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Posted on Apr 4, 2023

The AWS Academy Cloud Architecting - Capstone Project

The AWS Academy Cloud Architecting Capstone Project was all about designing and implementing a cloud-based solution using Amazon Web Services to solve a particular business problem. This included developing an architectural plan, deploying and configuring the required AWS services, and implementing the solution using industry best practices.

Additionally, I made sure that this project related to cost optimisation, by selecting and making use of the most efficient computing resources when initialising processes, (as a budgeting precaution, of course), which could always be scaled up in case of business growth.

I followed a simple procedure in order to discover the issues and carry out the required tasks.

Inspecting the architecture

In this initial phase, I just wanted to have a look at the environment - what AWS had already provided us, as well as any guesses on what was missing from the scenario. These are some of the things I decided to do before starting:

• Inspect the VPC.
• Inspect the Subnets.
• Inspect the Security Groups.
• Inspect the Instances.

The Cloud 9 IDE

Shortly after creating an AWS Cloud9 environment, I used the following command to get the ".zip" file which contains the PHP and image files for the website of the organisation which was then extracted.

wget <link of the zip file>

The LAMP web server stack on Linux

The following commands were used to install the LAMP stack:

sudo yum -y update sudo amazon-linux-extras install -y lamp-mariadb10.2-php7.2 php7.2

sudo yum install -y httpd mariadb-server sudo systemctl start httpd

sudo systemctl enable httpd sudo systemctl is-enabled httpd

This stack is essential for us to successfully deliver the website in a simple yet, stable way!

LAMP stands for Linux, Apache, MySQL, and PHP. Together, they provide a proven set of software for delivering high-performance web applications. Each component contributes essential capabilities to the stack.

After installing the stack, I simply:

• Opened port 80 from the security group of the Cloud9 EC2 instance
• Got the cloud9 EC2 public instance IP address and tested that I could access the website

Creating a MySQL RDS database instance

First of all, I crated an AWS RDS subnet group in the private subnets in zones us-east-1a and us-east-1b.

Then I proceeded to create an AWS RDS database with the following specifications:

-Databasetype: MySQL -Template: Dev/Test -DBinstanceidentifier: Example -DB instance size: db.t3.micro -Storage type: General Purpose (SSD) -Allocatedstorage: 20GiB -Storageautoscaling: Enabled -Standbyinstance: Enabled -Virtualprivatecloud: ExampleVPC -Databaseauthenticationmethod: Passwordauthentication -Initialdatabasename: exampledb -Enhancedmonitoring: Disabled

Creating an Application Load Balancer

An Application Load Balancer is a requirement, so I created one using the following criteria:

-Create target group -Launch Web Instances in the private subnet

Importing the data into the RDS database

Used the wget <SQL dump file link> command on Cloud9 to get the file with the sample data, connected and imported the data into the RDS database using: mysql -u admin -p --host <rds-endpoint> mysql -u admin -p exampledb --host <rds-endpoint> < Countrydatadump.sql

Parameters Store Configuration

Added the following parameters to the Parameter Store and set the correct values:

/example/endpoint

/example/username

/example/password

/example/database exampledb

Creating a Launch Template and an Autoscaling Group

The final steps of this project consisted of:

• Modifying the IAM role of the instance created by Cloud9 to enable query on the website
• Created an Image of the instance (AMI)
• Modified Launch Template to use the recently created AMI
• Using the Launch Template with the correct AMI ID for the Autoscaling Group creation

This allowed me to connect to the website by entering the Load Balancer's endpoint, it queried the data from the RDS database successfully too (Check out my design for this scenario which sums up the architecture).

In conclusion, the AWS Academy Cloud Architecting 2.x - Capstone Project allowed me to develop the understanding of some concepts about creating a solution in a potentially real-life scenario. This project improved my overall confidence and knowledge about cloud environments, since in order to create a fully-functioning architecture there must be crucial factors to consider.

Lastly, I would recommend this project to everyone that is trying to commence their journey on the Cloud, because not only does this project challenge you to come up with solutions whenever there is an issue or whenever you are stuck, but it gives you some substantial hands-on experience and a taste of architecting a realistic case.

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CPSC 4440 Final Project

This project was assigned to me as a final project for the cloud architecture course I took at Clemson University. This project was split into five parts using different AWS services: IAM, EC2 with Load Balancing, VPC, RDS, and EC2 Auto-Scaling. Click here to see the project instructions. A diagram of the final product is shown below:

For the IAM part of the project, I had to create some IAM users and groups. I assigned the groups policies and then put each user into the group they belonged in following the principle of least privilege.

For the VPC part of the project, I had to allocate an elastic IP address, create a VPC that looked identical to the diagram, create an internet gateway, create 4 subnets, create a public route table, and to create a private route table associated with the private subnets.

For the database part of the project, I was instructed to make a new RDS instance running on MYSQL. The first step was to create a DB subnet group called CU-Subnets that included the two private subnets. Then, I created the RDS database. It had a burstable db.t2.micro instance and a general purpose storage type. The database had a Multi-AZ deployment using the VPC already set up and the CU-Subnets subnet group.

EC2 Auto-Scaling

For 10 points extra credit on the project, we had the option to configure EC2 Auto Scaling behind our load balancer. I decided to do this option. Auto Scaling enables your architecture to scale up by add more instances as load increases, and then scale down by removing instances as load decreases. The launch configuration used the AMI I had created earlier. It used a target tracking policy that scaled up when CPU utilization was greater than 60% for 3 minutes.

AWS Academy: Cloud Architecting Capstone Project

The capstone project for the AWS Academy Cloud Architecting course was the last assignment you had to complete in order to obtain the badge for completing the course. It took a combination of the skills learned throughout the previous challenge labs in order to obtain a perfect score. Unfortunately, I do not have a diagram of what the final architecture looked like, but I will go into detail about what the project instructions were. For starters, here six main steps that needed to be completed: 1. Create an EC2 auto-scaling group from an existing launch configuration in the environment 2. Attach an application load balancer to the EC2 auto-scaling group 3. Create an RDS instance that the PHP application can query 4. Create a MYSQL database from a SQL dump file 5. Update application parameters in the AWS Systems Manager Parameter Store 6. Secure the application to prevent public access to backend systems

Setting up auto scaling

Setting up the auto-scaling group was fairly straight forward since the launch configuration was already defined in the environment. It was just a matter of picking the right AWS region and VPC and subnets to deploy the auto-scaling group in. The instances would be placed in 2 private subnets, each in a different availability zone. I set the minimum number of instances to 2, the desired amount to 2, and max amount to 4. It would scale up to when the CPU utilization was above 60% for 3 minutes.

Attaching an Application Load Balancer

An application load balancer spreads HTTP and HTTPS traffic across registered instances equally. After the EC2 auto-scaling group instances had passed their health checks, I created an application load balancer and then selected my auto-scaling group. Under the details tab, I selected load balancing->edit. I then clicked the check mark for application load balancer and selected the right target group. There was 1 already made in the lab environment. The application load balancer will take traffic from the public internet and then distribute the load across the EC2 instances in the private subnets. This ensures greater security.

Creating an RDS instance

Creating an RDS instance is pretty straight forward. First, I created 2 database subnet groups (the private subnet for each availability zone). Then, using the RDS wizard I made a RDS instance running MYSQL. I used a multi availability zone deployment and made sure that only the web application servers could communicate with the database instance.

Creating a MySQL database from a MYSQL dump file and Updating the Parameter Store

The pre-configured environment for the capstone project had a bastion host setup to access the EC2 instances in the private subnets. I gained access to one of the EC2 instances through the bastion host and then used it to run a mysql dump. The EC2 instance already had the mysql dump file in its home directory. The command was similar to this: mysql -h RDS_Endpoint -u username -p databasename < databasename.sql. This command setup the RDS instance with all the data the previous database contained. All that I had to to do now was make the EC2 instances read and write to the RDS instance instead of the old database. This was solved by changing the endpoint and password values in the parameter store. I then deleted the old database since it was no longer needed.

Securing the application

The last step was ensuring that the VPCs, security groups, and route tables were setup correctly. All internet traffic was to be go through the elastic load balancer, which would then distribute the traffic evenly between the EC2 instances. HTTP and HTTPS traffic from any source would be allowed. The bastion host would only accept SSH traffic from my IP address and have outbound rules to the EC2 instances. The EC2 instances would accept inbound traffic from the elastic load balancer and from the RDS instance. The RDS instance would only accept traffic from the EC2 instances and would only send information to the EC2 instances. The architecture was secure.

Capstone Project: AWS Academy Cloud Architecting 2.x

Abstract: This article outlines the steps to complete the Capstone Project for the AWS Academy Cloud Architecting 2.x course. Learn how to design and deploy a secure and scalable infrastructure on AWS.

Capstone Project: AWS Academy Cloud Architecting 2.x - Site Focused with a Global Topic

In this capstone project, we will focus on designing and implementing a scalable, secure, and highly available website on the AWS cloud while adhering to best practices and architectural patterns. The website will be designed to handle global traffic, ensuring low latency and fast response times for users around the world.

Introduction

The AWS Academy Cloud Architecting 2.x course provides students with the skills and knowledge to design and implement scalable, secure, and highly available systems on the AWS cloud. The capstone project for this course involves designing and implementing a website that can handle global traffic, ensuring low latency and fast response times for users around the world.

Architecture Design

The architecture for the website will consist of the following components:

• A content delivery network (CDN) to distribute static content to users around the world
• An auto-scaling group of web servers to handle dynamic content
• A load balancer to distribute traffic across the web servers
• A relational database service (RDS) to store dynamic content
• A Simple Storage Service (S3) bucket to store static content
• A CloudFront distribution to distribute the static content

Content Delivery Network (CDN)

A CDN is a distributed network of servers that cache and deliver content to users from a location near them. This reduces latency and improves the user experience. In this project, we will use Amazon CloudFront as our CDN.

Auto-Scaling Group of Web Servers

An auto-scaling group is a collection of EC2 instances that can be automatically scaled up or down based on demand. In this project, we will use an auto-scaling group of web servers to handle dynamic content. The web servers will be configured to automatically scale up or down based on the CPU utilization of the instances in the group.

Load Balancer

A load balancer distributes traffic across multiple instances or servers to ensure that no single instance or server is overwhelmed with traffic. In this project, we will use an Application Load Balancer (ALB) to distribute traffic across the web servers in the auto-scaling group.

Relational Database Service (RDS)

RDS is a managed database service that makes it easy to set up, operate, and scale a relational database in the cloud. In this project, we will use RDS to store dynamic content. We will use Amazon Aurora as our RDS engine, which provides high performance and availability.

Simple Storage Service (S3) Bucket

S3 is a highly durable and scalable object storage service that can be used to store and retrieve any amount of data from anywhere on the web. In this project, we will use an S3 bucket to store static content, such as images, CSS, and JavaScript files.

CloudFront Distribution

CloudFront is a fast content delivery network (CDN) service that securely delivers data, videos, applications, and APIs to customers globally with low latency and high transfer speeds within a developer-friendly environment. In this project, we will use a CloudFront distribution to distribute the static content stored in the S3 bucket.

Implementation

To implement the architecture, we will perform the following steps:

• Create an S3 bucket to store the static content
• Create a CloudFront distribution to distribute the static content
• Create an RDS instance to store the dynamic content
• Create an auto-scaling group of web servers
• Create an Application Load Balancer to distribute traffic across the web servers
• Configure the web servers to use the RDS instance as the database
• Configure the web servers to serve the static content from the S3 bucket
• Configure the CloudFront distribution to use the S3 bucket as the origin
• Test the website to ensure that it is functioning correctly

In this capstone project, we have designed and implemented a scalable, secure, and highly available website on the AWS cloud that can handle global traffic. By using a CDN, auto-scaling group of web servers, load balancer, RDS, S3 bucket, and CloudFront distribution, we have ensured low latency and fast response times for users around the world. This project has demonstrated the power and flexibility of the AWS cloud and the importance of architectural patterns and best practices in designing and implementing scalable, secure, and highly available systems.

• In this capstone project, we have designed and implemented a website that can handle global traffic on the AWS cloud
• We have used a CDN, auto-scaling group of web servers, load balancer, RDS, S3 bucket, and CloudFront distribution to ensure low latency and fast response times for users around the world
• This project has demonstrated the power and flexibility of the AWS cloud and the importance of architectural patterns and best practices in designing and implementing scalable, secure, and highly available systems
• Amazon CloudFront
• Auto Scaling
• Elastic Load Balancing
• Relational Database Service
• Simple Storage Service
• Amazon Aurora

--questionbegin--

Pick another query string (89) "Connection error: php\_network\_getaddresses:getaddrinfofailed: Nameserver not known" bagaimana caranya, saya sudah melakukan configurasi dengan benar.

--questionend--

The error message "Connection error: php\_network\_getaddresses:getaddrinfofailed: Nameserver not known" typically indicates that there is a problem with the DNS configuration. Here are some steps you can take to troubleshoot this issue:

• Check that the DNS server is configured correctly in your system's network settings.
• Try flushing the DNS cache on your system.
• Check that the domain name you are trying to connect to is resolving to the correct IP address.
• Try using a different DNS server, such as Google DNS (8.8.8.8 and 8.8.4.4) or Cloudflare DNS (1.1.1.1 and 1.0.0.1).
• Check that the domain name is not expired or suspended.
• Check that there are no firewall rules or security groups blocking traffic to the domain name.

If you have already checked these steps and are still experiencing issues, you may want to contact your hosting provider or DNS provider for further assistance.

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Tags: :  AWS Cloud Architecting 2.x

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