ossrs/srs

SRS is a simple, high-performance, AI-driven real-time media server supporting RTMP, WebRTC, HLS, HTTP-FLV, HTTP-TS, SRT, MPEG-DASH, and GB28181, with codec...

View on GitHub ↗Jump to charts ↓Open shareable report

Summary Information

Updated 26 minutes ago
Added to GitGenius on September 1st, 2026
Created on April 29th, 2015
Open Issues & Pull Requests: 6 (+0)
GitHub issues: Enabled
Number of forks: 5,693
Total Stargazers: 29,215 (+0)
Total Subscribers: 820 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 45.8 hours
Mean response time: 39.3 days
90th percentile: 159.3 days
Tracked items: 424

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Work labelled "Enhancement" is answered fastest, typically in about 19 hours, while "AI Handled" waits about 6 days. Only 6% of issues opened in the past year have been closed. Three people close 88% of everything that gets resolved.

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 5
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 90 days
Stale 30+ days: 3
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 2

Top labels

  • TransByAI (253)
  • EnglishNative (198)
  • WebRTC (47)
  • Bug (44)
  • AI Handled (24)
  • Feature (24)
  • Enhancement (17)
  • good first issue (16)

Most active issues this week

Detailed Description

SRS is a real-time media server that ingests and distributes live streams across multiple protocols including RTMP, WebRTC, HLS, HTTP-FLV, SRT, MPEG-DASH, and GB28181.

The tool addresses the need for a unified streaming infrastructure capable of handling diverse input and output formats while maintaining low latency. It achieves this through a single-node architecture written in C++ that accepts streams in one protocol and transcodes or relays them to multiple output formats simultaneously. The server supports a broad range of video codecs (H.264, H.265, AV1, VP9) and audio codecs (AAC, Opus, G.711), allowing it to work with content from various sources and serve different client requirements.

Adoption suits organizations building live-streaming platforms, video conferencing systems, or broadcast infrastructure where protocol flexibility and performance matter. The tool runs on Linux and macOS across multiple architectures including x86_64, ARM variants, and RISC-V, making it deployable in diverse environments from cloud servers to edge devices. Docker deployment is recommended for simplified setup. The README does not position the tool against named alternatives, so no comparative guidance can be offered.

The project maintains active continuous integration with automated code quality analysis and release workflows. Development activity shows consistent engagement across multiple communication channels including Discord and Telegram communities. The codebase includes code coverage tracking, indicating attention to test quality and reliability.