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AWS Lambda

Generate SOCI Indices asynchronously with AWS Lambda

Base Project - Serverless Framework

This project is a base setup using the Serverless Framework, with Python as the primary programming language. The system is deployed on AWS Lambda and uses AWS API Gateway to bridge the connection between the Frontend and Backend.

The CI/CD pipeline is automated with AWS CodePipeline and AWS CodeBuild, ensuring a smooth and efficient build, test, and deployment process.

Key Technologies:

Language: Python Serverless Framework: Manage and deploy serverless services AWS Lambda: Serverless compute for backend logic AWS API Gateway: Create and manage API endpoints CI/CD: AWS CodePipeline + AWS CodeBuild This project is designed to streamline development and deployment processes, enabling teams to easily scale and maintain cloud-native systems.

IDS721 Spring 2025 course, second project

Set up GitLab CI/CD for deploying serverless applications

This is the integration of two APIs created on the local server. Here is a work by ASK: my Alexa skill, which will get a request from someone’s voice and send it to GPT3 API, after resending it back, preparing, and saying it to the user. The project is under development.

contact: sashapetrovskyidev@gmail.com

Cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, and intelligence—over the Internet.  

Major cloud providers:

Amazon Web Services (AWS): The largest and most comprehensive cloud provider, offering a wide range of services from compute and storage to machine learning and analytics. Google Cloud Platform (GCP): Known for its focus on data analytics, machine learning, and artificial intelligence, GCP is a popular choice for businesses that need powerful tools for data-driven insights. Microsoft Azure: A strong competitor to AWS, Azure offers a wide range of services and is particularly well-suited for businesses that already use Microsoft products. Examples of cloud computing services:

Compute: Virtual machines, serverless computing, containers Storage: Object storage, block storage, file storage Databases: Relational databases, NoSQL databases, data warehousing Networking: Virtual private clouds, load balancing, content delivery networks Machine learning: Training and deployment of machine learning models Analytics: Big data processing, data warehousing, business intelligence By using cloud computing, businesses can scale their resources up or down as needed, reduce costs, and improve flexibility.

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Serverless project with AWS which accepts to an SMS endpoint a text containing wordle guesses and texts back to the same number an analysis of how many possibilities remained given the clues obtained from each guess.