Cloud Commander AI

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  Architectural Diagram

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  Chatbot for query and lambda instance hitting

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  Live Dashboard

Inspiration

Cloud costs are often unpredictable and high. We wanted to build a smart system that helps companies automatically save money without manual effort.

What it does

It predicts which cloud resources will be expensive soon, then automatically stops or scales them down to reduce costs, while keeping a clear log of actions.

How we built it

We combined machine learning models for cost prediction, AWS S3 for data storage, AWS Lambda for automation, and AWS Bedrock for intelligent agent recommendations.

Challenges we ran into

Integrating multiple AWS services smoothly and handling complex decision logic without false positives was challenging.

Accomplishments that we're proud of

Automating end-to-end FinOps cost saving with minimal manual monitoring and clear audit logs.

What we learned

The power of combining AI predictions with agentic orchestration to solve real-world cost problems effectively.

What's next for Cloud Commander AI

Enhance predictive accuracy, expand agentic actions for broader cloud services, and add a conversational AI interface for easy user interaction.

Built With

• amazon-web-services
• aws-bedrock
• bedrock
• lambda
• python
• streamlit