SNOWFLAKE-GPT
Securely integrates GPT models with Snowflake to enable natural language querying of data, empowering analysts with advanced AI capabilities while maintaining strict access controls.
View ProjectArchitecting scalable solutions with Python & AWS.
My approach to cloud architecture is pragmatic: use the right tool for the job. I started with EC2-based deployments but evolved toward serverless and containerized solutions. I use AWS Lambda for quick, focused APIs and Docker containers (via services like Lightsail) for robust, long-running applications like this portfolio.
I prefer microservices for their clarity. They allow me to track costs at a granular level (knowing exactly which feature is driving the bill) and significantly boost developer velocity. New team members can onboard and contribute to a specific service without needing to understand a massive monolithic codebase.
However, microservices bring their own challenges, like "function sprawl." In one role, our environment grew to over 50 Lambda functions in a single year. To manage this, I rely heavily on Terraform and structured Git repositories to keep infrastructure organized. I also lean on CloudWatch for detailed logging and debugging, which is essential when you're trying to figure out why a Lambda layer is failing to connect to a legacy MSSQL server from 2004.
Securely integrates GPT models with Snowflake to enable natural language querying of data, empowering analysts with advanced AI capabilities while maintaining strict access controls.
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View ProjectInfrastructure as Code (IaC) solution for dynamic Tableau subscription management, utilizing Python, AWS, and Terraform to automate user group updates.
View Project