
Over a two-month period, Nasaoreo121 contributed to the aws-samples/aws-kr-startup-samples repository by developing two core features focused on generative AI and SaaS analytics. They built an AI-powered webtoon background transformation tool using Python and AWS CDK, leveraging Amazon Bedrock’s Stable Diffusion XL within a secure VPC to enable style-preserving image variations. Additionally, they implemented a multi-tenant SaaS metering and analytics capability, designing an end-to-end workflow with TypeScript, API Gateway, and Athena for usage tracking and reporting. Their work established scalable, privacy-conscious infrastructure and demonstrated depth in serverless architecture, infrastructure as code, and data analytics pipelines.
December 2025 monthly summary for aws-samples/aws-kr-startup-samples. Focused on delivering a multi-tenant SaaS metering and analytics capability using AWS Bedrock. Key milestones include end-to-end metering workflow, authentication, request processing, and analytics pipeline. The work lays the groundwork for usage-based billing and scalable analytics across tenants. Key features delivered: - Multi-tenant SaaS Metering and Analytics with Bedrock: implemented a Bedrock-based metering demo with multi-tenant usage tracking and extended analytics, including authentication and request processing infrastructure (Cognito, API Gateway, Lambda) and analytics pipeline (Athena, Glue). - CDK TypeScript source for bedrock-saas-metering: created infrastructure-as-code for deployment and future enhancements. Major bugs fixed: - No major bugs reported this month; any minor issues resolved within standard sprint cycles. Overall impact and accomplishments: - Established a scalable, secure, and observable foundation for usage-based metering and billing. - Enabled tenant-scoped analytics and reporting, improving product visibility and customer value. Technologies/skills demonstrated: - AWS Bedrock, Cognito, API Gateway, Lambda, Athena, Glue, CDK TypeScript, serverless architecture, data analytics pipelines, and multi-tenant software design.
December 2025 monthly summary for aws-samples/aws-kr-startup-samples. Focused on delivering a multi-tenant SaaS metering and analytics capability using AWS Bedrock. Key milestones include end-to-end metering workflow, authentication, request processing, and analytics pipeline. The work lays the groundwork for usage-based billing and scalable analytics across tenants. Key features delivered: - Multi-tenant SaaS Metering and Analytics with Bedrock: implemented a Bedrock-based metering demo with multi-tenant usage tracking and extended analytics, including authentication and request processing infrastructure (Cognito, API Gateway, Lambda) and analytics pipeline (Athena, Glue). - CDK TypeScript source for bedrock-saas-metering: created infrastructure-as-code for deployment and future enhancements. Major bugs fixed: - No major bugs reported this month; any minor issues resolved within standard sprint cycles. Overall impact and accomplishments: - Established a scalable, secure, and observable foundation for usage-based metering and billing. - Enabled tenant-scoped analytics and reporting, improving product visibility and customer value. Technologies/skills demonstrated: - AWS Bedrock, Cognito, API Gateway, Lambda, Athena, Glue, CDK TypeScript, serverless architecture, data analytics pipelines, and multi-tenant software design.
November 2024: Delivered an AI-powered webtoon background transformation feature that runs inside a secure VPC, enabling weather, time-of-day, and seasonal variations while preserving original art style using Amazon Bedrock Stable Diffusion XL. Built end-to-end infrastructure with AWS CDK to provision the VPC and processing resources, and provided a Jupyter notebook for image-to-image generation to support rapid experimentation and validation. Added sample code demonstrating the workflow, establishing a reusable baseline for privacy-conscious image processing in this repository.
November 2024: Delivered an AI-powered webtoon background transformation feature that runs inside a secure VPC, enabling weather, time-of-day, and seasonal variations while preserving original art style using Amazon Bedrock Stable Diffusion XL. Built end-to-end infrastructure with AWS CDK to provision the VPC and processing resources, and provided a Jupyter notebook for image-to-image generation to support rapid experimentation and validation. Added sample code demonstrating the workflow, establishing a reusable baseline for privacy-conscious image processing in this repository.

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