aws capstone project ideas

15+ AWS Projects Ideas for Beginners to Practice in 2024

Explore some interesting guided AWS projects ideas for beginners with source code to practice that can be a value add-on to a resume in 2024.

AWS (Amazon Web Services) is the world’s leading and widely used cloud platform, with over 200 fully featured services available from data centers worldwide. This blog presents some of the most unique and innovative AWS projects from beginner to advanced levels. These AWS project ideas will give you a better idea of various AWS tools and their business applications.

AWS Project-Website Monitoring using AWS Lambda and Aurora

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With over 1 million active enterprise customers, 8K AWS partner network members,1900+ third-party software products, and over 70 million hours spent on the Amazon Marketplace monthly by its customers - AWS is a name to reckon with in the cloud computing industry. Amazon Web Services was launched in July 2002 from the existing Amazon cloud platform with the initial purpose of managing online retail transactions. Today, AWS offers over 200 fully-featured services spread across 18 geographical regions. You can access these services for free or by paying nominal charges using an AWS Free Tier account. AWS generated revenue of $18 Billion in 2017, and the figure has been aggressively rising since then.  Before we get into the technicalities on how one can leverage any AWS service and build some exciting AWS projects, here is a quick overview of AWS to understanding the cloud platform and its services. 

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AWS is a secure cloud computing platform that provides cloud computing, databases, networking, content storage, etc. AWS offers improved flexibility and security to the customers. The core infrastructure is formed to meet the security requirements for various applications developed using the services and the platform. As illustrated in the figure below, AWS offers a wide range of services classified into different types and categories. 

Image Credit: aws.amazon.com 

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AWS projects have a broad array of applications. It is possible to quickly develop and deploy AWS real-time projects for fundamental to advanced applications. Any cloud computing professional can design AWS cloud projects and AWS enterprise projects using these services. Amazon Elastic Compute Cloud, EC2, enables users to rent virtual computing resources to run their applications. AWS Lambda is another foundation service for serverless computing. AWS users can run code without worrying about managing the services or creating workload-aware cluster scaling logic. AWS Lambda projects are popular as they require zero administration. Internet of Things, IoT is one of the emerging technologies. AWS resources offer immense opportunities in AWS IoT projects as well. 

AWS has exceptional flexibility to select the desired operating system, database, and other services. The virtual environment provides the capabilities to load the services and the software as per the application needs. The migration process from an existing platform to an AWS-based solution is also easy—security, reliability, and ease of use are other attributes attached to AWS projects and applications. 

As a result, these projects are applicable in the academic phase and the professional journey. Students can work on these AWS project ideas to list them on their resumes and showcase their cloud computing skills to the recruiters to land their dream job. AWS provides ease of developing highly complex projects for industrial and business applications. 

New Projects

AWS platform allows the user to use cloud computing models, such as Infrastructure as a Service, IaaS, Platform as a Service, PaaS, and Software as a Service, SaaS. Cloud Computing technologies are now an integral part of business processes and operations. The projects on AWS can assist in developing skills in cloud computing and the other advanced and significant technologies, such as IoT, AI, and many more. 

AWS projects for beginners can allow professionals to explore the various service offerings. They can also assist in developing and enhancing web development, hosting, design, and deployment skills. Data management and handling is another area that can be explored and improved by working on these project ideas. 

Many of the open-source projects on AWS are available and can provide a better understanding. Professionals can also enhance their skill-sets by working on these AWS freelance projects. 

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We have curated a list of exciting project ideas on AWS. You can work on these AWS sample projects to expand your skills and knowledge.  

This section lists some of the easiest AWS projects for beginners that will help you upskill yourself by working on various AWS cloud services.

1. Rapid Document Conversion 

The goal is to quickly and accurately convert the document to the desired format as selected by the user. Many document converters, such as PDF to word converters and others, are available online. You must have experienced the need to convert an HTML page/document into PDF format. Similarly, it is often required to convert an excel sheet to a word document or other formats. AWS Lambda will allow you to develop an app that can rapidly convert documents from one format to the other. You can retrieve the required content and can format and convert the content to download or display on the webpage. You can deploy such an app in a job portal wherein the users often wish to convert their resume to another format. 

Build a Job Winning Data Engineer Portfolio with Solved End-to-End Big Data Projects .

2. Windows Virtual Machine – Deployment 

The goal is to deploy Windows Virtual Machine with zero security violation instances in the process. VM Management in Microsoft Azure is a popular tool utilized to deploy virtual machines. You can deploy Windows VM in AWS, and for this purpose, you can use Amazon Lightsail as the web service. It will assist in simplifying the task and will enable you to utilize the optimum number of resources as per the need. The user interface offered with this service is easy to adapt to, and you can use the service to connect with the RDP client. 

3. Mass Emailing using AWS Lambda

This project aims to send mass e-mails to a business firm's existing and potential customers. MoonMail is one of the real-world mass mailing cloud platforms designed with the help of AWS Lambda.  To develop a cost-effective mass-mailing platform, you can combine AWS Lambda with Simple Email Service, SES. Along with S3, you can share mass mails with more recipients. 

As soon as you upload a CSV file, it will trigger an S3 event. Lambda function will then import the file into the database. The process of sending the mail to the addresses provided will begin. 

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4. Website Development using AWS

The goal is to develop a website with the help of AWS with high security, reliability, usability, and availability. AWS Lightsail is the virtual private server for creating numerous websites. You can experiment with working on AWS by creating a website. You may create a website to store the student details in a university ay develop the website to track your home expenses. You can use AWS EC2 or AWS Lambda services with AWS Lightsail as the virtual private server. It will provide SSD-based storage and comes pre-configured with several web development options. 

5. Serverless Web App 

The goal is to develop and deploy a serverless web app that is secure and usable with the help of AWS (Amplify, Lambda, etc.).  Netflix is a popular real-world application that uses many AWS and cloud services. You can combine numerous technologies to work on the project. AWS Amplify, for instance, will be needed for the front-end of the app along with hosting processes. AWS Cognito can manage the authentication and administration for the back-end. You can also use DynamoDB to incorporate a persistence layer for storage. AWS Lambda and API Gateway are suitable for using the backend API. You shall also be aware of HTML, JavaScript, CSS, and RESTful API implementation. You can begin with a simple app, such as a MI calculator. 

Once you've worked on the beginner-level AWS projects, it's time for you to test your progress by trying your hands-on few intermediate-level AWS projects. These projects are mainly suitable for working professionals having around two to four years of working experience.

6. Real-time Data Processing Application 

The goal is to process the high-volume data quantities in real-time with no compromises on the accuracy of the outcomes. Bustle is a real-world example that processes massive volumes of site metric data in real-time by leveraging AWS resources. You can use Amazon Kinesis Stream and AWS Lambda to work on this project. You will be required to create a Kinesis Stream in the initial step, and it will be essential for you to configure it to capture the data from a web source. Several Lambda function instances will be scaled up or down automatically with the scaling of the stream. You can use social media timelines or location-based data as your data sources. 

Image Credit:  www.simform.com 

You can integrate Kinesis and AWS Lambda in either three formats: a stream-based model, synchronous invocation model, or event structure model. 

7. Customer Logic Workflow

The goal is to design and deploy custom logic workflows for the applications in response to the trigger events.  Coke vending machine is a real-world application of AWS Lambda and SNS. Food Panda, a food delivery app, is another famous example that implements this.  It is now possible to include Lambdas in the existing workflows with step functions. It is an AWS project for beginners because these functions will be short, and you can quickly test and validate the outcome. Shopping cart management is one of the areas wherein you can design and implement this project. The information will be readily available from any of the e-commerce websites. 

8. Kubernetes Clusters on Amazon EC2 Spot

The project aims to set up Kubernetes clusters on Amazon EC2 Spot with 100% adherence to the best practices. Kubernetes is open-source and extremely popular in the cloud computing industry with abundant real-world applications. It is an excellent AWS project for beginners developing AWS and Kubernetes skills. Amazon EC2 is one of the foundational services of AWS, and you will have to work on the same. The service gets dynamic computing capabilities on the cloud. You shall take a step ahead and use Amazon EC2 Spot instances for this project. These instances and Kubernetes follow the same approach towards containers, so you will have the option to use both of them. In this project, you can build multiple node groups. Also, you shall focus on capacity optimization for allocation. It will make sure that the functions of the worker nodes are adequate. 

Ace your Big Data engineer interview by working on unique end-to-end solved Big Data Projects using Hadoop .

9. Content Recommendation System

The goal is to use AI and ML with AWS to recommend the content to the end-users based on the history.  Almost all streaming apps, such as Netflix or Amazon Prime, have content recommendation systems. You can use AWS cloud with nearest neighbor algorithms to work on this project. For this project,  use Amazon SageMaker . It is the tool for carrying out ML implementations with ease. It includes built-in algorithms that do not need label data. Also, it uses semantic search in place of string matching to simplify the tasks. AWS combined with nearest neighbor algorithms will provide accurate results and recommendations. 

10. Chatbots using AWS Lex

The project’s goal is to develop a chatbot to provide instant replies to the messages sent by the users. Amazon and many other e-commerce android apps have chatbots installed to reply to users’ queries instantly. You can use Amazon Lex to build a chatbot and combine it with AWS Lambda for exceptional outcomes. Lex is the service specifically developed to simplify chatbot development. You can use the same to experience one-click deployment and add your application to the desired platform. Platform independence is also essential for the chatbots created using Amazon Lex. 

This section includes some advanced-level projects suitable for professionals who are willing to further strengthen their skillset by working on industry-relevant projects.

11. Custom Alexa Skills

The goal is to develop a virtual assistant replicating the skills and functions of Amazon Alexa. Alexa is a product by Amazon and is a widely used virtual assistant.  You can use AWS Lambda with a custom Alexa skill set, and it is an object embedded within AWS Console to invoke the handler function. Along with this, use the Alexa skill handler function, which is an AWS Lambda function. You will obtain the custom logic, and it will manage the fulfillment of the user’s request. You can also use third-party functions hosted outside of the Alexa skill. You can begin with the basic tasks, such as playing the music or creating a reminder. 

Recommended Reading: 

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12. Serverless Image Recognition Engine 

The goal is to develop an application that can automatically recognize the images uploaded on the app. NatGeo image recognition is an example of a widely used real-world app. You can use AWS Lambda and several in-built functions to develop this machine learning project . For example, one of the Lambda functions will invoke the metadata in the image uploaded. The other will gather Rekognition to identify the patterns in the picture. You shall also use DynamoDB to maintain the back-end of the application. 

13. Text-to-Speech Converter

This machine learning project aims to develop an app that can convert text to speech. Text-to-Speech is an AI-based functionality witnessed in many websites and web apps. Google Text-to-Speech is one of the popularly used applications. With AWS Lambda & Amazon Polly, you can convert textual information to speech. The combination can provide you with the ability to develop lifelike speech synthesis applications. With Amazon Polly, you can use advanced deep learning technologies to carry out accurate conversions. AWS Lambda will provide the ability to improve the response rate as it will be critical in any of the real-time applications. 

14. Personalized News Feed

The goal is to create a personalized news feed based on the preferences and previous search and browsing history. Google uses this functionality to show the suggested articles in the mobile browser based on the search and browsing history. You can use AWS DynamoDB and AWS Lambda to develop a personalized content delivery platform. You will be required to extract the information from user touchpoints. DynamoDB stores the information for the application. Data stored and Lambda functions are the platforms to develop the user profiles. Associated parameters enable the creation of the customer feed. 

15. Blood Bank Management System

The project's goal is to develop a web app for accurately managing the blood bank. Many city blood banks now use cloud-based platforms to keep track of the blood units available or needed.  You can use AWS EC2 and AWS DynamoDB as the services to develop this application. In this project, you can create a simple UI to enable the users to view the blood units available in the blood bank, book the requirements, and book the donation to the blood bank.DynamoDB stores the data at the back-end. 

16. Orchestrate Redshift ETL using AWS Glue and Step Functions

Amazon began offering its cloud computing services in 2006. And since then, it hasn’t stopped adding exciting features to its product for its valuable customers. One such feature is the Redshift which can be used as a data warehousing tool. In this project, you will understand how to build an ETL (Extract, Transform, and Load) Big Data pipeline with the help of AWS tools and in-house featured applications for drawing relevant business insights from the data.

Data Description

The Amazon eCommerce website hosts various products from various sellers and thus has a massive dataset of its customers' reviews. This dataset is now a valuable asset for machine learning, Natural language processing, and deep learning applications . In this project, you will be working on the Amazon Customer Reviews dataset that contains product reviews written by Amazon customers between the years 1995-2015. There are about 200K+ reviews from customers from five different countries. You can download the dataset in two formats: TAV (Tab-separated values)/ Parquet (an optimized columnar binary format).

Services- Amazon Redshift, Amazon Glue, AWS Step Function, VPC, QuickSight

Language Used - Python3, SQL

Packages/Libraries - Boto3, Sys

Source Code- Orchestrate Redshift ETL using AWS Glue and Step Functions

The most effective strategy to earn a hiring manager's trust is to showcase your ability to perform the tasks they need. In the Big data industry, this strategy entails building a solid portfolio. How can you do that? Well, add a good number of projects to your Big Data portfolio. This section includes some unique industry-relevant AWS project ideas for beginners. Working on these projects will make you stand out from the rest of your competitors and help you land your dream job.

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17. Building Real-Time AWS Log Analytics Solution

Log analytics, a typical Big Data use-case, enables you to monitor application availability, detect fraud, and manage service level agreements. In this AWS project, you will create an end-to-end log analytics solution to gather, ingest, and analyze data. Once the data analysis is over, it will allow you to assess the status of production systems on AWS. Working on this real-time AWS project will allow you to explore various AWS native services such as Amazon S3, AWS IAM, AWS EC2, AWS Glue, etc.

Source Code- Building Real-Time AWS Log Analytics Solution

18. Website Monitoring using AWS Lambda and Aurora

Website Monitoring validates that the website is fully operational and that web users can navigate the site without difficulty. For this real-time AWS project, you will leverage AWS tools such as Amazon Dynamo DB, Lambda, Aurora, MySQL, and Kinesis to put together optimum solutions for website monitoring. Create an AWS EC2 instance and install Amazon Kinesis on it. Then, with Amazon Kinesis , build data analytics streams for real-time data streaming. Then, after launching AWS EC2 instances, assign the EC2 instance an Identity Access Management (IAM) role. Create Kinesis Analytics for performing log streaming on Kinesis data streams. Use AWS Lambda to load order logs into Amazon DynamoDB, and then use Kinesis Analytics to stream the data in real-time.

Source Code- Website Monitoring using AWS Lambda and Aurora

19. Build an Analytical Platform for eCommerce using AWS Services

Ecommerce analytics gathers information from all of the factors that impact a retail outlet. Analysts can then use this data to infer changes in customer behavior and online shopping trends. In this project, you will use an eCommerce dataset to develop two analytical pipelines: batch and real-time, based on logs of user purchases, product views, cart history, and the user's path on the digital platform. This project requires you to perform batch processing that entails ingesting data using S3, processing the data with Amazon Glue, and visualization using Amazon Kinesis. Use AWS QuickSight to draw relevant business insights from the data.

Source Code- Build an Analytical Platform for eCommerce using AWS Services

Github offers various projects and repositories that help students and working professionals enhance their skill set by practicing those projects. You will find several open-source projects with source code on Github that you can try your hands on. Below are a few exciting AWS project ideas for beginners that are available on Github-

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20. Hybrid Recommendation System

In this project, you will use the Yelp dataset to perform a high-level data analysis to generate hotel recommendations. The project mainly focuses on designing a hybrid system that combines content-based, collaborative-based, and social networking-based systems. The tech stack for this machine learning project includes Apache Spark, MongoDB , AWS - EC2, EMR, and Java.

Github link- Hybrid Recommendation System

21. Forest Wildfire Analytics

Wildfire prediction is an intelligent approach to preventing and minimizing wildfires. Wildfire predictions enable you to quickly analyze the source of the fire and determine the best course of action. Create a dynamic, efficient, and automatic machine learning workflow with AWS Cloud for this wildfire analytics project. Create functions with AWS Lambda and a Redshift cluster to interact with AWS Lambda and AWS Glue . Storing the input CSV file in the S3 bucket helps trigger the Lambda function. You can use the AWS Sagemaker Python SDK to prepare and train your machine learning model on the data. Use Quicksight to create wildfire data visualizations and interactive dashboards after executing queries on the data with AWS Athena and Glue crawlers.

Github link- Forest Wildfire Analytics

22. Sentiment Analysis on Real-time Twitter Data

This AWS project aims to create a system that can evaluate the sentiment of all real-time Tweets using a specified Twitter hashtag. Use a basic Python script to obtain real-time Twitter data. Put the Tweets directly into a Kinesis Firehose delivery stream with a transformation Lambda function from the script. Use Amazon Comprehend to get sentiment data and a cleaned/processed Twitter comment. Finally, an Elasticsearch domain saves the Tweet and its sentiment data, where custom charts will display real-time data.

Github link- Sentiment Analysis on Real-time Twitter Data

23. Object Detection using AWS Sagemaker

Using the TensorFlow Object Detection API and Amazon SageMaker, this existing git repository involves building, training, and deploying an EfficientDet model. It leverages TensorFlow 2 to make developing, training and deploying object detection models simple. It also features the TensorFlow 2 Detection Model Zoo, a library of pre-trained detection models that speeds up your project. You will train a Tensorflow Object Detection model to detect bees from RGB images using an example dataset from inaturalist.org . This project will show you how to use SageMaker Processing to create the TFRecords dataset and label map. You will learn how to use TF2 on Amazon SageMaker to fine-tune an EfficientDet model. Working on this project will also teach you how to use Tensorboard and the SageMaker Debugger to track your machine learning model training.  The project's final step is to deploy your model on a SageMaker Endpoint and visualize the results.

Github link- Object Detection using AWS Sagemaker

When working with specific AWS resources, Python is one of the most popular choices. One of the reasons causing this popularity is that using Python SDK 'Boto' in AWS allows for efficient development with less code. If you wish to learn more about how Python makes AWS easier to use, here are a few AWS project ideas for beginners worth exploring.

24. AWS Athena Big Data Project for Querying COVID-19 Data

This is one of the easiest AWS projects you can practice. You will learn to examine the covid-19 dataset using AWS Athena, a serverless SQL query engine. The Covid-19 database comprises Covid-related timestamps, posts, and comments. The project will teach you how to leverage Amazon Glue to create tables and offers you a chance to explore various Athena joins. In the AWS Glue Data Catalog, you will use Python to create tables using crawlers. Working on this project will also help you understand how AWS Athena pricing varies depending on the file size. Additionally, this project involves a few other services such as Amazon S3, Amazon CloudWatch , etc. AWS S3 allows you to store the dataset (CSV file) in S3 buckets for further processing, and CloudWatch keeps track of your data's log files and lets you analyze them as needed. 

Source Code- AWS Athena Big Data Project for Querying COVID-19 Data

25. Build an AWS ETL Data Pipeline in Python on YouTube Data

Cloud-based security Data Lake solutions help to generate rich analytics on data by categorizing it into multiple storage segments, such as raw, cleaned, and analytical. This project intends to organize, simplify, and analyze structured and semi-structured YouTube video data based on video genres and trending metrics securely and efficiently. It contains data (in CSV files) on the YouTube videos trending daily for several months.

Source Code- Build an AWS ETL Data Pipeline in Python on YouTube Data

26. Build a Real-Time Streaming Data Pipeline using Flink and Kinesis

Real-time data gives you the information you seek quickly and in context, allowing you to make highly informed business decisions. This AWS big data project will teach you how to use Amazon Kinesis to host an Apache Flink Python program for a real-time streaming platform. This project involves simulating real-time accident data and building a pipeline that will allow you to analyze the situation and take timely measures. Working on this project will help you better understand various services such as AWS Kinesis, Apache Flink, Grafana, and Amazon SNS.

Source Code- Build a real-time Streaming Data Pipeline using Flink and Kinesis

AWS sample project ideas listed above will introduce a broad range of capabilities you can explore with AWS services. You can also use these ideas to enhance your AWS cloud platforms and frameworks skill-set to land a top gig as a AWS cloud computing professional. Successful outcomes in these projects will inspire you to develop self-motivated projects on AWS. You can implement your ideas to build useful industrial and business apps using AWS services. You will gain experience in cloud technologies with other latest technological concepts. Artificial Intelligence and Big Data are some of the technologies with active involvement in many project ideas. You will acquire additional analytical, problem-solving, and risk resolution skills with hands-on experience by working on these AWS projects. 

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1. What are AWS projects?

Build an AWS ETL Data Pipeline in Python on YouTube Data- This AWS project entails organizing, streamlining, and analyzing structured and semi-structured YouTube video data based on video categories and trending metrics in a secure manner. Use the YouTube trending video dataset from Kaggle, which contains statistics (CSV files) on popular YouTube videos daily for several months.

AWS Snowflake Data Pipeline Example using Kinesis and Airflow- In this project, you will build a data pipeline that starts with EC2 logs and ends with Snowflake and S3 post-transformation and Airflow DAGs processing. Use two different data files (for example, customers and orders) to implement this project.

AWS Project-Website Monitoring using AWS Lambda and Aurora- This AWS project entails real-time monitoring of webpages by employing various AWS services like Lambda, Aurora MySQL, Amazon Dynamo DB, and Kinesis to monitor your website.

2. How do you create a project in AWS?

Step 1- Log in to the AWS Management Console and go to console.aws.amazon.com to access the Amazon Pinpoint console.

Step 2- It will take first-time users to a page that walks them through the platform's functions. Choose Create a project from the Get started section after giving your project a name. Existing users choose the option Create a project from the All projects page and enter a name for your project in the Project name box.

Step 3- Choose Configure next to Email on the Configure features page.

Step 4- Fill in the Email address field with the email address for user authentication (personal email address or work email address) you want to send emails. Then, select Verify.

Step 5- You will receive an email from Amazon Web Services with the subject line "Amazon Web Services – Email Address Verification Request in region RegionName," where RegionName is the name of the AWS Region in which Amazon Pinpoint is configured.

Step 7- After opening the email, click the link in the email's body.

Step 8- Head back to the Amazon Pinpoint console in your browser. Choose Save on the Setup email page.

Is AWS easy to learn?

Yes, AWS is easy to learn. Learning AWS is easy if you have a good understanding of the fundamentals of cloud computing. Referring to AWS documentation, YouTube videos, and working on hands-on real-time AWS projects are some of the best ways to learn AWS. 

3. Where can I find AWS Projects for Practice?

You will find various unique and exciting AWS projects for practice on ProjectPro , Github, etc.

4. How do I practice AWS Projects?

Setting up the AWS Account on the Free Tier is one of the best ways to practice AWS projects. Customers can use it to try out AWS services for free, up to the limits set for each service.

5. How long does it take to learn AWS?

If you put in at least 2 to 3 hours each day and have fundamental IT and networking abilities, it will take 2 to 3 months to learn AWS.

6. How do I learn AWS from scratch?

You can learn AWS from scratch with the freely-accessible AWS Training center. You can proceed further by attending AWS events, webinars, workshops, etc. You can check out Youtube tutorials and free AWS courses. Once you have gained sufficient theoretical knowledge, it's time to put them into practice. You will find some interesting industry-relevant AWS projects on ProjectPro, Github, etc.

7. How can I take up Open AWS Projects?

To take up open AWS projects, you can start by joining online communities and forums related to AWS. There, you can find open-source projects that need contributors. You can also search for GitHub repositories that use AWS services and contribute to them. Additionally, you can participate in hackathons and online coding competitions that involve AWS technologies.

8. How to build a Portfolio for AWS Projects?

To build a portfolio for AWS projects, start by identifying projects that align with your interests and skills. Build small applications that demonstrate your ability to use AWS services such as EC2, S3, and Lambda. Document your projects with code samples, screenshots, and brief descriptions. Publish your portfolio on platforms like GitHub or LinkedIn to showcase your skills to potential employers.

9. What are Some Small Projects using AWS that Will Be Good for Resume?

Here are some small projects using AWS that would be good for a resume:

Build a serverless web application using AWS Lambda and API Gateway.

Create a static website using AWS S3 and CloudFront.

Set up a continuous deployment pipeline using AWS CodePipeline and CodeDeploy.

Develop a chatbot using AWS Lex and Lambda.

Implement a database using AWS DynamoDB and Lambda.

10. What are Some Best Practices for AWS Project Development and Deployment?

Here are some best practices for AWS project development and deployment:

Use infrastructure as code to manage your AWS resources and configurations.

Implement security best practices, including least privilege access and encryption.

Test your applications thoroughly before deployment using automated testing.

Monitor your AWS resources using CloudWatch and implement automated alerting.

Use a version control system for your code and infrastructure to track changes and collaborate with your team.

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50+ AWS Projects for Beginners to Practise in 2024

In the fast-evolving landscape of cloud computing, Amazon Web Services (AWS) stands tall as a pioneer. For beginners stepping into the realm of cloud technology, embarking on hands-on projects is crucial. This blog aims to guide AWS projects for beginners through essential projects, providing a practical and immersive learning experience.

Why AWS for Beginners?

Table of Contents

AWS has emerged as the industry leader in cloud services, and acquiring AWS skills is a strategic move for any aspiring IT professional. The platform’s popularity is not only due to its robust infrastructure but also to its comprehensive free tier, which allows beginners to experiment without incurring costs. Additionally, AWS offers extensive documentation and a vibrant community, making it an ideal choice for those starting their cloud journey.

Essential Concepts for AWS Beginners

Before diving into AWS projects for beginners, it’s crucial to grasp fundamental AWS concepts. Understanding the global infrastructure of AWS, and key services such as EC2, S3, RDS, and IAM basics lays a solid foundation for beginners.

• AWS Global Infrastructure: AWS operates on a global scale, with data centers strategically located worldwide. Understanding the global infrastructure helps beginners make informed decisions about service selection based on factors like latency and compliance.
• Key AWS Services: Amazon Elastic Compute Cloud (EC2), Simple Storage Service (S3), Relational Database Service (RDS), and AWS Lambda are cornerstones of AWS. Familiarizing oneself with these services is essential for project success.
• IAM (Identity and Access Management): Security is paramount in the cloud. IAM allows users to control access to AWS services securely. Learning IAM basics ensures beginners can manage user identities, roles, and permissions effectively.

50+ AWS Projects for Beginners

• Launching a Virtual Server (EC2)
• Hosting a Static Website (S3)
• Setting up a Relational Database (RDS)
• Building a Serverless Function (Lambda)
• Creating a Virtual Private Cloud (VPC)
• Configuring CloudFront for Content Delivery
• Implementing Cross-Region Replication (S3)
• Setting Up Multi-Factor Authentication (IAM)
• Creating an AWS Simple Notification Service (SNS)
• Deploying a Docker Container on ECS
• Setting Up an API Gateway
• Implementing auto-scaling for EC2 Instances
• Configuring AWS CloudTrail for Logging
• Creating an AWS Elastic Beanstalk Application
• Setting Up AWS CloudFormation
• Implementing Serverless RESTful API (API Gateway + Lambda)
• Configuring AWS Identity Federation
• Integrating AWS Cognito for User Authentication
• Implementing AWS Step Functions for Workflow Automation
• Configuring AWS Key Management Service (KMS)
• Setting Up AWS Direct Connect
• Implementing AWS CloudWatch Alarms
• Configuring AWS Elastic Load Balancing
• Setting Up Amazon Simple Queue Service (SQS)
• Deploying a Machine Learning Model on SageMaker
• Creating a Data Lake with AWS Glue
• Setting Up AWS Secrets Manager
• Implementing AWS X-Ray for Application Tracing
• Configuring AWS Certificate Manager for SSL
• Setting Up AWS CodePipeline for CI/CD
• Implementing AWS Transit Gateway
• Creating an Alexa Skill with AWS Lambda
• Configuring AWS DMS for Database Migration
• Implementing Amazon Polly for Text-to-Speech
• Setting Up AWS WAF for Web Application Firewall
• Configuring AWS Storage Gateway
• Creating an AWS Cloud9 Development Environment
• Implementing AWS Budgets for Cost Management
• Configuring AWS Elastic File System (EFS)
• Setting Up AWS App Mesh for Microservices
• Implementing AWS App Runner for Containerized Applications
• Configuring AWS Elemental MediaConvert for Video Processing
• Creating an AWS Data Pipeline
• Setting Up AWS CodeBuild for Continuous Integration
• Implementing Amazon Aurora Serverless
• Configuring AWS AppConfig for Application Configuration
• Setting Up AWS OpsWorks for Configuration Management
• Implementing AWS Device Farm for Mobile App Testing
• Configuring AWS Backup for Data Protection
• Creating a Serverless Chatbot with Amazon Lex and Lambda

Tips for Successful Completion of AWS Projects

Embarking on AWS projects for beginners requires more than just following step-by-step guides. To enhance the learning experience:

• Reading AWS Documentation: AWS provides comprehensive documentation for all its services. Regularly referring to the documentation enhances understanding and builds self-reliance.
• Participating in AWS Forums and Communities: Engaging with the AWS community through forums and online groups provides opportunities to seek advice, share experiences, and stay updated on the latest developments.
• Exploring Additional Resources: Beyond the projects outlined here, exploring tutorials, video courses, and other resources helps deepen one’s understanding of AWS.

Best Resources to Practice AWS Projects

Practicing AWS projects for beginners is crucial for gaining hands-on experience and confidence in working with cloud services. Here are some of the best resources to practice AWS projects:

AWS Free Tier

Utilize the AWS Free Tier, which provides a limited amount of AWS resources for free. This allows you to experiment and practice without incurring charges.

AWS Documentation

The official AWS documentation is a comprehensive resource that provides detailed guides, tutorials, and examples for each AWS service. It’s an invaluable reference while working on projects.

AWS offers self-paced labs covering various topics and services. These labs provide step-by-step instructions and a sandbox environment for hands-on practice. You can find them on the AWS Training and Certification website.

AWS Training and Certification

AWS provides a range of training courses, both free and paid, covering different skill levels and specializations. These courses often include practical exercises and labs. Aws application development services teams can create custom training programs tailored to your needs.

AWS GitHub Repositories

Explore AWS’s official GitHub repositories for sample code, templates, and projects. This is a great way to learn from real-world examples and best practices.

A Cloud Guru and Linux Academy

These online learning platforms offer AWS-focused courses and labs. They provide a structured learning path with hands-on exercises and projects.

CloudFormation Templates

Practice using AWS CloudFormation by working with templates available in the AWS CloudFormation Sample Templates GitHub repository. This helps you understand infrastructure as code (IaC) principles.

AWS Workshops

AWS regularly hosts workshops, either online or at events. These workshops cover a variety of AWS topics and often include hands-on labs.

AWS Community Builders

Join the AWS Community Builders program, a community-driven initiative by AWS. It provides resources, mentorship, and opportunities to collaborate on projects with other community members.

AWS Blogs and Webinars

Stay updated with the latest AWS developments by reading the AWS blogs and attending webinars. These resources often showcase real-world use cases and projects.

YouTube Tutorials

Numerous AWS experts and trainers share tutorials and walkthroughs on YouTube. Follow channels that focus on AWS and provide practical demonstrations.

Remember to start with beginner-level projects and gradually progress to more complex scenarios as you gain confidence. Regular, hands-on practice is key to mastering AWS services and concepts.

Challenges and Solutions: AWS Projects For Beginners

Common challenges faced by beginners.

• Security Configuration: Understanding and configuring security settings can be challenging for beginners.
• Resource Management: Managing resources efficiently and avoiding unnecessary costs can be daunting.
• Troubleshooting: Identifying and resolving issues, especially in a cloud environment, can be complex.

Solutions and Troubleshooting Tips

• Start with Simple IAM Policies: Gradually progress from basic IAM policies to more complex configurations.
• Regularly Monitor Resources: Utilize AWS CloudWatch and other monitoring tools to keep track of resource usage.
• Utilize AWS Support and Forums: Leverage AWS support plans and community forums for assistance when facing challenges.

Embarking on AWS projects for beginners is not just about learning a set of tools; it’s a journey into the heart of cloud computing . The outlined projects provide a structured path for beginners to gain hands-on experience with key AWS services. As you navigate through these projects, remember that the cloud is dynamic, and continuous learning is the key to staying at the forefront of this ever-evolving technology. 

AWS offers a vast ecosystem of services waiting to be explored, and these initial projects serve as a launchpad for your exciting journey into the world of cloud computing. So, dive in, experiment fearlessly, and let the projects pave the way for your mastery of AWS.

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Top AWS Projects for Beginners to Advanced [With Source Code]

Introduction, what is aws, aws project ideas:, best aws projects for beginners:, intermediate aws projects with source code, advanced aws projects, aws projects: why are they so important, additional resources.

Various technologies have revolutionized different aspects of our lives today, such as how we work, run our businesses, interact with each other, etc and one such technology is cloud computing. Cloud Computing is one of the most flourishing and in-demand technology. Businesses and organizations are transforming their operations to take advantage of this new technology.

So, let us begin with a quick overview of AWS.

Cloud service is not a new term for us as we all are using smartphones nowadays. One such cloud service is AWS which stands for Amazon Web Services. AWS provides a web-based interface through which we can create resources and deploy our applications. It a is comprehensive and broadly adopted cloud platform developed by Amazon that offers more than 200 services from data centers spread across the globe. With the help of AWS, there is no need to maintain physical data centers and servers and data can be accessed from anywhere across the world. Several customers, including large organizations such as Adobe, Twitter, Netflix, Facebook, etc, and government agencies, rely on AWS to make their businesses more productive.

Confused about your next job?

This cloud platform is a combination of Infrastructure as a service (IaaS), Platform as a Service (PaaS), and packaged Software as a Service (SaaS) offerings. 

What does it allow you to do?

In simple words AWS allows you to do the following things-

• AWS allows you to run web and application servers in the cloud to easily host dynamic websites.
• Aws securely stores all your files on its cloud server so you can access them from anywhere in the world.
• Information is stored in managed databases such as MySQL, PostgreSQL, Oracle, or SQL Server.
• AWS delivers static as well as dynamic files around the world using a  CDN i.e Content Delivery Network.
• Aws allows you to send bulk emails to your customers quickly.

Now if you are looking for some good project ideas on AWS then in this article you will find projects on AWS of various sectors and skill levels along with their source code link so you can choose according to your interests.

1. Deploy a Windows Virtual Machine

Objective: To deploy Windows Virtual Machine without any security violations  using a popular CMS, like Magento, WordPress, etc

If you want to become a cloud computing professional in AWS, start working on simple projects. And one of the simplest beginner-friendly projects to get started with AWS is deploying a Windows Virtual Machine(Windows Virtual machines are emulations of computer systems. A virtual machine, according to a more sophisticated definition, represents an abstraction of a physical device’s resources. If many virtual machines are present within a network then all of them work independently). You can deploy Windows VM in AWS, and for this purpose, you can use Amazon Lightsail as the web service which we have discussed earlier.

Virtual machines are useful in a wide range of fields. As a developer, virtual machines come in quite handy because they allow you to run multiple operating systems on a single machine and they are also useful for enhancing the efficiency of an operation

Getting familiar with VMs will help you in becoming a proficient engineer and is quite a necessary skill.

 After you have created the VM, you can use Lightsail to connect with an RDP client.

Source Code Link

2. Migrate a Git Repository on AWS

Objective: To migrate an existing Git repository using AWS CodeCommit.

In this project you will learn how to migrate an existing Git repository using AWS CodeCommit.AWS CodeCommit is a platform for hosting Git-based repositories. Depending on your needs, you can migrate either an existing Git repository or a locally stored unversioned project.

Before migrating a repository to CodeCommit, you must create and configure an IAM user for CodeCommit. And for managing CodeCommit AWS CLI should also be installed. AWS CLI offers flexibility when working with Git at the command line or terminal, even though most CodeCommit tasks can be performed without it.

There are many benefits of hosting your source code with CodeCommit such as its fully-managed experience, high availability, security.

3. Rapid Document Conversion 

Objective: The goal is to quickly and accurately convert the document to the desired format as selected by the user.

Data is everywhere around us and therefore we feel the need to convert this data into many formats from time to time. If you are a student or a working professional you must have come across the need to convert a document to pdf or excel to a word document or any other format. That’s what AWS Lambda is for.AWS Lambda allows us to develop an application that can convert documents from one format to the other very easily and conveniently. 

The CloudConvert API can be use to automatically convert all files, added to a specific S3 bucket. 

Here is how the process works:

• User will upload their Office Document to the S3 bucket.
• Now, the Lambda function will be triggered by the S3 bucket with uploaded files details.
• Lambda function will convert documents with LibreOffice.
• Lambda function will upload PDF to S3 Bucket after conversion.
• After uploading you can also write additional code to update details in the Database.

4. Build a Website Using AWS Lightsail

Objective : To create a secure, reliable, usable, and readily available website using AWS.

You will need to use Amazon Lightsail, which is a virtual private server that can be used to create numerous websites.

Amazon Lightsail is a free AWS cloud service platform that provides you with the required resources to build an application. Completing this project will definitely make you familiar with this software

You will need to sign up for the AWS platform and then access Lightsail. You can create any type of website such as a website that displays the results of students in a University. The main reason for using AWS Lightsail is that It will enable you to utilize the optimum number of resources as per the need and also it comes with pre-configured leading CMSs such as WordPress, Magento, Redmine, etc. By using a CMS, it’s easier for us to deploy a website. Using a CMS will allow you to quickly get a new website up and running if you are a beginner or don’t want to write code from scratch.

When using AWS Lightsail as a virtual private server, you can use AWS EC2 or AWS Lambda. It comes pre-configured with several options for web development and provides SSD-based storage.

5. Create an Online Store

Objective: Creating an e-commerce-like platform that can handle all the tasks such  as requests, payments, etc by itself

AWS offers a highly secured and low-cost solution e-commerce platform to all small and large business organizations. For building e-commerce like platform, we need to use the  AWS Marketplace service. AWS Marketplace enables organizations to discover, procure, entitle, provide, and govern third-party software easily.

To find free, open-source, and fully customizable e-commerce stores in AWS Marketplace one must search e-commerce in the search menu.AWS also provides auto-scaling services which help the e-commerce website grow and shrink on-demand. To deliver the website to the customers without any delay Amazon CloudFront is used through which all the requests are routed to the nearest edge locations.

6. Build a Simple Android App

Objective : To create a simple Android application using Amazon AWS Amplify.

Suppose that you want to build native Android app to display a list of student results . You want to set up APIs to allow listing, creating, and storing student data and you also want user authentication but you don’t want to manage the backend then AWS amplify will cater to all your needs. 

The Amplify Android library is AWS’ preferred mechanism for interacting with AWS services from an Android device. As it provides a high-level interface to perform different categories of cloud operations. 

To get started with the project, you will need to download Java JDK as well as Android Studio into your system. 

 In this project, you will learn:

• How to add a GraphQL API that’s backed by AWS AppSync.
• How to manage a serverless cloud backend using the command line interface Amplify. 
• How to enable user authentication through Amazon Cognito.
• How to enable querying and displaying the list of student results in a RecyclerView.
• How to enable adding new student data and persisting data in the backend.

This project will help you gain a deeper understanding of the AWS services required to build and launch Android apps.

7. Create Attendance Automation

Objective: We will be creating a website for attendance automation using services such as AWS cognito, lightsail, amazon rekognition, etc .

For authentication purpose, we will use AWS cognito so that students can log in on the website using their roll numbers.

Further, Amazon virtual cloud server (LightSail) will be used which provides a free static IP address to host the website. Select an OS from the list of options and build the website using the MEAN stack.Following successful login, the user will have the option to open the device camera and scan their identity card on the dashboard.

The Amazon Rekognition service which can store information about detected faces in server-side containers known as collections will be used to read and scan the image of students on the identity card. With this service, images are analyzed using a deep learning algorithm and are highly scalable. But first we have to manually add faces of students in that collection in one of the AWS regions in our account.

As soon as the card is scanned, the details of students are saved in DynamoDB.

8. Create and Deploy a React Web Application

Objective(s) : To build a full-stack React web application.

ReactJS is one of the most popular javascript libraries trending nowadays for building UI of the web as well as a mobile application. React can be used to create single-page applications very easily.

By building this project you can get a good experience of full-stack development as well as AWS cloud computing professional.

For building full-stack application AWS amplify is used that allows us to build, deploy, and host serverless web applications.

There will be several steps that you have to follow to complete this project. Firstly host the React app on AWS Amplify. Secondly, use Amazon Cognito for authentication. After building the frontend using react you have to create APIs to send data to the frontend. GraphQL can be used to develop a RESTful API for your application.

9. Create a Traffic Monitoring Tool

Objective: Creating a Framework for Smart Traffic Control using AWS IOT

Amazon Web Services offers the most comprehensive portfolio for building scalable, extensible, and NoOps systems. Another benefit of AWS is that it enables the architecture to bridge the gap between real and simulated paradigms by interacting with virtual as well as physical devices. AWS IoT is a platform that allows us to securely connect devices to relay information to and from the AWS platform using Message Queue Telemetry Transport(MQTT). therefore through IoT Core service, cameras can be connected to applications without requiring server management.

A connection protocol will be chosen among the available options. It supports

• MQTT (Message Queuing and Telemetry Transport),
• HTTPS (Hypertext Transfer Protocol – Secure),
• MQTT over WSS (WebSockets Secure), and
• LoRaWAN (Low-power Long-range Wide-area Network).

Another service by Amazon namely the Amazon Kinesis service will be used to collect and analyze all the real-time traffic videos. As data is received, this service responds instantly, instead of waiting for full data to arrive.

10. Create a Chatbot With Amazon Lex

Objective : The project’s objective is to create a chatbot that provides instant replies to the messages sent by the users

A chatbot is an application that conducts a conversation automatically without the presence of a person on one end. They allow companies to enhance customer experience and reduce costs of hiring a person to communicate with users. There are many types of chatbots available right now, and they all are developed for different purposes.

Chatbots are implemented with the help of AI i.e Artificial Intelligence. During the process of building a chatbot, you will be able to apply artificial intelligence concepts in real-world situations.

Amazon, Flipkart and many other e-commerce apps have chatbots installed to reply to users’ queries instantly.Another good example is telegram which you all must be aware about. You can use Amazon Lex which is an AWS service which helps in development of voice and text-based conversational interfaces such as chatbots… You can also use Lex to experience one-click deployment and then add your developed application to the desired platform. For the chatbots created using Lex platform independence is also essential. 

You will need to build a chatbot for this project that will generate automated responses to users’ questions.

To ensure that your chatbot works correctly, test it by starting conversations with it from the users’ perspective. As you configure the chatbot, make sure that the conversations relate to the intent that you chose.

11. Orchestrate Redshift ETL using AWS Glue and Step Functions

Objective: In this project, you will learn how to build an ETL (Extract, Transform, and Load) Big Data pipeline with the help of AWS’s in-house featured applications for drawing relevant business insights from the available data.

Amazon Redshift is fully managed petabyte-scale cloud data warehouse service. Using Redshift Spectrum, you can directly query structured and unstructured data in Amazon S3 without deploying them into the Redshift cluster. In Redshift, we can run complex, analytic queries against structured data and semi-structured data, while using sophisticated query optimization, columnar storage on high-performance storage like SSD, and massively parallel query execution. It is an OLAP solution that can store petabytes of data without owning any infrastructure (PaaS).

Data Description – The Amazon eCommerce website hosts a wide range of products from a large number of sellers and thus has a vast database of customer reviews. Now this dataset can be used for machine learning, natural language processing, deep learning, and other applications. In this project, you will work with the Amazon Customer Reviews dataset that contains product reviews written by Amazon customers. There are more than 200K reviews from customers in five different countries. The dataset can be downloaded in two formats: TAV (Tab-separated values)/ Parquet (an optimized columnar binary format).

12. Alexa, Who’s At The Door?

Objective: An Amazon Alexa and Raspberry Pi project that used AWS lambda to allow users to know who exactly is knocking at their door using facial recognition.

Alexa, Who’s At The Door? Is an Amazon Alexa skill set that uses the Raspberry Pi and Firebase, as well as a facial recognition API, to let users know who is at their door. Alexa sends a command to the Raspberry Pi to take a picture of visitor’s face using the camera module. Kairos, a facial recognition algorithm, is then used to identify whether the face is recognized, unknown, or not present at all.

For “Who’s at the Door?”, as a connection between local and cloud communication, Firebase is used. Both the lambda function as well as the Raspberry Pi are listening to the firebase DB (the lambda function gets triggered by Alexa Voice Services and then it listens to firebase).

According to a survey by Accenture in 2018, developers consider Amazon Web Services the most future-looking platform. Participants in the survey also rated AWS as a highly developer-friendly platform.

Here are some of the main characteristics of AWS that will justify why are they considered important:

• The AWS Auto Scaling feature allows developers to automatically adjust resources as demand changes.
• The pay-as-you-go model makes it extremely budget-friendly and payment is on par with services availed
• Services are provided immediately on demand and there is no visible delay when more servers are deployed
• Certain AWS resources can be accessed for free with the AWS Free Tier account.
• AWS employs advanced security measures to ensure that user data remains protected.

So in this article, we discussed about various projects which can be built using AWS. Cloud computing is in great demand today. If you are interested in working with any of the cloud technologies, keep in mind that there will be problems in implementation, but things will become clearer as you practice more and more. For practice, you will get a lot of projects available on Github to try on too, and also AWS has a very good set of documentation. Apart from this, online communities have a bunch of experienced professionals to help.

Q.1) How do I learn AWS from scratch? A: AWS (Amazon Web Services) is overwhelming and If you are new to AWS you’ll know the feeling of being lost and not knowing where to start so start by taking small steps at a time and begin with simpler things first, then move on the advanced topics.

There are three things you should focus on when learning AWS:

• Learn core AWS services first
• Prioritize hands-on learning
• Structure your learning

For hands-on learning here are some steps you can follow:

• First, you have to create an AWS account
• Then enroll in any online course that you find relevant according to your needs.
• Explore the guides or blogs provided by AWS which contains CF templates as well.
• Try building a  small application, that also you can get from AWS blogs.
• Finally, Experiment In this way, you can have a good command on AWS.

Q.2) Is AWS easy? A: Learning AWS can be quick and easy and can take as little as a few days up to a few months depending on your past experience. If you’ve already worked with similar technologies for example systems administration or with other hosting and cloud services then you might find AWS easier to learn. To learn AWS, however, no previous experience, special knowledge, or coding experience is necessary.

So, if you work hard, get hands-on experience, and Network with other people you will learn AWS easily.

Q.3) Is AWS free to use? A: The short answer is, no Amazon Web Services isn’t free to use. However, AWS has a free offering for 12 months. Also, there are a number of services that are always free. You can test out various products before making a big commitment using the free trial versions of many of their services. Customers can use the free 12-months products (up to a specific level of usage) for one year from the date the account was created if they are new trial customers. When your free tier expires or if your application use exceeds the free tier limits then you will start paying standard, pay-as-you-go service rates.

Q.4) How long does it take to learn AWS? A: You can learn the basics of AWS in just a few weeks but if you want to be professional in AWS  then there are  four levels depending on various levels of learning or expertise:

-In order to become an AWS Cloud practitioner, it takes around one month to learn the basics of cloud computing, setting up an AWS account, using the AWS management console, and working with S3 services.

-For an AWS Architect, it takes around 1.5 months to learn Identity Access Management, EC2, Database on AWS, Route53, Network Address Translation, HA Architecture, etc.

-For an AWS Developer, it takes around 2-3 months to learn AWS SDK, Access Management, Integrate AWS applications by using AWS Lambda, AWS API Gateway, Amazon SNS, etc.

-For an AWS Operations level, it takes around 3-4 months to learn basic concepts like managing AWS instances and permissions, securing AWS, troubleshooting problems, and configuring ECS.

• AWS Interview Questions
• AWS vs Azure
• AWS Projects

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10 Best AWS Projects to Better your Learning

Ever since its inception in 2006, Amazon Web Services has been the uncontested leader in the cloud computing niche. AWS has more than 30% of the entire cloud computing market , which is even more than the combined market share of Microsoft Azure and Google Cloud, the no.2 and no.3 among the cloud computing providers.

Amazon Web Services is the digital services offered by the FAANG firm, Amazon. It provides on-demand cloud computing services to individuals and organizations of all sizes and even to governments. The pricing follows a flexible pay-as-you-go basis.

Due to AWS’s immense popularity, it is only natural that its skills are in high demand. As such, learning the cloud computing platform can lead to a lucrative career. Here we’ve compiled a list of the ten best AWS projects to help you learn and advance in AWS, plus followed by a section detailing why developers shower AWS with so much love. So, let’s start.

• 10 Best AWS Projects

1: Build a Website Using AWS Lightsail

Expected Time to Complete - 20 to 30 minutes Level - Beginner Objective(s)

• To build a simple website using a popular CMS, like WordPress.

If you want to become a cloud computing professional in AWS, start working on simple projects. The website you need to build in this project will require you to use Amazon Lightsail, a virtual private server from AWS.

In this project, begin with signing up for the AWS platform and then access the Lightsail service. The main reason for using AWS Lightsail to create a website is that it comes pre-configured with leading CMSs, including WordPress, Magento, Joomla, and Redmine.

By using a CMS, it will be easier for you to create and deploy a website. If you are new to web development or don’t want to create a website by writing code from scratch, it will be better to use a CMS to get the website up and running in no time.

If you are interested in building a website without using a CMS, Lightsail virtual servers are highly suitable. You get the flexibility to choose from a wide range of operating systems for your virtual server along with support for a wide range of development technologies, including Node.js, LAMP stack, MEAN stack, Django, and Nginx .

Reference Free Projects @GitHub:

• project-website-template
• Social Stream: a framework for building social network websites
• HTML KickStart

2: Deploy a Virtual Linux/Windows Machine

• To launch virtual Linux and Windows machines separately with Amazon Lightsail.

One of the most important things you should know as a cloud computing professional is configuring and launching a virtual machine.

This project aims to launch a Windows virtual machine and a Linux virtual machine by creating two distinct instances. As this project is one of the simplest AWS projects out there, you will be able to complete it with relative ease.

To get started with this AWS project, access the Amazon Lightsail service after signing up for an AWS account. Lightsail allows you to create an instance and configure it as per your preferences.

While configuring the instance, you will be required to choose one of the two platforms offered by it, i.e., Windows and Linux/Unix. Next, you would be prompted to choose the OS for your virtual machine. While the process for launching the Windows virtual machine and Linux virtual machine is the same, it would be great to create separate instances for both.

The biggest advantage of virtual machines is that you can run multiple operating systems on a single machine using them, which comes quite handy as a developer.

• VMware Cloud on AWS Integration Examples
• Deploy an application to any Cloud VM with Terraform, Docker & cloud-init

3: Build a Serverless Web Application

Expected Time to Complete - 4 to 6 hours Level - Intermediate Objective(s)

• To create a basic serverless web app using various AWS services.

Web applications are highly popular as they can integrate advanced features and deliver a great user experience. Also, a serverless web application handles the back-end of the application effortless for the app developers.

This project aims at building a serverless web application with AWS. The biggest benefit you will get working on this project is that you will become familiar with the AWS platform’s potential.

For accomplishing the project, you should have knowledge of HTML, CSS, and Javascript for creating the web resources for your application.

The project will help you get familiar with several AWS products and services, namely AWS Amplify, Amazon Cognito, Amazon API Gateway, AWS Lambda, and Amazon DynamoDB.

We recommend you choose a simple web application like a to-do list app for this project as this will make it easier for you to understand the process of building and deploying a serverless web app on AWS.

Within the project, you will use AWS Amplify to host your app’s static web resources, while Amazon Cognito will help you with user authentication and management. You will leverage RESTful APIs built using AWS Lambda and API Gateway for the back-end of the app. All the app data handled using API calls will be stored and managed with DynamoDB.

• AWS -cognito-apigw-angular-auth (Also uses CSS, HTML, JavaScript, and TypeScript.)
• Serverless Web Application with AppSync Workshop (Also uses JavaScript.)
• Happy Path - Building flexible serverless backends for web apps (Also uses HTML, JavaScript, and Vue.)
• Serverless React Web App Example

4: Create and Deploy a React Web Application

Expected Time to Complete - 3 to 5 hours Level - Intermediate Objective(s)

• To build a full-stack React web application.

React is one of the most popular Javascript libraries  used for building the UI of both web and mobile applications. The front-end development technology is developed and maintained by Facebook, which is another reason for its widespread popularity.

By working on this project, you will develop your skills as a React developer and AWS cloud computing professional.

The project requires you to create a full-stack React application by making use of AWS Amplify. It’s important to know that AWS Amplify allows you to build, deploy, and host serverless web applications.

There will be several steps that you have to follow to complete this project. First, host the React app on AWS Amplify.Next, integrate the authentication to the app using Amazon Cognito.

Once the front-end and authentication part is done, create appropriate APIs to enable the app to add, read, modify, and delete data. You can use GraphQL to develop RESTful API for your application.

• Tinode Web (Uses CSS, HTML, and JavaScript.)
• Topcoder Community App (Uses JavaScript, SCSS, TypeScript, etc.)
• webapp (Uses CSS, HTML, and JavaScript)

Related Course

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5 - Build a Content Recommendation System

• To build a content recommendation system using Amazon SageMaker.

If you are interested in artificial intelligence (AI) and machine learning (ML) , developing a content recommendation system is what you should consider seriously. By working on this project, you will learn how Amazon SageMaker builds, trains, and deploys ML models.

The content recommendation system create within this project will require you to use the k-Nearest Neighbours Algorithm provided by Amazon SageMaker. You can use the algorithm to develop a model that will enable the content recommendation system to provide meaningful suggestions.

To make sure that you complete this project without facing any significant challenges, divide it into multiple phases. First set up the environment with the Amazon SageMaker Notebook instance and prepare the dataset to be used. In the later phases, train and deploy the topic model first and then the content recommendation model.

After developing the content recommendation system, test it and observe if its suggestions are reliable.

• Basic Recommender System (Also uses Batchfile, Python, and Shell.)
• EC2-AWS-AND-SHELL (Uses Shell.)
• Hybrid-Recommendation-System-for-Yelp

6: Big Data Analysis Using Apache Hadoop

Expected Time to Complete - 2 to 4 hours Level - Intermediate Objective(s)

• To deploy a Hadoop cluster and process a vast amount of sample data using the Hive script.

Big Data analytics is one of the professional skills that are high in demand. This project will help you get familiar with Amazon EMR, which helps process huge amounts of data using different tools. The AWS project aims to process an extensive amount of sample data using Apache Hadoop and HiveQL.

To get started with the project, the first s set up Amazon EMR to launch an Amazon EMR cluster. It is better to put some time into understanding the EMR workflow to accomplish the project faster.

Once the Amazon EMR cluster is set up, use the HiveQL script to process the large quantities of data stored in the Amazon S3 bucket. The resulting dataset needs to be loaded to an output bucket on Amazon S3, from where you will be able to download the dataset to your local machine.

• Flamingo (Uses CoffeeScript, CSS, HTML, GAP, Java, and JavaScript.)
• Big Data Analysis and Recommender System for Amazon
• Big-Data-Analysis (Uses Java, Scala, and Shell.)

7: Create a Chatbot With Amazon Lex

Expected Time to Complete - 3-5 hours Level - Advanced Objective(s)

• To build and deploy a chatbot using Amazon Lex.

For anyone interested in working in the field of artificial intelligence, this project is highly recommended. During building a chatbot, you will be able to implement various artificial intelligence concepts and see how they are used in real-world applications.

To build a chatbot, use Amazon Lex, an AWS service available specifically for the development of voice and text-based conversational interfaces.

The chatbot that you need to build in this project should generate automated responses for users’ queries.

While configuring a chatbot, pay special attention while adding the intents, making it possible to decide the invocation phrases.

To ensure that your chatbot works fine, test it by starting conversations with it from its intended users’ perspective. Make sure that the conversations are around the intent that you selected for the chatbot while configuring it.

The best thing about developing chatbots with Amazon Lex is that you can easily deploy them on different platforms. Also, it’s quite convenient to train the chatbot by providing relevant phrases.

• Sample Amazon Lex Web Interface (Also uses CSS, HTML, JS, Makefile, Python, Shell, and Vue.)
• Amazon-lex--customer service-workshop (Also uses JavaScript and Makefile.)
• Amazon Lex .NET Core Chatbot (Also uses C#, CSS, HTML, JS, Shell, Ruby, and more.)
• AWS -textract-comprehend-lex-chatbot (Uses Python.)

8: Create or Migrate a Git Repository on AWS

Expected Time to Complete - 1-2 hours Level - Beginner Objective(s)

• To use AWS CodeCommit to create a private Git repository or migrate an existing Git repository.

Version control systems are of extreme importance for developers because they make it possible to streamline the overall development process. Version control is essential for both individuals and teams to review code before committing it.

Now, you may be aware that Git is among the most popular version control software tools out there. This project requires to use AWS CodeCommit, which is a platform for hosting Git-based repositories.

In this project, you need to either migrate an existing Git repository to CodeCommit or host an unversioned project stored locally on your machine. You need to create a private Git repository using AWS CodeCommit, where you will host the code.

Before you jump in and start working on this project, you need some things beforehand. These include an AWS account and an existing Git repository or a local project. Also, experience working with Git would be a plus for you and make it easier to understand and complete it.

• GitHub Link Card Creater (Uses Go.)
• Rotate AWS Access token stored in Github Repository secrets (Uses Dockerfile and Python.)
• GitHub -s3 (Uses Shell.)

9: Launch a Drupal Website

• To set up a Drupal blog (website) and maintain all the website data with Amazon RDS.

It is another popular AWS project related to website development that you can add to your portfolio. In this AWS project, you will deploy and launch a website powered by Drupal. Being one of the most popular content management systems (CMS), Drupal makes it extremely easy to create and manage complex websites.

For storing and handling the Drupal website’s data, use a relational database, which you can set up using Amazon RDS. Get yourself familiar with the advantages of the cloud relational database offered by Amazon RDS, such as the ability to scale up easily with the increase in website traffic.

To launch the Drupal website, create an instance on Amazon EC2. Also, configure both the Drupal website and RDS database to make sure that the website launches and works without any issue.

• Public-cloud formation-templates
• Deploy Drupal Website Docker Containers on AWS ECS (Also uses Dockerfile, Groovy, HCL, PHP, and Shell.)
• ansible-AWS_dolibarr_drupal (Uses Shell.)

10: Build a Simple Android App

To create a simple Android application using Amazon AWS Amplify.

The demand for Android developers is quite high and is one of the most lucrative careers for computer science students. You can make yourself more valuable as an Android developer by learning to develop Android apps using cloud-based tools and services provided by Amazon AWS.

This project will help you get hands-on experience building a basic Android app using AWS Amplify. While working on this project, you will learn various steps essential for creating and deploying an app with Amazon AWS.

You will learn to manage a serverless cloud backend using the command line interface of AWS Amplify. Also, you will have to enable the authentication feature in the app using Amazon Cognito. One more key thing you will be doing within this project is to add API and database for the app using GraphQL.

Overall, this project will enhance your knowledge about the AWS services required for building and launching Android apps. Also, by completing this project, you will be able to level yourself as a cloud computing professional.

• AWS Device Farm Sample App for Android (Uses Java.)
• AWS AppSync SDK for Android (Uses Groovy, Kotlin, and Java.)
• amplify-android (Uses Java and Kotlin.)
• Why is Developers Love Working with AWS?

Many reasons tech professionals trust AWS as their reliable partner are the most important being the cloud computing industry’s market leader.

According to a 2018 survey conducted by Accenture , developers consider AWS the most future-looking platform. Also, developers who participated in the survey perceived AWS as a highly developer-friendly platform.

Here are some of the main characteristics of AWS that will justify it is highly popular among the devs:

• AWS Auto Scaling feature allows developers to automate the resources required with the change in demand.
• Employs advanced security measures to ensure complete user data protection.
• The pay-as-you-go model makes it extremely budget-friendly.
• The AWS Free Tier account gives access to certain AWS resources for free.

What are your reasons to prefer AWS? Let us know in the comments section below.

AWS has been a leader in the cloud computing space, and there are no signs of it stepping down from the designation anytime soon. So, treading on the learning AWS path is a fruitful decision but requires determination, the will to do hard work, and passion for trying repeatedly.

The AWS projects mentioned in this article will help you advance with cloud computing technology and make it a beneficial endeavor.

Stuck somewhere? Let us help by dropping your comments down below. You can also share which AWS project(s) you find the most helpful/useless here.

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Gaurav was one of the earliest software developers at SlideShare-LinkedIn which was followed by working for companies like Naukri.com, Educomp, Tata Institute of Fundamental Research etc. He is a techie not only by profession but also my passion and believes that going online is the future of education.

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10+ AWS Project Ideas of 2024 with Source Code [All Levels]

Home Blog Cloud Computing 10+ AWS Project Ideas of 2024 with Source Code [All Levels]

AWS is one of the topmost cloud platforms that allows us to remotely provision and manage computing resources and applications. It is popular and holds the largest market share because of its affordable and easy-to-use services. One of the reasons why cloud computing got famous worldwide is its simplicity to provision and manage computing resources. To help professionals learn cloud computing, create AWS projects, and become job-ready, we provide various Cloud Computing training courses .  

As there are numerous opportunities available in cloud computing, young professionals are seeking to learn AWS. Nowadays, AWS has become a viable choice for professionals and organizations that want to develop highly scalable solutions at a low cost. If you want to gain practical experience that can be added to your profile, working on AWS projects is a great way to achieve your goal. In this blog, we will show some interesting AWS project ideas for all professionals, including beginners, intermediate, and advanced.

Why is Learning AWS Important?

AWS provides a flexible solution to emerging and existing businesses that want to minimize the costs of their IT infrastructure without investing in maintenance and capital expenditure. With AWS, they can simply use computing resources whenever they want and can save a lot. Over 95% of new digital workloads will be implemented on the cloud by 2025, according to Gartner's prediction.

You should consider learning AWS for multiple reasons:

• It offers many useful and easy-to-use tools and services at an affordable price.
• You can provision any sort of applications or servers on AWS as its infrastructure is highly scalable and reliable to handle workloads of all types.
• AWS dominates the market and has a large client base, making it a highly sought-after skill these days.

By acquiring this skill, you can be in demand and stay up-to-date with the current industry trends. Top organizations like Adobe, Netflix, Facebook, and Twitter use AWS for providing their services, making it a viable choice for young professionals. Learning AWS can open the door to an ample number of great opportunities in India as well as abroad. As a beginner, start with the AWS Practitioner Certification to get familiar with AWS services.

Why You Should Work on AWS Projects?

In this competitive market, it is difficult for professionals who have just a theoretical understanding of AWS to get a job. How can AWS cloud projects help? Well, if you work on a variety of AWS real-time projects, you will understand how to use AWS services in real time and get familiar with the issues that arise while working on the platform.

You can learn how to build scalable and reliable applications, manage infrastructure using automation tools, and create efficient solutions that are cost-effective. Having AWS real-time project examples on your resume can help you get shortlisted and even hired with significantly higher chances. Moreover, you can identify the weak areas where you need to improve, while working on these projects. This would help you strengthen your AWS skills and become an expert.

Top AWS Project Ideas for Beginners

Are you an aspiring AWS professional looking for a smooth transition to AWS? If yes, then this will help you in getting your dream job. Students or professionals who are new to AWS can get started with AWS projects for beginners. Final-year students can take up these AWS real-time projects for practice. Some suitable AWS projects for final-year students include:

1. Create a Website on AWS h3+

What could be better than creating a website to get started? Creating a website can be a simple AWS project for students to start experimenting with the AWS platform and services. You can use the Amazon Lightsail service to create a website on the platform. Amazon Lightsail is an AWS-managed virtual private server that can help you create websites.

With Amazon Lightsail, you would get all the important resources required to build a website for free. It provides leading CMSs for hosting websites such as Magneto, WordPress, and Joomla. You can deploy a website (e.g., blog) easily using any of your preferred CMS. This project will help you learn how to choose a CMS and deploy a website without writing its code from scratch. CMSs are pre-configured web development solutions used for managing content for websites. Amazon S3 and EC2 instances can also be used to host a website. Students can do this project as an AWS mini-project while studying.

Source code: GitHub

2. Mass Emailing using AWS Lambda

This AWS beginner project helps you build an email application using AWS Lambda that can send mass emails to a large audience. AWS Lambda can be utilized with other email or SMS services to create a cost-effective mass mailing solution. You can use AWS SES (Simple Email Service) to send emails and AWS SNS (Simple Notification Service) to trigger the email-sending process.

Amazon Lambda is closely linked to the S3 service in this project. Once you upload a CSV file to S3, an S3 event is triggered. This makes the Lambda function import the file into the database. After the file is imported, the process of mass emailing begins. Students can easily do this AWS project for practice.

Source Code: Mass Emailing

3. Building Custom Alexa Skills 

This AWS sample project for beginners aims to build a virtual assistant like Alexa and replicate its behavior. You can create custom Alexa Skills using AWS Lambda and the Alexa Skills Kit. "Alexa Skills" are the actions that Alexa takes in response to user requests. An Alexa Skill is essentially a voice-activated Alexa app. Alexa handler function, a function of AWS Lambda, can be used in this project. The Lambda service allows you to implement customized logic for invoking the handler function.

Furthermore, this project offers the flexibility to incorporate third-party functions that are hosted outside of Alexa. This means you can explore various possibilities, such as playing music, setting reminders, or executing other specific functions. You can develop voice-enabled applications that can do different tasks like booking a hotel room, ordering food, or playing music. Know more about how to develop Alexa skills to get a detailed picture of how AWS can help you. 

Source Code: GitHub

4. Creating a Text-to-speech Converter 

This project involves building a text-to-speech converter using AWS Lambda and AWS Polly (a text-to-speech converter service). The text-to-speech converter is nowadays widely used in modern applications as well as websites. This service converts written text into spoken audio in different languages and voices. You can develop real-life speech synthesis applications using AWS Lambda and AWS Polly. This AWS sample project will help you learn how to use AI -powered AWS services for text-to-speech conversion.

5. Content Recommendation System 

You can build a content recommendation system using Amazon SageMaker, a machine learning service offered by AWS. Most streaming platforms, including Netflix and Amazon Prime Video, already utilize content recommendation systems. This AWS project example is highly relevant nowadays when social media is widely using content recommendation systems to present things of our interest. This project helps you recommend content to end users based on their past online behavior or actions with the help of AI and ML.

You can use Amazon SageMaker to recommend services, products, or content based on the browsing history, purchase behavior, and preferences of users. It comes with in-built ML algorithms that do not require label data and leverages semantic search to simplify tasks. When AWS is used along with nearest-neighbor algorithms, you can get relevant recommendations and accurate results. For accurate and realistic suggestions, use the K Nearest Neighbor algorithm with the content recommendation system for this project.

Top AWS Project Ideas for Intermediate Professionals

If you are someone who has practiced basic projects on AWS and want to practice more AWS projects for resume, the following project ideas can help you:

1. Launch a Serverless Web App

This project involves creating a serverless web application using various AWS services such as Amazon Cognito, DynamoDB, Amplify, API Gateway, and Lambda. These services help in the development of a robust web application that can manage any type of workloads. Launching a serverless web app requires you to have knowledge of technologies like JavaScript, CSS, and HTML. Also, the knowledge of implementing RESTful APIs is required as you need to implement RESTful APIs in this project. Start with a simple web app, for example, a BMI calculator.  

2. Use Lex to Create Chatbots

You can use Amazon Lex to create chatbots that can interact with users in a conversational tone like a human agent. As Amazon Lex is a natural language processing service, it can help you develop chatbots that can perform multiple tasks, such as answering customer queries, booking appointments, or providing product information.  

With Amazon Lex, you can deploy chatbots in one click and respond to both voice-based and text-based customer queries. Building chatbots will require you to implement AI models to make the chatbot responses automated and conversational. You can easily integrate Amazon Lex with other AWS services for added functionalities. To ensure the responses work as intended, test them by having conversations with them from the perspective of users.  

3. Creating Real-time Data Processing Application

You can build a real-time data processing application using Amazon Kinesis along with Amazon Lambda. The project involves processing large amounts of data to get highly accurate results in real time. Amazon Kinesis helps in capturing and processing streaming data in real time. Use this service to develop an application for analyzing and processing data when it arrives (e.g., streaming data from any social media platform or IoT sensors).

You must create an Amazon Kinesis stream first and then configure it to collect data from a web source. You can configure the Lambda function instances to scale up/down automatically with respect to the stream. Location-based data and social media timelines can be used as data sources.  

4. Create Attendance Automation

You can build an attendance automation system using Amazon Rekognition, Amazon Lightsail, and Amazon Cognito. Amazon Rekognition helps recognize and identify faces in images and videos. You can use this service to develop an application that can automate the attendance process, such as scanning the faces of students or employees and marking their attendance. For this, the faces of the users are scanned and added using Amazon Rekognition to server-side containers called Collections. These containers scan and read the identity cards using deep learning algorithms for marking attendance.  

5. Creating a Personalized News Feed

You can build a personalized news feed based on your preferences and past browsing and search history. For a personalized delivery platform, you can use AWS Lambda and DynamoDB. Information can be extracted from different touch points and stored in DynamoDB. Later, user profiles can be developed using the stored information. Lambda uses this data to create customized news feeds.

Top AWS Project Ideas for Advanced Professionals

If you want to work on some high-level AWS projects, consider the following project ideas:

1. Kubernetes Clusters on Amazon EC2 Spot

In this AWS DevOps project, you can build a Kubernetes cluster on Amazon EC2 Spot instances, a cost-effective option for running applications that can handle interruptions. For orchestrating, managing, and scaling containers, Kubernetes is widely used in the industry. You can use either Kubernetes or Amazon EKS for this project to deploy and manage your cluster and use Amazon EC2 Spot instances to save costs on running your applications. While working with spot instances, ensure that best practices for spot instances are followed.  

2. Build a Traffic Monitoring Tool

This AWS IoT project involves creating a Smart Traffic Control framework using AWS IoT. You can use this service along with Amazon Kinesis to gather and analyze traffic from different sources, including web servers, and databases. AWS IoT supports various connection protocols, including HTTPS, MQTT, LoRaWAN, and MQTT over WSS for data transfer between AWS and devices.

3. Orchestrate Redshift ETL using AWS Glue and Step Functions

In this project, build an ETL Big Data pipeline using Amazon Redshift to extract business insights from the stored data. Amazon Redshift is a cloud warehouse service that is fully managed by AWS. With Redshift, you can query structured or unstructured data directly from Amazon S3 even when the data is not deployed in the Redshift cluster. It also helps in running complex analytics queries against data and supports sophisticated query optimization, parallel query execution, and columnar storage.  

You can utilize the dataset containing seller and product information from the Amazon E-commerce website for deep learning, machine learning, and natural language processing. For this project, use the Amazon Customer Reviews dataset that contains product reviews from numerous Amazon customers. This dataset can be downloaded in two formats: Parquet and TAV.

4. Serverless Image Recognition Engine

You can build a serverless image recognition app (similar to NatGeo) that can recognize images uploaded to the app automatically using AWS services like AWS Lambda, DynamoDB, and Amazon Rekognition. You can use this service to analyze images and videos in real time and recognize objects, people, and text in them. Lambda functions will identify the patterns in the uploaded image using Rekognition and invoke the metadata in the image. Use DynamoDB for the application back-end maintenance.

Wrapping Up

AWS provides numerous services and tools for developers and businesses to build scalable and cost-effective applications. Working on AWS hands-on projects can be a great way to gain practical experience with AWS services and tools and showcase your skills to potential employers. For more clarity, we have included some AWS projects with source code. We hope this blog provided you with some exciting AWS project ideas that you can work on as a beginner, intermediate professional, or advanced user. To start the journey as an AWS professional, enroll in KnowledgeHut's AWS Practitioner Certification .

Frequently Asked Questions (FAQs)

Learning outcomes during an AWS internship vary by role and project. Common outcomes include gaining technical skills through hands-on experience with AWS services, industry experience with live projects and a certificate, and professional development such as time management and communication skills.

Due to the increasing adoption of cloud computing industry-wide, AWS skills are in high demand. As many organizations are migrating to AWS, the demand for skilled AWS professionals seems to increase further. Gaining AWS skills can open up the doors of opportunities like Cloud Engineers, DevOps Engineers, Security Engineers, etc.

When adding AWS experience to your CV, consider the following points:

• Add specific skills that you are good at. Highlight your strong areas where you are an expert.
• Mention the real-time projects you worked on in detail.
• Show end results; what you achieved via that project (e.g., cost savings or increased productivity)
• Mention your AWS certifications.

Having AWS experience is highly valuable in the current and future scenarios when organizations are moving rapidly to AWS. With hands-on experience on AWS, you will be given more preference in the job market than others. As the demand for AWS professionals is anticipated to increase, you will be more likely to be hired quickly and comfortably.

As AWS is becoming quite popular, many new jobs have emerged in the market that are directly linked to AWS. Multiple streams are available for AWS professionals to choose from, ranging from Solutions Architects to Data Engineers.

• Solutions Architects: Design suitable cloud solutions for client needs.
• SysOps Administrators: Manage cloud infrastructure on AWS.
• Software Developers: Enhance application scalability, security, and performance with AWS integration.
• DevOps Engineers: Streamline development and operations for efficient software delivery.
• ML Engineers: Work on data preprocessing, model training, and model deployment.
• Data Engineers: Handle data storage, processing, and analytics with AWS services.
• Security Engineers: Secure cloud environments from cyber threats using AWS services

There is no definite answer to this question. It depends on your skills, interest, and the present job market. Firstly, check which of the above streams interests you the most. Secondly, see if you can acquire the required skills for the job. Lastly, analyze the current and future job trends in the market for that particular role. Based on these parameters, you can decide on the most suitable stream for yourself. Also, our expert counselors can help you decide the best stream as per your interest and job demand.

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Posted on Jun 26, 2023

Capstone Project - Cloud Architecture

The Capstone project is quite a formidable task, making even quite experienced users work hard on how to overcome this scenario. We find ourselves working at a Social Research organisation that has a website that allows users to look up various data. Over the past few years, the website has grown in popularity and begun experiencing traffic issues as well as complaints about how slow it is. Additionally, there have been attempted ransomware attacks and security breaches. This is where we come in. We are here to design an infrastructure for the company's website that follows best practises and improves upon the existing architecture.

This blog is a record of how I overcame the Capstone project.

What we started with At the start, we were given a diagram of the current environment and how the company's website was laid out:

This current architecture shows us how the bastion host has been set up as well as its additional security groups placed in multiple subnets. This current architecture does not follow best practises as it is not highly available or does not scale automatically.

The solution

The solution I came up with not only solves the initial problem of being unable to scale automatically but also makes it more secure and highly available. By storing data within a MySQL RDS Multi-AZ database in a private subnet across multiple availability zones (AZ), it allows for more users around the world to access the website without experiencing traffic delays. Additionally, this meant that this solution had failover, allowing the secondary database to take over if the primary one were to fail or become unavailable.

The Application Load Balancer (ALB) is placed in front of the autoscaling group, which is linked to both applications in each AZ, allowing for a smoother runtime. Admin users would be able to access the applications by using SSH through the bastion host and access or store data.

We start off by downloading a SQL dump file provided by AWS that gives us the necessary tools in order for our applications as well as our databases to run. We create an internet-facing Application Load Balancer and attach it to two public subnets, as well as attaching the respective security groups. As we were setting up the autoscaling group, which would be behind the ALB, it gave us the option to attach it to both availability zones as well as both subnets (public and private). This would allow the infrastructure to be highly available.

Once the two had been created, it allowed the application to also be created within the process. After configuring the security groups, I was finally able to access the website. However, not only did it not look like a proper website, it was not functioning like one either.

The website would list what users may want to find information about, but it would not be able to list any of the necessary information. The website would return a connection error.

The next step was to create a multi-RDS database. This would allow for a secure and highly available way to store and access data that users could access without experiencing traffic.

note   (I had used a burstable class for this instance as it would allow for performance to exceed regular use if there was a need for it as we were already experiencing traffic issues.)

While the database was being created, I used this time to go into Systems Manager and create the parameters needed in the parameter store:

  Once the database was created, it was time to connect to it through the application we created earlier. This was done through the Bastion host and accessing it through the Access Key and Secret Access Key provided by AWS. Upon entering, I was able to import the SQL dump file, which allowed the database to have the data it needed. This was done by listing within the file to ensure that Countrydatadump.sql was inside of it. After the commands mysql -u username -p database_name < file.sql and entering the required password that I had set earlier when creating the RDS database, it was successfully able to ingest all the data it needed.

Upon successfully launching the application, the last thing to do was to check the website one last time and see if users could access the data they were looking for. After all my hard work, it was finally a success.

The Capstone project really pushed me to think outside the box and utilise all the skills I acquired during my journey as a trainee cloud engineer. This was something I had never experienced before, and I look forward to working on more projects like this in the future. I plan to update my blog throughout my career to not only allow readers to see my work but also to use it as a portfolio to show myself and others how I have evolved over the coming years with each project.

I appreciate you taking the time to read this!

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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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AWS Academy Cloud Architecting 2.x – Capstone Project

by XX · Published September 22, 2022 · Updated September 24, 2022

Environment Overview

Environment navigation, access the aws management console.

Using the terminal in the browser

Project Overview

Introducing the Example Social Research Organization

Solution requirements, project deliverables, assets for completing the project.

This environment is long-lived. When the session timer runs to 0:00, the session will end, but any data and resources that you created in the AWS account will be retained. Any running resources (such as an EC2 instance) will be stopped. If you later launch a new session (for example, the next day), you will find that your work is still in the lab environment. However, you will need to manually start any stopped resources. You can continue to develop your solution as you progress through the course materials.

 IMPORTANT: Monitor your lab budget in the lab interface above. Whenever you have an active lab session, the remaining budget will display at the top of this screen. For this Capstone Project environment, the limit is $40. If you exceed your lab budget your lab account will be disabled and all progress and resources will be lost . Therefore, it is important for you to manage your spending. Suggestions to avoid overspending : Launch only the number of instances you need, sized to your requirements. Stop EC2 and RDS instances when not in use. Delete no longer needed resources and data.

Use the  Readme link above to return to these instructions at any time.

Use the  AWS Details link above to access information about your environment.

After you start the lab, the AWS Details panel will display and you will need to choose Readme to return to these instructions.

 Tip: you can resize this panel at anytime by dragging the bar to the left of these instructions to make it wider or narrower.

Use the  Reset link above if you ever want to reset your AWS account back to the way it was in the beginning, before you ever ran sessions of this lab environment.  CAUTION : if you choose reset and then choose Yes to confirm that you do want to reset, you will permanently delete everything that you have created or stored in the AWS account.

The terminal window to the left of these instructions can be used to run AWS CLI commands or code such as AWS SDK for Python code (details provided below).

• The lab session is started and session information is displayed.
• A timer above shows the time remaining in the session. Tip: You can refresh the session length at any time by choosing Start Lab again before the timer reaches 0:00.
• Choose the  Readme link to return to these instructions.
• You should be connected to the AWS Management Console. Tip: If a new browser tab does not open, a banner or icon is usually at the top of your browser with the message that your browser is preventing the site from opening pop-up windows. Choose the banner or icon, and then choose Allow pop-ups. Tip: if you are interested in interacting with the AWS account programmatically, read the Configuring and using the terminal in the browser section below for details.

Using the Terminal in the browser

A terminal window displays to the left of these instructions. The terminal provides access to a Linux shell on a server that exists outside of the AWS account that you use when your lab is running. Credentials are configured on the server that provide the same level of AWS service access via the terminal that you also have via the AWS Management Console.

Project overview

This project provides you with an opportunity to demonstrate the solution design skills that you develop throughout this course. Your assignment is to design and deploy a solution for the following case.

By the end of this project, you should be able to apply the architectural design principles that you learned in this course to:

• Deploy a PHP application that runs on an Amazon Elastic Compute Cloud (Amazon EC2) instance
• Create a database instance that the PHP application can query
• Create a MySQL database from a structured query language (SQL) dump file
• Update application parameters in an AWS Systems Manager Parameter Store
• Secure the application to prevent public access to backend systems

Example Social Research Organization is a (fictitious) nonprofit organization that provides a website for social science researchers to obtain global development statistics. For example, visitors to the site can look up various data, such as the life expectancy for any country in the world over the past 10 years.

Shirley Rodriguez, a researcher at the organization, developed the website. She thought it would be valuable to share the data that she had gathered with other researchers. Shirley stores the data in a MySQL database, and the data is available through a PHP website that she built. She initially published the site through a commercial hosting company that provides limited support for technical issues and security.

Over the past year, Shirley’s website has grown in popularity. As a result of increased traffic, she started receiving complaints that the site is not as responsive as it used to be. She also experienced an attempted ransomware security breach. The security breach was unsuccessful, but her supervisor, Mateo Jackson, suggested that Shirley investigate new ways to host the website.

Shirley heard about Amazon Web Services (AWS), and initially moved her website and database to an EC2 instance that runs in a public subnet. She also runs an instance of MySQL on the same EC2 instance.

Shirley approached your team to make sure that her current design follows best practices. She wants to make sure that she has a robust and secure website. One of your colleagues started the process of migrating the site to a more secure implementation, but they were reassigned to another project. Your tasks are to complete the implementation, make sure that the website is secure, and confirm that the website returns data from the query page.

The following summary lists the solution requirements, and provides a diagram of the current environment.

• Provide secure hosting of the MySQL database
• Provide secure access for an administrative user
• Provide anonymous access to web users
• Run the website on a t2.small EC2 instance, and provide Secure Shell (SSH) access to administrators
• Provide high availability to the website through a load balancer
• Store database connection information in the AWS Systems Manager Parameter Store
• Provide automatic scaling that uses a launch template

The following parameters are used by the PHP application to connect to the database:

• /example/endpoint
• /example/username
• /example/password
• /example/database

 These parameter values are case sensitive.

To complete this assignment, you must:

• Deploy a PHP application that meets the system requirements outlined above
• Submit a diagram that illustrates your solution
• Submit a written summary of the design decisions that you made to achieve the result

You can use the following assets for this project:

• A SQL dump file that contains sample data
• A .zip file that contains the PHP and image files for the Example Social Research Organization website

Tags: AWS awscloud awstraining cloud cloudcomputing

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4 Responses

• Pingbacks 0

I watched all your videos related to aws and all of them helped me a lot ??. But I’m unable to complete the caspton 2.x project ????. Please help me . Connect with me through Instagram or Facebook ??. Message me ur Instagram or FB id or Whatsapp number.

Hi did you check the you check the youtube video? Exactly which part you can’t accomplish?

What can I do if my parameter store is Restricted? is there another approach to finish the capstone without configuring the parameter store? Your video helped me a lot, but I can’t do that part.

Hello I am stuck at the Putty console step when trying to ping google.com. Nothing happens and when exited the ping fails.

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