SPOTO has collected a collection of fascinating project ideas on AWS. These AWS sample project dumps might help you enhance your skills and knowledge.

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AWS Projects for Novices/Newcomers

This section provides a collection of the most specific AWS projects for beginners that will help you gain experience with AWS cloud services.

1.Rapid Document Transformation

The objective is to efficiently and precisely convert the document to the format requested by the user. There are numerous online document converters, including PDF to Word converters and others. You have likely encountered the necessity to convert an HTML page or document to PDF format. Similarly, it is commonly essential to convert an excel sheet to a word document or other form. AWS Lambda permits the creation an application that can instantly transform documents from one format to another. You can retrieve the relevant content and can format and convert the content to download or display on the webpage. You can put this application on a job platform where users frequently wish to convert their resumes to a different format.

2. Windows Virtual Machine – Deployment

The objective is to deploy Windows Virtual Machine with zero security violations. VM Management in Microsoft Azure is a standard tool utilized to deploy virtual machines. You can deploy Windows virtual machines on AWS using Amazon Lightsail as the web service. It will assist in simplifying the process and will enable you to utilize the optimum number of resources as necessary. This service provides an easily adaptable user interface, and you may use it to connect with the RDP client.

3. Mass Emailing using AWS Lambda

This project intends to send mass e-mails to an organization’s current and prospective clients. MoonMail is one of the real-world cloud-based bulk mailing services developed with AWS Lambda. You can use AWS Lambda and Simple Email Service (SES) to construct a cost-effective platform for bulk mailing. With S3, you can send mass emails to additional recipients.

Uploading a CSV file will immediately generate an S3 event. Following this, a Lambda function will import the file into the database. The process of sending mail to the specified addresses will commence.

Advanced Level AWS Projects

After working on beginner-level AWS projects, it’s time to evaluate your progress by tackling a few intermediate-level AWS tasks. These projects are primarily suited for experts with two to four years of experience.

4.Real-time processing of data application

The objective is to process high-volume data quantities in real time without compromising the results’ precision. Bustle is a real-world example that utilizes AWS services to process enormous volumes of site statistic data in real time. Amazon Kinesis Stream and AWS Lambda can be used for this project. In the first phase, you will be required to construct a Kinesis Stream, and it will be necessary to configure it to collect data from a web source. Several Lambda function instances will be automatically scaled up or down based on the stream’s scaling. As data sources, you can utilize social media timelines or location-based data.

5.Customer Workflow Logic

The objective is to design and install application-specific logic workflows in response to the trigger events. The Coca-Cola vending machine is an application of AWS Lambda and SNS in the real world. Meal Panda, an app for food delivery, is another well-known example. It is now feasible to incorporate Lambdas into step-function-based workflows. This is an AWS project for beginners because the functions are brief, and the outcome can be tested and validated rapidly. One of the areas where you can create and implement this project is shopping cart management. The information will be easily accessible on all e-commerce websites.

6. Kubernetes Clusters on Amazon EC2 Spot

This project aims at setting up Kubernetes clusters in Amazon EC2 Spot using 100% compliance with best practices. Open-source Kubernetes is a popular cloud computing platform with many real-world applications. This is an excellent AWS project to learn AWS and Kubernetes skills. Amazon EC2 (the foundational service of AWS) is what you will need to do. This service has dynamic computing capabilities in the cloud. This project will be ahead of the rest using Amazon EC2 Spot instances. Kubernetes and these instances follow the same approach to containers, so you can use both. You can create multiple node groups in this project. You will also be focusing on capacity optimization to optimize allocation. This will ensure that worker nodes perform as expected.
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Advanced Level AWS Projects

This section contains advanced-level projects suitable for professionals who want to improve their skills by working on relevant projects in the industry.

7. Custom Alexa Skills

Our goal is to create a virtual assistant that replicates the functions and skills of Amazon Alexa. Alexa, a product of Amazon, is a popular virtual assistant. AWS Lambda can be used with a custom Alexa skill embedded in AWS Console. This object invokes the handler function. You can also use the Alexa skill handling function, an AWS Lambda operation. The custom logic will be provided and will handle the fulfillment of the request. Third-party parts can be used outside of the Alexa skill. You can start with basic tasks, like playing music or creating reminders.

8. Serverless Image Recognition Engine

Our goal is to create an app that automatically recognizes images uploaded to the app. NatGeo’s image recognition is a popular real-world application. This machine learning project can be developed using AWS Lambda and several built-in functions. One Lambda function will invoke metadata from the uploaded image. The other will use recognition to identify patterns in the picture. DynamoDB will also be used to maintain the backend of the application.

9. Text-to-Speech Converter

This machine-learning project aims at developing an app that converts text to speech. Text-to-Speech, an AI-based function used in many websites and web apps, can be found on many websites. Google Text-to-Speech has been a popular application. You can transform textual information into speech with AWS Lambda and Amazon Polly. Combining the two can allow you to create lifelike speech synthesis apps. Amazon Polly will enable you to use deep learning technology to perform accurate conversions. AWS Lambda can improve the response time for any real-time application.

10. A personalized news feed

It is designed to provide a customized news feed based on your browsing history and search preferences. This functionality is used by Google to display suggested articles in mobile browsers based on search history and browsing history. AWS DynamoDB or AWS Lambda can be used to create a personalized content delivery system. The information will need to be extracted from user touchpoints. The application information is stored in DynamoDB. The platforms for creating user profiles are Lambda functions and stored data. The creation of customer feeds is possible thanks to the parameters.

Portfolio AWS Projects

To earn the trust of a hiring manager, it is essential to demonstrate your ability to complete the required tasks. This strategy is necessary for the Big Data industry. It involves building a solid portfolio. How do you achieve this? You can do this by adding a lot of projects to your Big Data portfolio. This section contains some great AWS projects for beginners relevant to the industry. These projects will help you stand out among your peers and land the job you want.

11. Building Real-Time AWS Log Analytics Solution

Log analytics is an everyday use case for Big Data. It allows you to monitor application availability and detects fraud. This AWS project will allow you to create an end-to-end log analytics solution to gather, ingest and analyze data. After the data analysis is complete, you can evaluate the status of AWS production systems. This real-time AWS project allows you to explore AWS native services like Amazon S3, IAM, and AWS EC2. AWS Glue is also available.

12. Website Monitoring with AWS Lambda or Aurora

Website monitoring validates that the website works properly and users can navigate it easily. This project will use tools like Amazon Dynamo DB and Lambda as well as MySQL, Aurora, MySQL, MySQL, and Kinesis. Install Amazon Kinesis on an AWS EC2 instance. Next, you can use Amazon Kinesis to create data analytics streams for real-time data streaming. After launching AWS EC2 instances and assigning the Identity Access Management (IAM) role to each model, you can create data analytics streams for real-time data streaming. Kinesis Analytics can be used to log stream Kinesis data streams. You can load order logs into Amazon DynamoDB using AWS Lambda, then use Kinesis Analytics to stream the data in real-time.

13. AWS Services can be used to build an analytical platform for eCommerce.

Ecommerce analytics collects data from all factors that affect a retail outlet. This data can be used by analysts to predict changes in customer behavior or online shopping trends. This project will require you to use an eCommerce dataset to create two analytical pipelines. They will be based on logs of user purchases, product views, cart history, and user’s path through the digital platform. Batch processing is required for this project. This involves ingesting data via S3, processing it with Amazon Glue, visualization using Amazon Kinesis, and processing it again using Amazon Glue. To extract relevant business insights from the data, use AWS QuickSight.

Python AWS Projects

Python is a popular choice when working with AWS resources. This popularity can be attributed to the fact that AWS uses Python SDK Boto, which allows for more efficient development and less code. Here are some AWS project ideas that beginners should explore to learn more about Python’s ease of use.

14. AWS Athena Big Data Project to Query COVID-19 Data

This is one of the easiest AWS projects that you can do. The covid-19 data will be examined using AWS Athena. This is a serverless SQL query tool. The Covid-19 database contains Covid-related timestamps and posts as well as comments. This project will show you how to use Amazon Glue to create tables. It also gives you a chance to explore different Athena joins. You will learn to use Python to create tables with crawlers in the AWS Glue Data Catalog. This project will help you to understand how AWS Athena pricing changes depending on file size. This project also involves Amazon S3, Amazon CloudWatch, and others. AWS S3 allows the storage of the CSV file (CSV file) in S3 buckets. CloudWatch tracks your log files and will enable you to analyze them.

15. Python Data Pipeline for AWS ETL Data Pipeline

Cloud-based security Data Lake solutions allow you to create rich analytics from data by categorizing it into multiple storage segments, such as raw, clean, and analytical. This project aims to simplify, organize, and efficiently analyze structured and semi-structured YouTube data based on trending metrics and video genres. It includes data in CSV files on YouTube videos that have been trending for several months.

16. Flink and Kinesis can be used to build a real-time streaming data pipeline.

Real-time data allows you to quickly access the information you need in context and allow you to make informed business decisions. This AWS big-data project will show you how to use Amazon Kinesis to host an Apache Flink Python script to create a streaming platform. This project will simulate real-time accidents and build a pipeline to allow you to analyze and take appropriate actions. This project will enable you to better understand AWS Kinesis and Apache Flink services.

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Last modified: 2022-11-15



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