r/WebRTC

Hey folks,

Been hacking on a side project called Rendezvous for a while and figured this sub would be the right place to share it. It's a small Zoom-like video conferencing web app built with React + PeerJS, and the whole thing runs without an app server (it's just a static site on GitHub Pages).

https://preview.redd.it/ke1yehmqi72h1.png?width=3164&format=png&auto=webp&s=721b4382f9ebc6a1fa738d7139bcc7293e6b16b5

The idea is pretty simple: instead of doing a full mesh between every participant, the meeting host acts as a relay hub for both chat and media streams. So each client only keeps connections to the host, not to everyone else. Trades off some host bandwidth for avoiding the O(N²) mesh. PeerJS's public broker handles the initial signaling and that's about it.

Honestly I mostly built it because I wanted to see how far we can push WebRTC without any backend, and it turned out more usable than I expected.

Code available at: https://github.com/predatorray/rendezvous
Try it at: https://predatorray.github.io/rendezvous/

Curious if anyone here has tried similar host-as-relay setups for video conferencing, or if there are obvious things I'm missing. Also open to hearing about better ways to handle the media forwarding part.

Hey everyone,

I'm currently dealing with a tricky backend performance bottleneck in a compact, fast-paced baccarat environment.

As the game tempo increases, the betting cycle shortens drastically. This triggers a massive spike in traffic frequency between the client and the server. Because the user's decision-making window is so tight, card distribution and result-calculation APIs are being called consecutively within milliseconds, leading to severe packet accumulation.

Normally, we manage data load by lightweighting the game state data and optimizing the socket connection's keep-alive timeout. However, when the game tempo gets pushed to the absolute extreme, we still run into synchronization errors in real-time result calculations.

We are currently looking into optimizing our event processing routines to reduce infrastructure load while keeping everything perfectly synced. I've been researching architectures like Event Loops with priority queues, or moving some state validation to the edge using a lumix solution setup, but I'm open to better ideas.

For those who have built high-frequency, real-time gaming backends: What is the most efficient event processing routine or pattern to prevent sync lag under extreme load without melting the infrastructure?

Any insights on message brokers (Redis Pub/Sub vs. MQTT) or specific thread/worker pool configurations for this specific micro-window use case would be highly appreciated!

특정 플랫폼의 중계 데이터와 실제 이용량 지표가 동조화되면서 시스템 부하가 특정 시간대에 비정상적으로 집중되는 패턴이 나타납니다. 이는 게임의 구조적 재미보다 방송인의 영향력에 의존하는 콘텐츠 소비 방식이 서버의 트래픽 예측 가시성을 떨어뜨리기 때문입니다. 온카스터디 운영 측면에서는 API 호출 제한을 강화하고 방송 유입 트래픽을 별도 채널로 분산하여 안정성을 확보하는 방향으로 대응합니다. 플랫폼 중계 시 발생하는 데이터 동기화 지연과 시청자 반응 속도 사이의 간극을 기술적으로 어떻게 해결하고 계신가요?