NVIDIA Triton Management Service (TMS) will reach the end of life on July 31, 2024. The version 1.4.0 is the last release.
Triton Management Service (TMS) is a Kubernetes microservice intended to manage the deployment of AI models on Triton Inference Servers (TIS). The benefit of using TMS over manual or custom deployment solutions comes from TMS in-depth understanding of TIS and GPU hardware, and how they interact with various model frameworks such as PyTorch, TensorFlow, ONNX, and others. TMS strives to balance the deployment of the minimum number of TIS instances with the performance of TIS served AI models.
This container contains the primary server process for managing Triton deployments.
Getting started with Triton Management Service (TMS) Helm Chart
Triton Management Service (TMS) Helm Chart is exclusively available with NVIDIA AI Enterprise.
Before you start, ensure that your environment is set up by following one of the deployment guides available in the NVIDIA AI Enterprise Documentation.
This Helm chart contains installation descriptors which can be used to easily configure and install TMS. For instructions on how to configure and install TMS, please see our TMS installation instructions. For additional information about the values configurable via Helm installation, see our TMS Helm Chart documentation.
For optimal performance, deploy the supported NVIDIA AI Enterprise Infrastructure software with Triton Management Service (TMS).
The latest version of Triton Management Service (TMS) is compatible with:
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