I am developing a web-based photo and video editing application, and I’m encountering performance issues with video processing tasks, especially when dealing with high-resolution videos. Here are some specifics about the current setup:

The app is built using JavaScript for the frontend and Python (with Flask) for the backend.
Video processing tasks include filtering, trimming, and adding effects, handled primarily by FFmpeg on the server side.
Videos are uploaded by users and stored in an AWS S3 bucket.
What are some effective strategies or techniques to optimize the performance of video processing algorithms in this context? Specifically, I’m interested in:

Reducing latency and processing time for video edits.
Best practices for integrating FFmpeg with a web application to handle concurrent processing tasks efficiently.
Utilizing cloud resources (e.g., AWS Lambda, EC2) to scale processing power dynamically.
Any code examples, libraries, or architectural recommendations that could help improve the efficiency and speed of video processing in a web-based application would be greatly [appreciated]!

Best regards
Adeel Ahmad

What I’ve Tried:

Multi-threading in Python:

Approach: Implemented multi-threading to handle multiple video processing tasks concurrently.
Outcome: While this improved the handling of multiple tasks, it didn’t significantly reduce the processing time for individual video tasks due to the Global Interpreter Lock (GIL) in Python.
Caching Mechanisms:

Approach: Implemented caching to store and reuse processed video segments. Used a Redis cache to store metadata and frequently accessed video segments.
Outcome: This approach reduced the need to reprocess the same video segments, thus saving some processing time. However, the initial processing time for new segments remained high.
Optimizing FFmpeg Commands:

Approach: Tweaked FFmpeg command options to use faster encoders and adjusted parameters to balance quality and speed.
Outcome: Saw marginal improvements in processing times, but the overall performance was still not meeting the desired benchmarks.
What I Expected:

Significant Reduction in Video Processing Time: Expected that multi-threading and optimized FFmpeg commands would substantially cut down the processing time for each video task.
Improved User Experience: Anticipated faster response times for video editing tasks, leading to a smoother user experience.
Efficient Concurrent Processing: Hoped that handling multiple video processing tasks concurrently would not overload the server, maintaining consistent performance even under high load.