srs/docs/proxy/proxy-load-balancer.md
Winlin ebf8b712c9 Proxy: restructure repo as Go project with proxy as first module (#4652)
Reorganize the SRS (Simple Realtime Server) repository to
follow a conventional Go project structure, setting the stage for a
progressive transition from a C++ project to a Go project. The proxy,
which was once contained within its own `proxy/` subdirectory, will now
be converted into the initial Go module located at the root of the
repository, serving as a template for subsequent Go modules.

- **Go module at repo root:** `go.mod` moved to repo root, module
renamed from `proxy` to `srsx`. The repo is now a proper Go project with
`cmd/` and `internal/` at the top level.
- **Elevation of Proxy Code:** Move the proxy code from
`proxy/cmd/proxy-go/` to `cmd/proxy/`, and from `proxy/internal/` to
`internal/`. The proxy serves as the inaugural application; subsequent
modules (for instance, `cmd/origin`) will mimic this arrangement.
- **Documentation Restructured:** Transfer the documentation from
`proxy/docs/` to `docs/proxy/`, revise the main README to endorse
OpenClaw as the preferred AI tool, and update `proxy/README.md` to point
to the new documentation locations.
- **Build and config:** `Makefile` moved to root, `PROXY_STATIC_FILES`
default path corrected for the new layout, `.gitignore` consolidated.
- **Cleanup:** removed standalone `proxy/LICENSE` (repo-level license
applies), all internal imports updated to `srsx/internal/...`.
- **OpenClaw workspace:** added community bot info, git workflow
conventions, and support group behavior guidance.

This restructuring was performed by OpenClaw orchestrating Claude Code
and Codex via ACP.

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: chatgpt-codex-connector[bot] <199175422+chatgpt-codex-connector[bot]@users.noreply.github.com>
2026-03-22 08:11:28 -04:00

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Markdown

# Load Balancer
## Overview
The proxy load balancer distributes client streams across multiple backend origin servers. It provides a pluggable interface with two implementations:
1. **Memory Load Balancer** - For single proxy deployments
2. **Redis Load Balancer** - For multi-proxy deployments with shared state
Both implementations maintain stream-to-server mappings to ensure stream consistency - once a stream is assigned to a backend server, all subsequent requests for that stream route to the same server.
## Core Responsibilities
1. Server Management
**Backend Server Registration**:
- Origin servers register themselves with the proxy via System API
- Servers provide their endpoints for each protocol (RTMP, HTTP, WebRTC, SRT)
- Registration includes server identity (ServerID, ServiceID, PID)
- Heartbeat mechanism maintains server health status
**Server Selection**:
- Pick appropriate backend server for new streams
- Consider server health (last heartbeat time)
- Random selection from healthy servers for load distribution
- Maintain stream-to-server mapping for consistency
2. Stream State Management
**Protocol-Specific State**:
- **HLS Streams**: Dual-index storage for M3U8 playlists and TS segments
- Index by stream URL for initial playlist requests
- Index by SPBHID (SRS Proxy Backend HLS ID) for segment requests
- **WebRTC Connections**: Dual-index for session management
- Index by stream URL for initial connection setup
- Index by ufrag (ICE username) for STUN binding requests
3. Load Balancing Strategy
**Stream-Level Stickiness**:
- First request for a stream selects a backend server
- All subsequent requests for that stream use the same server
- Ensures session continuity and state consistency on backend
**Health-Based Selection**:
- Only consider servers with recent heartbeats (within 300 seconds)
- Fallback to any registered server if no healthy servers available
- Random selection among healthy servers for even distribution
## Architecture
The load balancer uses a clean interface-based architecture:
**Core Interface**: `SRSLoadBalancer`
- Initialization and lifecycle management
- Server registration and updates
- Stream routing (Pick operation)
- Protocol-specific state management (HLS, WebRTC)
**Data Models**:
- `SRSServer`: Backend origin server representation
- `HLSPlayStream`: Interface for HLS streaming sessions
- `RTCConnection`: Interface for WebRTC connections
## Memory Load Balancer
1. Design
**Storage**: In-memory maps for fast access
- Server registry with thread-safe concurrent access
- Stream-to-server mappings
- Protocol-specific session state (HLS, WebRTC)
**Use Case**: Single proxy instance handling moderate stream counts
**Characteristics**:
- Lowest latency (no network operations)
- Simple deployment (no external dependencies)
- State limited to single proxy instance
- Best for deployments where proxy isn't the bottleneck
2. Configuration
```bash
PROXY_LOAD_BALANCER_TYPE=memory
```
## Redis Load Balancer
1. Design
**Storage**: Shared Redis instance for distributed state
- All proxies read/write to same Redis
- TTL-based expiration for automatic cleanup
- JSON serialization for cross-process communication
**Use Case**: Multiple proxy instances sharing load
**Characteristics**:
- Enables horizontal scaling of proxies
- Higher latency (network + serialization overhead)
- Requires Redis infrastructure
- Best for large deployments with many streams
2. Configuration
```bash
PROXY_LOAD_BALANCER_TYPE=redis
PROXY_REDIS_HOST=127.0.0.1
PROXY_REDIS_PORT=6379
PROXY_REDIS_PASSWORD=
PROXY_REDIS_DB=0
```
3. Redis Key Design
**Server Keys**:
- `srs-proxy-server:{serverID}` - Server registration (300s TTL)
- `srs-proxy-all-servers` - Server list index (no expiration)
**Stream Mapping Keys**:
- `srs-proxy-url:{streamURL}` - Stream-to-server mapping (no expiration)
**Session State Keys**:
- `srs-proxy-hls:{streamURL}` - HLS by URL (120s TTL)
- `srs-proxy-spbhid:{spbhid}` - HLS by SPBHID (120s TTL)
- `srs-proxy-rtc:{streamURL}` - WebRTC by URL (120s TTL)
- `srs-proxy-ufrag:{ufrag}` - WebRTC by ufrag (120s TTL)
## Expiration and Cleanup
**Server Heartbeat**: 300 seconds
- Servers must send updates every 30 seconds (recommended)
- Considered dead if no update within 300 seconds
- Memory LB: filtered during selection
- Redis LB: automatic TTL expiration
**Session State**: 120 seconds
- HLS and WebRTC sessions expire after 120 seconds of inactivity
- Automatic cleanup via TTL (Redis) or garbage collection (Memory)
- Sessions renewed on each request
**Stream Mappings**: No expiration
- Stream-to-server mappings persist indefinitely
- Ensures consistent routing for long-running streams
- Only reset when backend server dies or mapping explicitly cleared
## Comparison: Memory vs Redis
| Aspect | Memory Load Balancer | Redis Load Balancer |
|--------|---------------------|---------------------|
| **Deployment** | Single proxy | Multiple proxies |
| **State Storage** | Local memory | Shared Redis |
| **Latency** | Lowest (in-process) | Network + serialization |
| **Scalability** | Single instance | Horizontal scaling |
| **Dependencies** | None | Redis required |
| **Complexity** | Simple | Moderate |
| **Fault Tolerance** | Single point of failure | Multiple proxies |
| **Best For** | Moderate traffic | High traffic, high availability |