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A serving component that routes requests to different models based on rules, performance, cost, or experimentation policies.
DESCRIPTION
A model router directs inference requests among multiple candidate models or versions using predefined rules or learned policies. It enables A/B tests, canary deployments, fallback paths, and dynamic selection based on latency, accuracy, or cost. Routers can integrate with feature flags, observability, and model registries to automate decisioning. Implementations exist in open platforms like KServe, Seldon, and Ray Serve. Effective routing reduces cost and risk while accelerating iteration on model quality.
ALTERNATIVE DEFINITIONS
KServe
A Router node routes the request to one of the child nodes based on user specified rules.
Defines a router within an inference graph for conditional request flow.
Ray Serve
Ray Serve allows you to split traffic between deployments using a traffic policy.
Emphasizes traffic splitting as a routing mechanism across deployments.
Seldon Core
Routers can be used to direct a request to a particular model based on configurable logic.
Highlights configurable logic for directing requests in a model graph.
RELATED TERMS
Model Gateway A/B Testing Canary Release Ensemble Load Balancer Traffic Splitting Latency Optimization Cost Optimization
COMPETING TERMS
Single-Model Endpoint
RELATIONS
- Broader: Router
KNOWLEDGE AREAS
MLOps AI Platform & Tooling Observability & Telemetry
TARGET AUDIENCE
MLOps Engineer AI Engineer Data Scientist Solution Architect Cloud Architect
EXTERNAL SOURCES
- Wikipedia - A/B testing
- KServe - Inference graph routers
- Ray Serve - Model serving and routing
- Seldon Core - Routers in inference graphs
TOP QUESTIONS
What problems does a Model Router solve?
It enables dynamic model selection, A/B testing, canary deployments, and graceful fallbacks, improving reliability and experimentation velocity.
Category: Definition
How does a Model Router differ from a load balancer?
Routers apply model-aware policies (accuracy, cost) rather than purely distributing traffic for availability.
Category: Misunderstanding
What are common routing strategies?
Static rules, weighted traffic splits, performance-based selection, and risk-aware fallbacks are common strategies.
Category: Example
What’s a common mistake with model routing?
Ignoring monitoring and feedback loops; without metrics, routing policies can degrade performance over time.
Category: Mistakes
How is a Model Router measured?
Latency, error rate, cost per request, and outcome quality (e.g., accuracy) guide policy tuning.
Category: Requirements
What risks come with model routing?
Policy misconfiguration or drift can direct traffic to underperforming models, harming user experience.
Category: Risks
Where should a Model Router run?
Commonly in the serving layer near inference endpoints, integrated with feature flags and observability.
Category: Management
What’s hot around model routing today?
Context-aware routing using online evaluation and bandit algorithms is gaining traction.
Category: Topic
How to start implementing a Model Router?
Use platforms like KServe, Ray Serve, or Seldon for inference graphs and traffic policies, then iterate with metrics.
Category: Learning