sglang_v0.5.2/sglang/docs/advanced_features/router.md

SGLang Router

The SGLang Router is a high-performance request distribution system that routes inference requests across multiple SGLang runtime instances. It features cache-aware load balancing, fault tolerance, and support for advanced deployment patterns including data parallelism and prefill-decode disaggregation.

Key Features

• Cache-Aware Load Balancing: Optimizes cache utilization while maintaining balanced load distribution
• Multiple Routing Policies: Choose from random, round-robin, cache-aware, or power-of-two policies
• Fault Tolerance: Automatic retry and circuit breaker mechanisms for resilient operation
• Dynamic Scaling: Add or remove workers at runtime without service interruption
• Kubernetes Integration: Native service discovery and pod management
• Prefill-Decode Disaggregation: Support for disaggregated serving load balancing
• Prometheus Metrics: Built-in observability and monitoring

Installation

pip install sglang-router

Quick Start

To see all available options:

python -m sglang_router.launch_server --help  # Co-launch router and workers
python -m sglang_router.launch_router --help  # Launch router only

Deployment Modes

The router supports three primary deployment patterns:

1. Co-launch Mode: Router and workers launch together (simplest for single-node deployments)
2. Separate Launch Mode: Router and workers launch independently (best for multi-node setups)
3. Prefill-Decode Disaggregation: Specialized mode for disaggregated serving

Mode 1: Co-launch Router and Workers

This mode launches both the router and multiple worker instances in a single command. It's the simplest deployment option and replaces the --dp-size argument of SGLang Runtime.

# Launch router with 4 workers
python -m sglang_router.launch_server \
    --model-path meta-llama/Meta-Llama-3.1-8B-Instruct \
    --dp-size 4 \
    --host 0.0.0.0 \
    --port 30000

Sending Requests

Once the server is ready, send requests to the router endpoint:

import requests

# Using the /generate endpoint
url = "http://localhost:30000/generate"
data = {
    "text": "What is the capital of France?",
    "sampling_params": {
        "temperature": 0.7,
        "max_new_tokens": 100
    }
}

response = requests.post(url, json=data)
print(response.json())

# OpenAI-compatible endpoint
url = "http://localhost:30000/v1/chat/completions"
data = {
    "model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
    "messages": [{"role": "user", "content": "What is the capital of France?"}]
}

response = requests.post(url, json=data)
print(response.json())

Mode 2: Separate Launch Mode

This mode is ideal for multi-node deployments where workers run on different machines.

Step 1: Launch Workers

On each worker node:

# Worker node 1
python -m sglang.launch_server \
    --model-path meta-llama/Meta-Llama-3.1-8B-Instruct \
    --host 0.0.0.0 \
    --port 8000

# Worker node 2
python -m sglang.launch_server \
    --model-path meta-llama/Meta-Llama-3.1-8B-Instruct \
    --host 0.0.0.0 \
    --port 8001

Step 2: Launch Router

On the router node:

python -m sglang_router.launch_router \
    --worker-urls http://worker1:8000 http://worker2:8001 \
    --host 0.0.0.0 \
    --port 30000 \
    --policy cache_aware  # or random, round_robin, power_of_two

Mode 3: Prefill-Decode Disaggregation

This advanced mode separates prefill and decode operations for optimized performance:

python -m sglang_router.launch_router \
    --pd-disaggregation \
    --prefill http://prefill1:8000 9000 \
    --prefill http://prefill2:8001 9001 \
    --decode http://decode1:8002 \
    --decode http://decode2:8003 \
    --prefill-policy cache_aware \
    --decode-policy round_robin

Understanding --prefill Arguments

The --prefill flag accepts URLs with optional bootstrap ports:

• --prefill http://server:8000 - No bootstrap port
• --prefill http://server:8000 9000 - Bootstrap port 9000
• --prefill http://server:8000 none - Explicitly no bootstrap port

Policy Inheritance in PD Mode

The router intelligently handles policy configuration for prefill and decode nodes:

1. Only --policy specified: Both prefill and decode nodes use this policy
2. --policy and --prefill-policy specified: Prefill nodes use --prefill-policy, decode nodes use --policy
3. --policy and --decode-policy specified: Prefill nodes use --policy, decode nodes use --decode-policy
4. All three specified: Prefill nodes use --prefill-policy, decode nodes use --decode-policy (main --policy is ignored)

Example with mixed policies:

python -m sglang_router.launch_router \
    --pd-disaggregation \
    --prefill http://prefill1:8000
    --prefill http://prefill2:8000 \
    --decode http://decode1:8001
    --decode http://decode2:8001 \
    --policy round_robin \
    --prefill-policy cache_aware  # Prefill uses cache_aware and decode uses round_robin from --policy

PD Mode with Service Discovery

For Kubernetes deployments with separate prefill and decode server pools:

python -m sglang_router.launch_router \
    --pd-disaggregation \
    --service-discovery \
    --prefill-selector app=prefill-server tier=gpu \
    --decode-selector app=decode-server tier=cpu \
    --service-discovery-namespace production \
    --prefill-policy cache_aware \
    --decode-policy round_robin

Dynamic Scaling

The router supports runtime scaling through REST APIs:

Adding Workers

# Launch a new worker
python -m sglang.launch_server \
    --model-path meta-llama/Meta-Llama-3.1-8B-Instruct \
    --port 30001

# Add it to the router
curl -X POST "http://localhost:30000/add_worker?url=http://127.0.0.1:30001"

Removing Workers

curl -X POST "http://localhost:30000/remove_worker?url=http://127.0.0.1:30001"

Note: When using cache-aware routing, removed workers are cleanly evicted from the routing tree and request queues.

Fault Tolerance

The router includes comprehensive fault tolerance mechanisms:

Retry Configuration

python -m sglang_router.launch_router \
    --worker-urls http://worker1:8000 http://worker2:8001 \
    --retry-max-retries 3 \
    --retry-initial-backoff-ms 100 \
    --retry-max-backoff-ms 10000 \
    --retry-backoff-multiplier 2.0 \
    --retry-jitter-factor 0.1

Circuit Breaker

Protects against cascading failures:

python -m sglang_router.launch_router \
    --worker-urls http://worker1:8000 http://worker2:8001 \
    --cb-failure-threshold 5 \
    --cb-success-threshold 2 \
    --cb-timeout-duration-secs 30 \
    --cb-window-duration-secs 60

Behavior:

• Worker is marked unhealthy after cb-failure-threshold consecutive failures
• Returns to service after cb-success-threshold successful health checks
• Circuit breaker can be disabled with --disable-circuit-breaker

Routing Policies

The router supports multiple routing strategies:

1. Random Routing

Distributes requests randomly across workers.

--policy random

2. Round-Robin Routing

Cycles through workers in order.

--policy round_robin

3. Power of Two Choices

Samples two workers and routes to the less loaded one.

--policy power_of_two

4. Cache-Aware Load Balancing (Default)

The most sophisticated policy that combines cache optimization with load balancing:

--policy cache_aware \
--cache-threshold 0.5 \
--balance-abs-threshold 32 \
--balance-rel-threshold 1.0001

How It Works

1. Load Assessment: Checks if the system is balanced

   • Imbalanced if: (max_load - min_load) > balance_abs_threshold AND max_load > balance_rel_threshold * min_load

2. Routing Decision:

   • Balanced System: Uses cache-aware routing
     • Routes to worker with highest prefix match if match > cache_threshold
     • Otherwise routes to worker with most available cache capacity
   • Imbalanced System: Uses shortest queue routing to the least busy worker

3. Cache Management:

   • Maintains approximate radix trees per worker
   • Periodically evicts LRU entries based on --eviction-interval-secs and --max-tree-size

Data Parallelism Aware Routing

Enables fine-grained control over data parallel replicas:

--dp-aware \
--api-key your_api_key  # Required for worker authentication

This mode coordinates with SGLang's DP controller for optimized request distribution across data parallel ranks.

Configuration Reference

Core Settings

Parameter	Type	Default	Description
--host	str	127.0.0.1	Router server host address
--port	int	30000	Router server port
--worker-urls	list	[]	Worker URLs for separate launch mode
--policy	str	cache_aware	Routing policy (random, round_robin, cache_aware, power_of_two)
--max-concurrent-requests	int	64	Maximum concurrent requests (rate limiting)
--request-timeout-secs	int	600	Request timeout in seconds
--max-payload-size	int	256MB	Maximum request payload size

Cache-Aware Routing Parameters

Parameter	Type	Default	Description
--cache-threshold	float	0.5	Minimum prefix match ratio for cache routing (0.0-1.0)
--balance-abs-threshold	int	32	Absolute load difference threshold
--balance-rel-threshold	float	1.0001	Relative load ratio threshold
--eviction-interval-secs	int	60	Seconds between cache eviction cycles
--max-tree-size	int	16777216	Maximum nodes in routing tree

Fault Tolerance Parameters

Parameter	Type	Default	Description
--retry-max-retries	int	3	Maximum retry attempts per request
--retry-initial-backoff-ms	int	100	Initial retry backoff in milliseconds
--retry-max-backoff-ms	int	10000	Maximum retry backoff in milliseconds
--retry-backoff-multiplier	float	2.0	Backoff multiplier between retries
--retry-jitter-factor	float	0.1	Random jitter factor for retries
--disable-retries	flag	False	Disable retry mechanism
--cb-failure-threshold	int	5	Failures before circuit opens
--cb-success-threshold	int	2	Successes to close circuit
--cb-timeout-duration-secs	int	30	Circuit breaker timeout duration
--cb-window-duration-secs	int	60	Circuit breaker window duration
--disable-circuit-breaker	flag	False	Disable circuit breaker

Prefill-Decode Disaggregation Parameters

Parameter	Type	Default	Description
--pd-disaggregation	flag	False	Enable PD disaggregated mode
--prefill	list	[]	Prefill server URLs with optional bootstrap ports
--decode	list	[]	Decode server URLs
--prefill-policy	str	None	Routing policy for prefill nodes (overrides --policy)
--decode-policy	str	None	Routing policy for decode nodes (overrides --policy)
--worker-startup-timeout-secs	int	300	Timeout for worker startup
--worker-startup-check-interval	int	10	Interval between startup checks

Kubernetes Integration

Parameter	Type	Default	Description
--service-discovery	flag	False	Enable Kubernetes service discovery
--selector	list	[]	Label selector for workers (key1=value1 key2=value2)
--prefill-selector	list	[]	Label selector for prefill servers in PD mode
--decode-selector	list	[]	Label selector for decode servers in PD mode
--service-discovery-port	int	80	Port for discovered pods
--service-discovery-namespace	str	None	Kubernetes namespace to watch
--bootstrap-port-annotation	str	sglang.ai/bootstrap-port	Annotation for bootstrap ports

Observability

Parameter	Type	Default	Description
--prometheus-port	int	29000	Prometheus metrics port
--prometheus-host	str	127.0.0.1	Prometheus metrics host
--log-dir	str	None	Directory for log files
--log-level	str	info	Logging level (debug, info, warning, error, critical)
--request-id-headers	list	None	Custom headers for request tracing

CORS Configuration

Parameter	Type	Default	Description
--cors-allowed-origins	list	[]	Allowed CORS origins

Advanced Features

Kubernetes Service Discovery

Automatically discover and manage workers in Kubernetes:

Standard Mode

python -m sglang_router.launch_router \
    --service-discovery \
    --selector app=sglang-worker env=prod \
    --service-discovery-namespace production \
    --service-discovery-port 8000

Prefill-Decode Disaggregation Mode

python -m sglang_router.launch_router \
    --pd-disaggregation \
    --service-discovery \
    --prefill-selector app=prefill-server env=prod \
    --decode-selector app=decode-server env=prod \
    --service-discovery-namespace production

Note: The --bootstrap-port-annotation (default: sglang.ai/bootstrap-port) is used to discover bootstrap ports for prefill servers in PD mode. Prefill pods should have this annotation set to their bootstrap port value.

Prometheus Metrics

Expose metrics for monitoring:

python -m sglang_router.launch_router \
    --worker-urls http://worker1:8000 http://worker2:8001 \
    --prometheus-port 29000 \
    --prometheus-host 0.0.0.0

Metrics available at http://localhost:29000/metrics

Request Tracing

Enable request ID tracking:

python -m sglang_router.launch_router \
    --worker-urls http://worker1:8000 http://worker2:8001 \
    --request-id-headers x-request-id x-trace-id

Troubleshooting

Common Issues

1. Workers not connecting: Ensure workers are fully initialized before starting the router. Use --worker-startup-timeout-secs to increase wait time.

2. High latency: Check if cache-aware routing is causing imbalance. Try adjusting --balance-abs-threshold and --balance-rel-threshold.

3. Memory growth: Reduce --max-tree-size or decrease --eviction-interval-secs for more aggressive cache cleanup.

4. Circuit breaker triggering frequently: Increase --cb-failure-threshold or extend --cb-window-duration-secs.

Debug Mode

Enable detailed logging:

python -m sglang_router.launch_router \
    --worker-urls http://worker1:8000 http://worker2:8001 \
    --log-level debug \
    --log-dir ./router_logs