Merge remote-tracking branch 'origin/main' into mwittwer/normalize_nvidia_user_ownership

# Conflicts:
#	build.py

Author: mattwittwer

CMakeLists.txt

@@ -1,4 +1,4 @@
-# Copyright 2020-2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# Copyright 2020-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
 # modification, are permitted provided that the following conditions
@@ -166,22 +166,9 @@ if (OPENSSL_ROOT_DIR)
   set(_CMAKE_ARGS_OPENSSL_ROOT_DIR "-DOPENSSL_ROOT_DIR:PATH=${OPENSSL_ROOT_DIR}")
 endif()
 
-# Location where protobuf-config.cmake will be installed varies by
-# platform
-if (WIN32)
-  set(_FINDPACKAGE_PROTOBUF_CONFIG_DIR "${TRITON_THIRD_PARTY_INSTALL_PREFIX}/protobuf/cmake")
-else()
-  set(_FINDPACKAGE_PROTOBUF_CONFIG_DIR "${TRITON_THIRD_PARTY_INSTALL_PREFIX}/protobuf/${LIB_DIR}/cmake/protobuf")
-endif()
+set(_FINDPACKAGE_PROTOBUF_CONFIG_DIR "${TRITON_THIRD_PARTY_INSTALL_PREFIX}/protobuf/${LIB_DIR}/cmake/protobuf")
 
-# Triton with Opentelemetry is not supported on Windows
-# FIXME: add location for Windows, when support is added
-# JIRA DLIS-4786
-if (WIN32)
-  set(_FINDPACKAGE_OPENTELEMETRY_CONFIG_DIR "")
-else()
-  set(_FINDPACKAGE_OPENTELEMETRY_CONFIG_DIR "${TRITON_THIRD_PARTY_INSTALL_PREFIX}/opentelemetry-cpp/${LIB_DIR}/cmake/opentelemetry-cpp")
-endif()
+set(_FINDPACKAGE_OPENTELEMETRY_CONFIG_DIR "${TRITON_THIRD_PARTY_INSTALL_PREFIX}/opentelemetry-cpp/${LIB_DIR}/cmake/opentelemetry-cpp")
 
 if (CMAKE_INSTALL_PREFIX_INITIALIZED_TO_DEFAULT)
   set(TRITON_INSTALL_PREFIX ${CMAKE_CURRENT_BINARY_DIR}/install)
@@ -202,7 +189,7 @@ endif() # TRITON_ENABLE_HTTP || TRITON_ENABLE_METRICS || TRITON_ENABLE_SAGEMAKER
 if(${TRITON_ENABLE_GRPC})
   set(TRITON_DEPENDS ${TRITON_DEPENDS} grpc)
 endif() # TRITON_ENABLE_GRPC
-if(NOT WIN32 AND ${TRITON_ENABLE_TRACING})
+if(${TRITON_ENABLE_TRACING})
   set(TRITON_DEPENDS ${TRITON_DEPENDS} opentelemetry-cpp)
 endif() # TRITON_ENABLE_TRACING
 

Dockerfile.sdk

@@ -29,7 +29,7 @@
 #
 
 # Base image on the minimum Triton container
-ARG BASE_IMAGE=nvcr.io/nvidia/tritonserver:26.04-py3-min
+ARG BASE_IMAGE=nvcr.io/nvidia/tritonserver:26.05-py3-min
 
 ARG TRITON_CLIENT_REPO_SUBDIR=clientrepo
 ARG TRITON_REPO_ORGANIZATION=http://github.com/triton-inference-server

README.md

@@ -29,8 +29,8 @@
 
 >[!WARNING]
 >You are currently on the `main` branch which tracks under-development progress
->towards the next release. The current release is version [2.68.0](https://github.com/triton-inference-server/server/releases/latest)
->and corresponds to the 26.04 container release on NVIDIA GPU Cloud (NGC).
+>towards the next release. The current release is version [2.69.0](https://github.com/triton-inference-server/server/releases/latest)
+>and corresponds to the 26.05 container release on NVIDIA GPU Cloud (NGC).
 
 # Triton Inference Server
 
@@ -90,16 +90,16 @@ Inference Server with the
 
 ```bash
 # Step 1: Create the example model repository
-git clone -b r26.04 https://github.com/triton-inference-server/server.git
+git clone -b r26.05 https://github.com/triton-inference-server/server.git
 cd server/docs/examples
 ./fetch_models.sh
 
 # Step 2: Launch triton from the NGC Triton container
-docker run --gpus=1 --rm --net=host -v ${PWD}/model_repository:/models nvcr.io/nvidia/tritonserver:26.04-py3 tritonserver --model-repository=/models --model-control-mode explicit --load-model densenet_onnx
+docker run --gpus=1 --rm --net=host -v ${PWD}/model_repository:/models nvcr.io/nvidia/tritonserver:26.05-py3 tritonserver --model-repository=/models --model-control-mode explicit --load-model densenet_onnx
 
 # Step 3: Sending an Inference Request
 # In a separate console, launch the image_client example from the NGC Triton SDK container
-docker run -it --rm --net=host nvcr.io/nvidia/tritonserver:26.04-py3-sdk /workspace/install/bin/image_client -m densenet_onnx -c 3 -s INCEPTION /workspace/images/mug.jpg
+docker run -it --rm --net=host nvcr.io/nvidia/tritonserver:26.05-py3-sdk /workspace/install/bin/image_client -m densenet_onnx -c 3 -s INCEPTION /workspace/images/mug.jpg
 
 # Inference should return the following
 Image '/workspace/images/mug.jpg':