Triton Mock (ailab-ml)
What It Is
A lightweight mock of NVIDIA Triton Inference Server implementing the KServe v2 protocol. It exposes server metadata, model management, inference, and shared memory endpoints.
Surface
| Endpoint |
Purpose |
GET /v2 |
Server metadata (name, version, extensions) |
GET /v2/health/ready |
Readiness probe |
GET /v2/health/live |
Liveness probe |
GET /v2/models |
Model listing (acme-fraud-detector, acme-embeddings) |
GET /v2/models/{name} |
Model metadata (inputs, outputs, platform) |
GET /v2/models/{name}/config |
Model configuration (backend, instances, max batch) |
POST /v2/models/{name}/infer |
Inference endpoint |
POST /v2/repository/index |
Repository index (all models with state) |
POST /v2/repository/models/{name}/load |
Load model |
POST /v2/repository/models/{name}/unload |
Unload model |
GET /v2/systemsharedmemory/status |
System shared memory regions |
GET /v2/cudasharedmemory/status |
CUDA shared memory regions |
Port & Unit
| Parameter |
Value |
| Host |
172.16.50.20 |
| Port |
8500 |
| Unit |
triton-mock.service |
| Runtime |
python3 server.py |
What aipostex Finds
- Triton fingerprint via
/v2 server metadata
- Model enumeration with full input/output tensor definitions
- Unauthenticated model management (load, unload via repository API)
- Shared memory status exposing system internals