In the blog post “Scaling up the Prime Video Audio-Video Monitoring Service and Reducing Costs by 90%” by Prime Video Tech, the author[1] outlines the challenges and solutions implemented by the Prime Video team to scale up their monitoring service while reducing costs. Let us discuss the main technical points discussed in the post.
Problem Statement and Goals:
The author identifies the main challenge that the Prime Video team faced, which was to efficiently monitor the quality of video streams at scale while minimizing costs. The goals of the project include reducing costs, improving the monitoring service, and maintaining high-quality video streams.
Illustration – Prior Architecture of Prime Video
The author then presents a comprehensive approach to address the problem, which includes several steps:
The most controversial – Moving to a monolithic architecture back from microservices
- Transitioning from CPU-based to GPU-based monitoring
- Reducing the number of frames to be analyzed
- Improving the video decoding pipeline
- Implementing a custom scheduler
- Upgrading the monitoring infrastructure
Moving to a monolithic architecture, back from microservices:
We discussed this in the last blogpost.
Transition to GPU-Based Monitoring:
The team switched from a CPU-based to a GPU-based monitoring solution, allowing them to process video streams more efficiently. This change not only improved the monitoring capacity but also contributed to significant cost savings.
Reducing the Number of Analyzed Frames:
Instead of analyzing all frames, the team devised a method to intelligently select a subset of frames to analyze. This reduced the computational load and further contributed to cost savings without compromising video quality.
Optimizing the Video Decoding Pipeline:
The Prime Video team implemented optimizations in the video decoding pipeline to improve resource utilization and reduce the time required for decoding video streams. This led to more efficient monitoring and lower costs.
Custom Scheduler Implementation:
A custom scheduler was developed to efficiently allocate resources to the monitoring tasks based on their priority and resource requirements. This scheduler allowed the team to maximize resource utilization and improve the overall monitoring capacity.
Upgrading the Monitoring Infrastructure:
The monitoring infrastructure was upgraded to accommodate the increased monitoring capacity and to take advantage of the cost-saving optimizations. This upgrade further contributed to the significant reduction in costs.
Success Metrics and Outcomes:
The blog post demonstrates the success of the implemented solutions by providing metrics such as a 90% reduction in costs, improved resource utilization, and increased monitoring capacity. These metrics showcase the effectiveness of the optimizations made by the Prime Video team.
Illustration – Redefined Architecture of Prime Video
In conclusion, the blog post highlights the challenges faced by the Prime Video team in monitoring video quality at scale, as well as the comprehensive approach they took to address these challenges. By implementing a series of optimizations and upgrades, the team was able to significantly improve their monitoring service while drastically reducing costs.
References
[1] https://www.primevideotech.com/video-streaming/scaling-up-the-prime-video-audio-video-monitoring-service-and-reducing-costs-by-90
Featured Image by Recklessstudios from Pixabay