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zicanl-amazon

PROFILE

Zicanl-amazon

Worked on the awslabs/sagemaker-hyperpod-usage-report repository, delivering end-to-end enhancements to HyperPod usage reporting over three months. Developed modular report generation in Python, introduced a Parquet-based data model with resource versioning, and improved deployment automation using AWS CloudFormation and Helm. Addressed data accuracy by refining utilization aggregation logic and expanded IAM policies for secure S3 bucket cleanup. Enabled regional deployment support by updating Helm charts for new AWS regions, supporting scalable rollouts. Focused on maintainable code organization, robust missing-data handling, and standardized Athena workgroup usage, resulting in more reliable reporting, improved governance, and streamlined onboarding for data engineering workflows.

Overall Statistics

Feature vs Bugs

75%Features

Repository Contributions

9Total
Bugs
1
Commits
9
Features
3
Lines of code
3,195
Activity Months3

Work History

July 2025

1 Commits • 1 Features

Jul 1, 2025

July 2025 monthly summary for awslabs/sagemaker-hyperpod-usage-report. Focused on expanding regional deployment coverage and validating the Helm-based deployment flow for new AWS regions.

May 2025

2 Commits • 1 Features

May 1, 2025

May 2025 monthly summary for awslabs/sagemaker-hyperpod-usage-report: Delivered two prioritized improvements to usage reporting. 1) Feature: S3 Bucket Versioned Objects Handling — extended the installer IAM policy to list and delete object versions, enabling complete cleanup of versioned S3 buckets used for usage reports. 2) Bug fix: Correct Utilization Aggregation — replaced instance-count based calculation with sum-based aggregation of CPU, GPU, and neuron core utilization; added 'pod' to team-level utilization grouping for accurate cross-team reporting. Impact: improved data accuracy, security/compliance through thorough cleanup, and reliable cost/resource visibility; reduced risk of stale data and misinterpretation of usage metrics. Tech/skills: IAM policy enhancement, S3 versioned object handling, precise data aggregation logic, and maintainable code changes with auditable commits.

April 2025

6 Commits • 1 Features

Apr 1, 2025

April 2025 monthly summary for awslabs/sagemaker-hyperpod-usage-report focusing on delivering business value and technical achievements, including end-to-end HyperPod usage reporting enhancement, data model upgrades, and streamlined deployment and governance.

Activity

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Quality Metrics

Correctness93.2%
Maintainability92.2%
Architecture93.2%
Performance84.4%
AI Usage20.0%

Skills & Technologies

Programming Languages

JSONMarkdownPythonYAMLpythonsqlyaml

Technical Skills

AWSAWS AthenaAWS CloudFormationAWS GlueAWS LambdaAWS S3Amazon AthenaAmazon S3AthenaCloud InfrastructureCloudFormationCode OrganizationData EngineeringData ReportingDevOps

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

awslabs/sagemaker-hyperpod-usage-report

Apr 2025 Jul 2025
3 Months active

Languages Used

MarkdownPythonYAMLpythonsqlyamlJSON

Technical Skills

AWSAWS AthenaAWS CloudFormationAWS GlueAWS LambdaAWS S3