When something breaks in a real-time application, users know immediately. There’s no grace period, no hiding behind a loading spinner. Voice, video, chat, and live data platforms demand a higher standard of maintenance and support than traditional web applications. The model you choose to deliver that support
Monitoring call quality in a WebRTC application is harder than it looks. You need consistent telemetry, enough context to interpret what you’re seeing, and dashboards that are actually useful when something goes wrong in production. This post covers how we integrated Peermetrics into an Amazon IVS Real-Time
This project shows how to prototype a real-time voice AI Android app using Gemini 2.0’s Live API over WebSockets as an open-source proof of concept before committing to full production infrastructure. By combining low-level audio control on Android, duplex audio streaming, and multimodal AI, we built an
Expert WebRTC testing is what separates functional real-time applications from reliable ones. A platform that works for two developers on the same high-speed office network can quickly fall apart when hundreds of users try to join simultaneously from coffee shops, firewalled corporate networks, and crowded classrooms. While
