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• Implementing Live Streaming Webinar Architecture - Need Guidance

  21 September 2023, by vishnugpl

  Question : I'm working on a project to implement a live streaming webinar platform, and I'm looking for guidance on the architecture and technologies to use. I have some specific requirements and constraints, and I'd appreciate any advice or pointers on how to get started.

  


  Context:
I'm tasked with building a live streaming webinar platform from scratch for our organization. Here are some key requirements and constraints:

  


  


  1. Live Video Streaming: We need to support live video streaming for
webinars, workshops, and conferences. Low latency is crucial for
real-time interaction between presenters and attendees.

     


  


  2. Scalability: The platform should be able to handle a large number of concurrent attendees, potentially thousands or more,
without compromising performance.

     


  


  3. Security: Security is a top priority. We need to ensure that only authorized users can access the webinars, and we must protect
against unauthorized recording or distribution of the content.

     


  


  4. User Interaction: Attendees should be able to ask questions, participate in polls, and interact with presenters in real-time.

     


  


  5. Recording and Playback: We also want to provide recorded versions of past webinars for on-demand viewing (HLS).

     


  


  


  Current Tech Stack:

  


  

  • Frontend: React

  


  • Backend: Node.js with Express

  


  • Database: MongoDB

  


  • Cloud Hosting: AWS

  


  


  Questions:

  


  


  • What technologies or services are best suited for handling live video streaming with low latency?

    


  


  • How can I ensure scalability in terms of both video streaming and handling a large number of users?

    


  


  • What security measures should I consider to protect the content and user data?

    


  


  • Are there any recommended frameworks or libraries for building interactive features like real-time chat and polling?

    


  


  • What's the best approach for recording and serving on-demand webinar content?

    


  


  


  Additional Information:

  


  


  • Budget is a consideration, so cost-effective solutions are preferred.

    


  


  • Any open-source or third-party tools that can simplify development are welcome.

    


  


  • I have experience with AWS, but I'm open to other cloud providers if they offer advantages for this project.

    


  


  


• Live streaming of processed frames to AWS

  22 April 2021, by MinasCham

  I'm working on a project where i need to capture live video feed from an RTSP camera source, process the video frame-by-frame and stream the result to an AWS Service.

  


  So far, my solution:

  


  

  • Captures frames from the RTSP camera source using OpenCV and performs some processing.

  


  • Feeds the processed frames to an ffmpeg pipe that packages the content for online streaming (HTTP Live Streaming - hls) and saves it locally.

  


  • Transfers the media content to an Amazon Kinesis Video Stream using a Gstreamer pipeline element with kvssink as a sink element.

  


  


  My questions are:

  


  

  • Currently I'm saving the content both locally and on an Amazon Kinesis Video Stream. Is this efficient?

  


  • Is it possible to directly stream the frames to the Amazon kinesis Video Stream (perhaps by connecting the ffmpeg output with the gstreamer pipeline element)?

  


  • Is the file format suitable for this implementation or would it better to encode the media differently?

  


  


• Scenecut detection and consistent GOP size - adaptive streaming

  24 March 2014, by Tarun

  Sample Command:

  -map 0:0 -f mp4 -vcodec libx264 -preset slow -profile:v main -vf scale="640:trunc(ow/a/2)*2" -vb 700k -minrate 650k -maxrate 750k -bufsize 10000k -an -g 48 -x264opts keyint=48:min-keyint=10:scenecut=40 -flags +cgop -sc_threshold 40 -pix_fmt yuv420p -threads 0 -y

  There is as such no error in encoding, But I wanted to understand following points-

  1) the above command will ensure that range of GOP size is 10,48, and if any scene change value (frame1 to fame2) is >40%, then a keyframe is introduced there?

  2) So that means in a 3 hours of source video, there is no guarantee that GOP size will remain same

  3) No consider, I am creating 7 MP4 files each with different bitrate and resolution. (These Mp4s will be encoded to smooth in later stage). Hence i am targeting adaptive streaming. But when I did that, I found that if GOP sizes were not consistent across each bitrates. What I mean by this is, for ex: if in Bitrate1 - GOP size is like 10, 20, 48 and so on, in other bitrates it wasnt in the same sequence. I hope my question makes sense.

  So is there a way to ensure that GOP size may vary across one single output. But it should be consistent across each bitrate provided that the source is same?

  Also for adaptive streaming Is scenecut detection advisable?