feat: add nixl benchmark deployment instructions (#2060)

benchmarks/nixl/README.md

+# NIXL Benchmark Technical Documentation (Kubernetes)
+
+This guide describes how to run the NIXL benchmark using the provided Docker image on a Kubernetes (K8s) cluster.
+
+---
+
+## Prerequisites
+
+- A running Kubernetes cluster with access to NVIDIA GPUs (e.g., using NVIDIA GPU Operator or device plugin)
+- `kubectl` configured to access your cluster
+- deploy dynamo cloud in a namespace
+
+---
+
+## 1. Prepare the Kubernetes Deployment
+
+A sample deployment YAML is provided in this repository:
+`benchmarks/nixl/nixl-benchmark-deployment.yaml`
+
+Update the image field in sample yaml to appropiate image in your registry.
+
+You can use the `yq` tool to update the image field in the deployment YAML
+```bash
+yq -i '.spec.template.spec.containers[] |= select(.name == "nixl-benchmark") .image = "your-registry/your-nixl-benchmark:your-tag"' benchmarks/nixl/nixl-benchmark-deployment.yaml > nixl-benchmark-deployment.yaml
+```
+
+## 2. Deploy using kubectl
+Launch using the command below:
+
+```bash
+kubectl apply -f  nixl-benchmark-deployment.yaml
+```
\ No newline at end of file

benchmarks/nixl/nixl-benchmark-deployment.yaml

+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: nixl-benchmark
+spec:
+  replicas: 2
+  selector:
+    matchLabels:
+      app: nixl-benchmark
+  template:
+    metadata:
+      labels:
+        app: nixl-benchmark
+    spec:
+      imagePullSecrets:
+        - name: nvcrimagepullsecret
+      containers:
+      - name: nixl-benchmark
+        image: nvcr.io/nvidian/nim-llm-dev/vllm-runtime:nixlbench-e42c07a8
+        command: ["sh", "-c"]
+        args:
+          - "nixlbench -etcd_endpoints http://dynamo-platform-etcd:2379 --target_seg_type VRAM --initiator_seg_type VRAM && sleep infinity"
+        resources:
+          requests:
+            nvidia.com/gpu: "1"
+          limits:
+            nvidia.com/gpu: "1"