
Brenno Passanha enhanced AWS cost analytics by developing tagging features across the awslabs/cid-framework and aws-samples/aws-cudos-framework-deployment repositories. He introduced a 'tags' column to CUR2 data exports, updating Athena schemas to support map<string,string> types for detailed billing analysis. In the following month, Brenno implemented comprehensive Account Tags support, enabling robust data discovery and improved dashboard readiness for cost attribution workflows. His work involved Python, SQL, and AWS Athena, focusing on schema evolution, error handling, and data presentation. The depth of his contributions lies in aligning data models with AWS specifications and ensuring backward-compatible, maintainable cloud infrastructure enhancements.
February 2026 monthly highlights for repo aws-samples/aws-cudos-framework-deployment. Focused on delivering robust Account Tags support from CUR Tags column, strengthening data discovery and dashboard readiness for CID workflows.
February 2026 monthly highlights for repo aws-samples/aws-cudos-framework-deployment. Focused on delivering robust Account Tags support from CUR Tags column, strengthening data discovery and dashboard readiness for CID workflows.
January 2026: Delivered CUR2 Data Exports enhancements in awslabs/cid-framework. Introduced a new 'tags' column for CUR2 data exports and updated the Athena table schema to support tagging data as map<string,string>, aligning with AWS CUR2 specifications. Version bumped to v0.9.0 to reflect the feature addition. These changes enable detailed tagging for billing data analysis and improve downstream cost visibility and analytics across export/query layers.
January 2026: Delivered CUR2 Data Exports enhancements in awslabs/cid-framework. Introduced a new 'tags' column for CUR2 data exports and updated the Athena table schema to support tagging data as map<string,string>, aligning with AWS CUR2 specifications. Version bumped to v0.9.0 to reflect the feature addition. These changes enable detailed tagging for billing data analysis and improve downstream cost visibility and analytics across export/query layers.

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