AWS-based Well-Architected Review of Data Governance Provider

Based on the critical findings, our team immediately prioritized production fixes and ecosystem enhancement within the AWS infrastructure:

• Implemented precisely assigned permissions, security groups, IAM roles, and robust encryption protocols

• Integrated consistent resource tagging and naming conventions, along with targeted virtual private cloud (VPC) improvements

• Enabled comprehensive global logging and auditing, configured Security Hub, and hardened CI/CD pipelines

• Defined and applied a robust multi-account strategy by setting up dedicated environments separated across distinct AWS accounts

Simultaneously, our data pipeline experts focused on achieving peak performance and reliability:

• Conducted a detailed performance analysis report, identifying primary database wait events and processing bottlenecks

• Executed performance tuning through advanced indexing strategies, query refactoring, and configuration adjustments

• Developed a robust end-to-end extract, transform, load (ETL) pipeline ready for future expansion and scaling

• Created a complete data build tool (DBT) project utilizing SQL models for complex data transformation tasks

• Provided a summary report detailing the final architecture, achieved data latency metrics, and performance benchmarks, serving as the blueprint for migrating all remaining reports

Our team proactively extended beyond the initial WAR scope, proposing strategic enhancements for long-term product performance. For instance, we recommended the client migrate from their existing OpenAI stack to the AWS-native Bedrock AI service, significantly enhancing solution security and improving seamless integration with other native AWS services.