Introduction
Model as a Service (MaaS) provides a managed gateway for serving large language models through an OpenAI-compatible API. It gives platform teams a consistent way to publish models, grant access, enforce token quotas, and understand usage, while application developers call the models they are subscribed to with API keys.
MaaS is based on Alauda Build of Envoy Gateway, Alauda Build of Envoy AI Gateway, and Authorino. Envoy Gateway provides the Kubernetes Gateway API foundation, Envoy AI Gateway provides model-aware routing and token accounting, and Authorino authenticates requests. Alauda AI installs and manages these components through the envoyGateway, envoyAIGateway, and authorino components of the default AmlCluster; see Install Alauda AI.
Why use MaaS?
MaaS separates model serving from model consumption:
- Model owners can publish an inference service without exposing its internal route details.
- Administrators can combine models into subscriptions and assign access to users.
- Developers use one OpenAI-compatible gateway instead of learning the URL and authentication method of every backend.
- Platform teams can enforce per-model token quotas and review consumption by user, subscription, model, and token type.
MaaS can expose both platform-hosted inference services and external OpenAI-compatible model providers through the same gateway.
Request flow
For each request, MaaS performs the following checks:
- The caller presents an API key and is authenticated.
- The caller has access to the requested model through an active subscription.
- The subscription has remaining token quota for that user and model.
- The gateway routes the request to the selected model and records the actual token usage returned by the model service.
An unauthenticated or unauthorized request returns 401 or 403. A request that exceeds its subscription quota returns 429.
Quotas are enforced per user, not per API key. Multiple API keys belonging to the same user share the user's allowance for a subscription and model.
Main concepts
Choose a guide
- MaaS Administrator Guide — publish and import models, create subscriptions, configure quotas and guardrails, and review reports.
- MaaS User Guide — create an API key, call a subscribed model, and view personal quota and usage.
Related topics
- Inference Service — create the
LLMInferenceServicemodels that can be published to MaaS. - Authenticating Consumers — authenticate callers and propagate identity to gateway policies.
- Configuring Token Quotas — configure token-based quota enforcement at the inference gateway.
- Metering Token Usage — understand how token consumption is reported.
- Routing to LLM Providers — route external providers through a controlled gateway.