High-Performance Serving with Triton Inference Server
Model repository, model config.pbtxt, concurrent model instances, dynamic batching.
What is Triton
NVIDIA Triton Inference Server is a production serving system that hosts many models at once across CPU and GPU. It supports multiple backends (TensorRT, ONNX, PyTorch, TensorFlow, Python) behind one HTTP/gRPC API, with built-in batching and concurrency.
The Model Repository
Triton loads models from a model repository: a directory where each model has its own folder, a numeric version subfolder, and a config.pbtxt.
model_repository/
resnet50/
config.pbtxt
1/
model.onnx
bert/
config.pbtxt
1/
model.ptAll lessons in this course
- Containerizing ML Models with Docker
- Cloud Deployment: AWS SageMaker
- High-Performance Serving with Triton Inference Server
- Scaling and Auto-Scaling Model Endpoints