sdk/python/endpoints/online/managed/debug-online-endpoints-locally-in-visual-studio-code.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Debug online endpoints locally in Visual Studio Code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See the [Debug online endpoints locally in Visual Studio Code](https://docs.microsoft.com/en-us/azure/machine-learning/how-to-debug-managed-online-endpoints-visual-studio-code) for detailed instructions on how to connect to VSCode for debugging. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Launch development container"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "name": "launch-container-1"
   },
   "outputs": [],
   "source": [
    "from azure.ai.ml import MLClient\n",
    "from azure.ai.ml.entities import (\n",
    "    ManagedOnlineEndpoint,\n",
    "    ManagedOnlineDeployment,\n",
    "    Model,\n",
    "    CodeConfiguration,\n",
    "    Environment,\n",
    ")\n",
    "from azure.identity import DefaultAzureCredential"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "name": "launch-container-2"
   },
   "outputs": [],
   "source": [
    "subscription_id = \"<SUBSCRIPTION_ID>\"\n",
    "resource_group = \"<RESOURCE_GROUP>\"\n",
    "workspace_name = \"<AML_WORKSPACE_NAME>\"\n",
    "\n",
    "endpoint_name = \"<ENDPOINT_NAME>\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "name": "launch-container-3"
   },
   "outputs": [],
   "source": [
    "credential = DefaultAzureCredential()\n",
    "ml_client = MLClient(\n",
    "    credential,\n",
    "    subscription_id=subscription_id,\n",
    "    resource_group_name=resource_group,\n",
    "    workspace_name=workspace_name,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "name": "launch-container-4"
   },
   "outputs": [],
   "source": [
    "deployment = ManagedOnlineDeployment(\n",
    "    name=\"blue\",\n",
    "    endpoint_name=endpoint_name,\n",
    "    model=Model(path=\"../model-1/model/sklearn_regression_model.pkl\"),\n",
    "    code_configuration=CodeConfiguration(\n",
    "        code=\"../model-1/onlinescoring\", scoring_script=\"score.py\"\n",
    "    ),\n",
    "    environment=Environment(\n",
    "        conda_file=\"../model-1/environment/conda.yml\",\n",
    "        image=\"mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu20.04\",\n",
    "    ),\n",
    "    instance_type=\"Standard_DS3_v2\",\n",
    "    instance_count=1,\n",
    ")\n",
    "\n",
    "deployment = ml_client.online_deployments.begin_create_or_update(\n",
    "    deployment, local=True, vscode_debug=True\n",
    ").result()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "name": "launch-container-5"
   },
   "source": [
    "## 2. Debug your endpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "endpoint = ml_client.online_endpoints.get(name=endpoint_name, local=True)\n",
    "\n",
    "request_file_path = \"../model-1/sample-request.json\"\n",
    "\n",
    "ml_client.online_endpoints.invoke(endpoint_name, request_file_path, local=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "name": "launch-container-6"
   },
   "outputs": [],
   "source": [
    "print(endpoint)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Edit your endpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "name": "edit-endpoint-1"
   },
   "outputs": [],
   "source": [
    "new_deployment = ManagedOnlineDeployment(\n",
    "    name=\"green\",\n",
    "    endpoint_name=endpoint_name,\n",
    "    model=Model(path=\"../model-2/model/sklearn_regression_model.pkl\"),\n",
    "    code_configuration=CodeConfiguration(\n",
    "        code=\"../model-2/onlinescoring\", scoring_script=\"score.py\"\n",
    "    ),\n",
    "    environment=Environment(\n",
    "        conda_file=\"../model-2/environment/conda.yml\",\n",
    "        image=\"mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu20.04\",\n",
    "    ),\n",
    "    instance_type=\"Standard_DS3_v2\",\n",
    "    instance_count=2,\n",
    ")\n",
    "\n",
    "deployment = ml_client.online_deployments.begin_create_or_update(\n",
    "    new_deployment, local=True, vscode_debug=True\n",
    ").result()"
   ]
  }
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