aws/modern-data-architecture-accelerator
Nov 2025 – Nov 2025
1 Month active
Languages Used
JSONTypeScript
Technical Skills
AWSAWS CDKCloud ComputingCloudFormationDevOpsInfrastructure as Code
SHAKTI SINGH SHEKHAWAT
PROFILE
Shakti Singh Shekhawat
Worked on the aws/modern-data-architecture-accelerator repository to enhance SageMaker Studio by implementing lifecycle configuration support, enabling per-session environment bootstrapping and automated package installation for JupyterLab. Addressed security and reliability by fixing EFS encryption permission gaps, ensuring encrypted EFS volumes are consistently created during SageMaker AI domain updates. Leveraged AWS, AWS CDK, and TypeScript to deliver infrastructure as code solutions that streamline developer onboarding and reduce manual setup for data science workflows. These improvements strengthened data security and operational efficiency, allowing for reproducible environments and aligning environment provisioning with encryption requirements across the accelerator’s cloud infrastructure.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
1,134
Activity Months1
Your Network
1693 peopleWork History
November 2025
2 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for aws/modern-data-architecture-accelerator focused on delivering secure, scalable SageMaker Studio enhancements and robust environment provisioning. Delivered a lifecycle configuration capability for SageMaker Studio to enable per-session environment bootstrap and package installation, and fixed EFS encryption permission gaps for SageMaker AI domain updates to ensure encrypted volumes are created reliably. These changes improve developer onboarding, reduce setup time, and strengthen data security for AI workflows.
2 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for aws/modern-data-architecture-accelerator focused on delivering secure, scalable SageMaker Studio enhancements and robust environment provisioning. Delivered a lifecycle configuration capability for SageMaker Studio to enable per-session environment bootstrap and package installation, and fixed EFS encryption permission gaps for SageMaker AI domain updates to ensure encrypted volumes are created reliably. These changes improve developer onboarding, reduce setup time, and strengthen data security for AI workflows.
November 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
JSONTypeScript
Technical Skills
AWSAWS CDKCloud ComputingCloudFormationDevOpsInfrastructure as CodeSageMaker
Repositories Contributed To
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