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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.

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Top AWS Solution Architect Projects in 2024 [with Source Code]

Home Blog Cloud Computing Top AWS Solution Architect Projects in 2024 [with Source Code]

The world's most valuable publicly listed firm, Amazon offers everything from e-commerce to cloud services. A majority of businesses and organizations around the globe rely on Amazon Web Services (AWS), the company's cloud computing division. As more enterprises adopt AWS for comprehensive operational management , the demand for cloud computing specialists rises. Consequently, individuals aiming to bolster their IT and cloud computing careers are keen on obtaining AWS credentials.

The AWS Solutions Architect certification stands out as the most desired among various AWS qualifications. AWS Solution Architect roles have significant applications in the realms of AI , Machine Learning, IoT, and numerous other cutting-edge technologies. As technology evolves, possessing this certification ensures a competitive edge in the industry.

Furthermore, it opens doors to myriad opportunities in the dynamic world of tech. In the below blog, we are going to read more about some of these AWS Solution Architect projects. We can also learn more about the same on Solution Architect Training .

Who is an AWS Solution Architect?

In the normal world, architects are responsible for creating structures and various designs of buildings. AWS Solution Architects are similar to them just instead of buildings, they are responsible for creating and designing in AWS. AWS Solutions Architects are primarily responsible for deploying applications to AWS cloud infrastructure . It is their duty to produce a design that not only reduces costs but also takes usability, dependability, scalability, and performance into account.

AWS Solutions Architects are also in charge of reducing risks that an organization can encounter, including risks related to application unavailability, calculation mistakes, and data breaches. To build the most secure cloud environment possible, this necessitates a thorough grasp of how to combine all the components in the AWS cloud. 

Why You Should Work on AWS Projects? 

Users of the AWS platform can take use of cloud computing concepts such as Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). Cloud computing technologies are becoming an essential component of business operations and procedures. The AWS projects can aid in the development of skills in cloud computing as well as other cutting-edge and critical technologies such as IoT, AI, and others. 

Professionals may be able to study the numerous service options for novices via AWS projects. They may also aid in the growth and enhancement of web development, hosting, design, and deployment abilities. Data management and handling is another area that may be examined and improved by working on these project ideas. There are several AWS open-source projects available that can aid with expertise. Professionals may broaden their skill sets by working on these AWS freelancing assignments. In the next section, we have discussed some of the sample projects for AWS Solution Architect.

Top 10 AWS Solution Architect Projects

Below are some of the AWS Solution Architect sample projects:

1. Rapid Document Conversion

The objective is to precisely and rapidly convert the document to the format that the user has chosen. Online stores provide a wide variety of document converters, including PDF to Word converters and others. You must have needed to convert an HTML page or document to PDF format at some point. In a similar vein, converting an Excel sheet to a Word document or other format is frequently necessary. You may create a program that quickly converts documents between different file formats using AWS Lambda. You may get the necessary content, format it, and transform it so that it can be downloaded or shown on the website. You may use such an app on a job portal where users frequently want to change the format of their resume. This is one of the basic projects and comes under AWS Solution Architect Associate projects. To learn more about cloud computing, visit the best Cloud Computing courses .

Source Code: Document Conversion

2. Windows VM Deployment

The objective is to install Windows Virtual Machines without introducing any instances that violate security. Microsoft Azure's VM Management is a well-liked utility for deploying virtual machines. Windows virtual machines can be deployed on AWS, and Amazon Lightsail may be used as the web service for this purpose. It will help to streamline the process and allow you to use the most resources possible in accordance with your needs. You may connect to the RDP client using this service, and the user interface is simple to get used to.

Source Code: VM Deployment

3. Website Development

The objective is to create a website using AWS that has high levels of security, dependability, usability, and availability. The virtual private server used to build various websites is AWS Lightsail. By building a website, you may practice using AWS. You may build a website to manage your household spending or one to record student information at a university. When using AWS Lightsail as the virtual private server, you may utilize either the AWS EC2 or AWS Lambda services.

Source Code: Website Development

4. Content Recommendation System

The objective is to utilize AI and ML with AWS to suggest content to end customers based on their past behavior. Nearly all streaming services, including Netflix and Amazon Prime, feature content suggestions. To work on this project, you may leverage the AWS cloud using closest-neighbor techniques. Please utilize Amazon SageMaker for this project. It is the instrument for easily carrying out ML implementations. It has built-in algorithms that don't require label information. Additionally, it streamlines the activities by substituting semantic search for string matching. Results and suggestions will be accurate thanks to AWS and closest neighbor algorithms. This comes under AWS Solution Architect live projects.

5. Serverless Web Application

With the aid of AWS (Amplify, Lambda, etc.), the objective is to create and release a serverless web app that is reliable and easy to use. A notable real-world application that makes use of several AWS and cloud services is Netflix. To work on the project, you can mix a variety of technologies. For example, the front end of the app and hosting procedures will require AWS Amplify. The back-end administration and authentication may be handled via AWS Cognito. Additionally, you may utilize DynamoDB to add a persistence layer for storage. The backend API may be used with AWS Lambda and API Gateway. Additionally, you must be familiar with how to develop RESTful APIs using HTML, JavaScript, and CSS. You may start with a straightforward app, like an MI calculator. This comes under the AWS Solution Architect Capstone project.

6. Text-to-speech converter

The goal of this machine learning project is to create text-to-speech software. A common AI-based feature seen in many websites and online apps is text-to-speech. The program Google Text-to-Speech is one of the most widely utilized. Text data may be spoken aloud using AWS Lambda and Amazon Polly. You may be able to create apps for speech synthesis that are realistic thanks to the combination. Utilize cutting-edge deep learning technology with Amazon Polly to do precise conversions. Since it will be crucial in all real-time applications, AWS Lambda will have the opportunity to increase response times.

7. Personalized News Feed

A personalized news stream based on preferences and past browsing and search history is the aim. According to search and browsing history, Google employs this feature to display suggested articles in the mobile browser. You may create a customized content delivery platform using AWS Lambda and DynamoDB. It will be your responsibility to gather the data from user touchpoints. The data for the application is kept in DynamoDB. The platforms for creating user profiles are Lambda functions and data that has been saved. The construction of the customer feed is made possible by associated factors.

8. Build Android Application

Consider creating a native Android app to provide a list of student outcomes. AWS Amplify will meet all of your requirements if you want to build up APIs that permit listing, generating, and saving student data as well as user authentication but don't want to handle the backend management. The primary method for communicating with AWS services from an Android smartphone is the Amplify Android library. Because it offers a high-level interface for carrying out all kinds of cloud activities.

9. Real Time Data Processing Application

The objective is to handle the large amounts of data in real-time while maintaining the correctness of the results. A real-world example is Bustle, which uses AWS services to handle enormous amounts of site statistic data in real-time. To complete this project, you may utilize AWS Lambda and Amazon Kinesis Stream. In the first stage, you will be needed to construct a Kinesis Stream, and it will be crucial for you to setup it so that it may collect data from a web source. With the scalability of the stream, several Lambda function instances will scale up or down automatically. You can utilize location-based data or social media timelines as your data sources. Three forms are available for integrating Kinesis with AWS Lambda: stream-based approach, synchronous invocation model, and event structure model. This comes under AWS Solution Architect real time projects.

10. Train Machine Learning Model

Machine learning specialists are in high demand, thus working on ML projects is a need if you want to work in this field. Amazingly, AWS has machine learning options in its services, with Amazon SageMaker being the most well-liked among them. SageMaker may be used in this project to train a machine-learning model. You may create machine learning applications using Amazon SageMaker's distinctive, integrated development environment. You may create notebooks, move between phases, examine the outcomes, and do a lot more using the IDE. You may rapidly and effectively obtain the compute instances using SageMaker notebooks. To finish the procedure with a lot less effort, you may also use SageMaker's Autopilot option.

Applications of AWS Solution Architect Projects

AWS Solution Architect applications are used in wide range of businesses and applications as discussed in above section. The aim of these applications is to design and provide scalable, secure, and cost-effective solutions for their customers for their daily needs and requirements. These projects cover wide range of applications in industries and other areas.

These applications include providing global infrastructure to enterprises and providing various scalable and cost-effective storage solutions. It also covers applications such as Big Data Analysis and IoT solutions. AWS Solution Architect applications also helps us in Machine learning algorithms and its applications which are in lot of demand right now. Other than these it also provides applications which provide serverless architecture, development tools and building of websites and mobile applications.

The above examples demonstrate the importance of AWS Solution Architect projects in meeting the ever-changing demands of industries and organizations. To get in-depth knowledge about the AWS Solution Architect course, you can check KnowledgeHut Solution Architect training .

An excellent career outlook is available for AWS Solutions Architects. Once you're in the industry and have established yourself as a competent and experienced expert, you'll likely become a sought-after professional with possibilities to climb up the career ladder or move to another organization in addition to the numerous opportunities that are now accessible to you.

Frequently Asked Questions (FAQs)

Some of the commonly faced challenges in AWS Solution Architect projects are cost management, performance challenges, and security-related and network issues.

You have access to a vast array of features and tools to assist you in achieving your security goals. In the areas of network security, configuration management, access control, and data encryption, AWS offers security-specific tools and services.

Some of the best practices for AWS Solution Architect projects are to make the project scalable and reliable, optimize the costs as much as possible, and make the performance as efficient as possible.

AWS Solution Architects adopt a consumption model where you only pay for what you use, evaluate your total resource usage efficiency, and avoid paying for data center operations like electricity cooling. Utilise managed services to lower the cost of ownership and spot patterns by tracking spending over time.

Suhas Hegde

Suhas is an software engineer working in the IT field with 4.5 years experience. In the past 4.5 years he has worked in various domains such as ERP and Cloud. And also have training and experience in SAP HR and SAP ABAP and currently working as a developer in SAP for MNC. And also  done certifications in AWS cloud like AWS solution architect and also have experience working in cloud domain.

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ZacharyLinton/AWS-Cloud-Architecting-Capstone-Project

Folders and files, repository files navigation, aws-cloud-architecting-capstone-project, this project consists of deploying a php application with the following requirements:, - provide secure hosting of a mysql database, - provide secure access to an administrative user, - provide anonymous access to public users, - website to be run on a t2.micro ec2 instance (providing ssh access to administrators), - provide high availability of website by using an application load balancer, - store database connection information in the aws systems manager parameter store, - provide automatic scaling using a launch template.