A complete solution for live streaming stability assurance
Preventing live streaming jams requires a system-level failure response strategy:
- Preprocessing Configuration::
- exist
docker-compose.ymlAdd a health check:healthcheck:
test: ["CMD", "curl", "-f", "http://localhost/health"]
interval: 30s - set up
restart: unless-stoppedEnabling automatic recovery
- exist
- Real-time monitoring measures::
- (of a computer) run
docker statsMonitor CPU/Memory Usage - Install Grafana Kanban (provided with the project)
monitoring/dashboard.json)
- (of a computer) run
- Degradation plan::
- Automatically switch to local mini-model when high latency is detected (modification)
fallback_model(Parameters) - Speech synthesis timeout 3 seconds after switching to text pop-up replies
- Automatically switch to local mini-model when high latency is detected (modification)
Hardware Recommended Configuration:
minimum requirement: 4-core CPU/8GB RAM/Solid State Drive
Live Optimization Configuration::
- Discrete graphics card (supports CUDA accelerated Bert-VITS2)
- Professional sound card (reduces audio processing delays)
- Alternate network connection (4G hotspot emergency switching)
This answer comes from the articleVirtualWife: A secondary digital person that supports B-station live streaming and voice interactionThe
May not be reproduced without permission:AI productivity tools " How can I avoid long unresponsive states of VirtualWife during live streaming?
