The Challenge
NBCUniversal's video content required quality control before distribution across their networks. Manual QC processes were time-consuming, inconsistent, and couldn't scale with the volume of content being produced. They needed an automated solution that could maintain broadcast-quality standards.
The challenge: replace manual video quality control with a fully automated pipeline that could process content at scale while maintaining the quality standards expected from a major media company.
Our Approach
- Serverless Pipeline: Architected fully automated video QC using AWS Step Functions and Kinesis
- Event-Driven Architecture: Built scalable workflows that processed video content asynchronously
- Quality Automation: Replaced manual QC processes with automated quality checks
- Test-Driven Development: Achieved 100% test coverage through rigorous TDD practices
- Technical Standards: Established engineering standards adopted across the team
Architecture
flowchart TB
subgraph Input
V[Video Upload] --> S3[(S3 Bucket)]
end
subgraph Pipeline["Automated QC Pipeline"]
S3 --> SF[Step Functions]
SF --> L1[Format Check]
SF --> L2[Audio Analysis]
SF --> L3[Video Quality]
L1 & L2 & L3 --> K[Kinesis]
end
subgraph Output
K --> DB[(DynamoDB)]
DB --> Dash[QC Dashboard]
end
Results
The automated pipeline transformed NBCUniversal's content operations:
- Fully automated video quality control pipeline in production
- Eliminated manual QC bottlenecks in content workflow
- 100% test coverage ensuring reliability and maintainability
- Established TDD practices and technical standards across the team
- Scalable serverless architecture handling variable content volumes
