srs/docs/proxy/proxy-load-balancer.md
Winlin 6ee6f1ca5f Proxy: Refactor for testability; add SRT/WHIP E2E and unit tests. v7.0.148 (#4675)
- Refactor the Go proxy for dependency injection: every proxy server,
the bootstrap, the signal handler, the load balancers, and AMF0 now accept
functional-option seams (factories/closures) so tests can inject fakes
without binding real sockets, talking to real Redis, or racing on
package globals.

- Drop the package-global `lb.SrsLoadBalancer`. The bootstrap creates
the LB locally and threads it through every proxy server constructor. Two old
global indirections in `internal/signal` and `internal/rtmp/amf0` are
likewise replaced by per-instance fields.

- Rename `internal/server` → `internal/proxy` and rename the `lb` public
surface for clarity: `SRSLoadBalancer` is split into `OriginService` /
`HLSService` / `RTCService` and recomposed as `OriginLoadBalancer`;
`SRSServer` → `OriginServer`; all proxy server types gain a `Proxy`
qualifier (e.g. `RTMPServer` → `RTMPProxyServer`).

- Extract the Redis client behind a new `internal/redisclient` package
with a minimal `RedisClient` interface and a counterfeiter fake.

- Add counterfeiter fakes (`proxyfakes`, `lbfakes`, `redisclientfakes`)
and ~7.5k lines of unit tests covering bootstrap, memory + Redis LBs, all
five proxy servers, the signal handler, and AMF0.

- Add two new E2E flows — `proxy-e2e-srt-test.sh` (SRT publish through
proxy, verify SRT/RTMP/HTTP-FLV/HLS playback) and `proxy-e2e-whip-test.sh`
(WHIP publish, verify RTMP/HTTP-FLV/HLS via origin `rtc_to_rtmp`) — plus
`setup-ffmpeg-with-whip.sh`, a macOS builder for an ffmpeg with
openssl-DTLS WHIP and SRT support that the two scripts auto-invoke when needed.

- Workspace reorg: move `memory/` and `skills/` to the repo root so all
agent tools (Claude / Codex / Kiro / OpenClaw) share one source of truth via
symlinks. Sync `docs/proxy/proxy-load-balancer.md` and
`memory/srs-codebase-map.md` with the new names.

No protocol, log, HTTP API, or wire-format changes. Refactor only — all
  externally observable proxy behavior is unchanged.

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-authored-by: chatgpt-codex-connector[bot] <199175422+chatgpt-codex-connector[bot]@users.noreply.github.com>
2026-05-17 12:09:07 -04:00

162 lines
5.3 KiB
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**: `OriginLoadBalancer`
- Initialization and lifecycle management
- Server registration and updates
- Stream routing (Pick operation)
- Protocol-specific state management (HLS, WebRTC)
**Data Models**:
- `OriginServer`: 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 |