VPC.

Thanks for your time and patience dear DevOps. Good Luck!

---

Expected Terraform Outcome

Load Balancer DNS Outcome Example

RDS Database Outcome Example

---

The following topics will be used at the end of the project:

• Bash scripting

• AWS EC2 Launch Template Configuration

• AWS VPC Configuration

  • VPC
  • Private and Public Subnets
  • Private and Public Route Tables
  • Managing routes
  • Subnet Associations
  • Internet Gateway
  • NAT Gateway
  • Bastion Host
  • Endpoint

• AWS EC2 Application Load Balancer Configuration

• AWS EC2 ALB Target Group Configuration

• AWS EC2 ALB Listener Configuration

• AWS EC2 Auto Scaling Group Configuration

• AWS Relational Database Service Configuration

• AWS EC2, RDS, ALB Security Groups Configuration

• IAM Roles configuration

• S3 configuration

• Static website configuration on S3

• DynamoDB Table configuration

• Lambda Function configuration

• Get Certificate with AWS Certification Manager Configuration

• AWS CloudFront Configuration

• Route 53 Configuration

• Git & Github for Version Control System

At the end of the project, you will be able to;

• Construct VPC environment with whole components like public and private subnets, route tables and managing their routes, internet Gateway, NAT Instance.

• Apply web programming skills, importing packages within Python Django Framework

• Configure connection to the MySQL database.

• Demonstrate bash scripting skills using user data section within launch template to install and setup Blog web application on EC2 Instance.

• Create a Lambda function using S3, Lambda and DynamoDB table.

• Demonstrate their configuration skills of AWS VPC, EC2 Launch Templates, Application Load Balancer, ALB Target Group, ALB Listener, Auto Scaling Group, S3, RDS, CloudFront, Route 53.

• Apply git commands (push, pull, commit, add etc.) and Github as Version Control System.

Solution Steps

• Step 1: Create dedicated VPC and whole components

• Step 2: Create Security Groups (ALB ---> EC2 ---> RDS)

• Step 3: Create RDS

• Step 4: Create two S3 Buckets and set one of these as static website

• Step 5: Download or clone project definition

• Step 6: Prepare your Github repository

• Step 7: Prepare a userdata to be utilized in Launch Template

• Step 8: Write RDS, S3 in settings file given by Fullstack Developer team

• Step 9: Create NAT Instance in Public Subnet

• Step 10: Create Launch Template and IAM role for it

• Step 11: Create certification for secure connection

• Step 12: Create ALB and Target Group

• Step 13: Create Autoscaling Group with Launch Template

• Step 14: Create CloudFront in front of ALB

• Step 15: Create Route 53 with Failover settings

• Step 16: Create DynamoDB Table

• Step 17-18: Create Lambda function

• Step 17-18: Create S3 Event and set it as trigger for Lambda Function

Notes

• Consider the developer team's notes for deployment. Look at the developer_notes.md file.

• RDS database should be located in private subnet. just EC2 machines that has ALB security group can talk with RDS.

• RDS is located on private groups and only EC2s can talk with it on port 3306

• ALB is located public subnet and it redirects traffic from http to https

• EC2's are located in private subnets and only ALB can talk with them

Resources

• Python Django Framework

• Python Django Example

• AWS CLI Command Reference

• AWS CloudFormation

• Terraform