Platform Engineering at Scale
summary
Cloud-native platform processes 15 TB to 140 TB monthly for healthcare analytics using AWS S3 and Amazon Redshift, automated ETL and a copy-command injection layer, with metadata-driven quality checks and compliance-as-code for HIPPA and GDPR. Processing time drops by 80% reduction in processing time, developer velocity rises 67%, workload capacity increases 340%, drug-discovery timelines shorten by 4.2 months per compound, and operations save $2.3 million annually through infra-as-code, self-service and multisite scaling.
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chapters (8)
- 0:00Introduction and Speaker Background
- 0:27Overview of Platform Engineering in Healthcare
- 0:41Challenges in Healthcare Data Management
- 1:47Platform Engineering Transformation
- 2:47Technical Implementation and Benefits
- 5:39Phased Approach to Cloud Transformation
- 6:17Addressing Challenges and Strategies
- 7:23Key Elements for Successful Platform Engineering
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