studio-setup.ipynb

{
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   "source": [
    "# Setting up SageMaker Studio\n",
    "\n",
    "Use this notebook to setup SageMaker Studio. You only need to go through the code here once.\n",
    "\n",
    "This notebook is part of the [Machine Learning School](https://www.ml.school) program."
   ]
  },
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n",
      "The dotenv extension is already loaded. To reload it, use:\n",
      "  %reload_ext dotenv\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "%load_ext dotenv\n",
    "%dotenv\n",
    "\n",
    "import os\n",
    "import sys\n",
    "from pathlib import Path\n",
    "\n",
    "CODE_FOLDER = Path(\"code\")\n",
    "CODE_FOLDER.mkdir(parents=True, exist_ok=True)\n",
    "\n",
    "sys.path.append(f\"./{CODE_FOLDER}\")\n",
    "\n",
    "DOMAIN_ID=os.environ[\"DOMAIN_ID\"]\n",
    "USER_PROFILE=os.environ[\"USER_PROFILE\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db6203b0-5a40-4a14-b9bb-6e092f1bb2e7",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Step 1 - Customize Kernel Libraries\n",
    "\n",
    "You can customize SageMaker Studio using Lifecycle configurations. These are shell scripts that will be triggered by lifecycle events, such as starting a new Studio notebook.\n",
    "\n",
    "The following script upgrades the packages on a SageMaker Studio Kernel Application."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "00311496-3a75-4a04-880b-4301a21cb259",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting code/packages.sh\n"
     ]
    }
   ],
   "source": [
    "%%writefile {CODE_FOLDER}/packages.sh\n",
    "\n",
    "#!/bin/bash\n",
    "# This script upgrades the packages on a SageMaker \n",
    "# Studio Kernel Application.\n",
    "\n",
    "set -eux\n",
    "\n",
    "pip install -q --upgrade pip\n",
    "pip install -q --upgrade awscli boto3\n",
    "pip install -q --upgrade scikit-learn==1.3.1\n",
    "pip install -q --upgrade PyYAML==6.0\n",
    "pip install -q --upgrade sagemaker\n",
    "pip install -q --upgrade ipytest"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e640493-d540-40ba-8147-f0094f46ac13",
   "metadata": {},
   "source": [
    "We can now create a new lifecycle configuration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c7b41df5-d6e7-4abe-a04d-8d390a3dea4f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "arn:aws:sagemaker:us-east-1:325223348818:studio-lifecycle-config/ml-school\n",
      "{\n",
      "    \"UserProfileArn\": \"arn:aws:sagemaker:us-east-1:325223348818:user-profile/d-givocgtibv1g/default-1682182522641\"\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "%%bash -s \"$DOMAIN_ID\" \"$USER_PROFILE\" \"$CODE_FOLDER\"\n",
    "\n",
    "DOMAIN_ID=$(echo \"$1\")\n",
    "USER_PROFILE=$(echo \"$2\")\n",
    "\n",
    "LCC_CONTENT=`openssl base64 -A -in $3/packages.sh`\n",
    "\n",
    "aws sagemaker delete-studio-lifecycle-config \\\n",
    "    --studio-lifecycle-config-name ml-school\n",
    "\n",
    "response=$(aws sagemaker create-studio-lifecycle-config \\\n",
    "    --studio-lifecycle-config-name ml-school \\\n",
    "    --studio-lifecycle-config-content $LCC_CONTENT \\\n",
    "    --studio-lifecycle-config-app-type KernelGateway) \n",
    "\n",
    "arn=$(echo \"${response}\" | python3 -c \"import sys, json; print(json.load(sys.stdin)['StudioLifecycleConfigArn'])\")\n",
    "echo \"${arn}\"\n",
    "\n",
    "aws sagemaker update-user-profile --domain-id $DOMAIN_ID \\\n",
    "    --user-profile-name $USER_PROFILE \\\n",
    "    --user-settings '{\n",
    "        \"KernelGatewayAppSettings\": {\n",
    "            \"LifecycleConfigArns\": [\"'$arn'\"]\n",
    "        }\n",
    "    }'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b42c75df-6592-47ac-867a-1ab0955e1653",
   "metadata": {},
   "source": [
    "## Step 2 - Set up Auto-Shutdown\n",
    "\n",
    "The following script configures auto-shutdown of inactive kernels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fb2699a8-1b33-454e-8b62-9b4a2df03bef",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting autoshutdown.sh\n"
     ]
    }
   ],
   "source": [
    "%%writefile {CODE_FOLDER}/autoshutdown.sh\n",
    "\n",
    "#!/bin/bash\n",
    "# This script installs the idle notebook auto-checker server extension to SageMaker Studio\n",
    "# The original extension has a lab extension part where users can set the idle timeout via a Jupyter Lab widget.\n",
    "# In this version the script installs the server side of the extension only. The idle timeout\n",
    "# can be set via a command-line script which will be also created by this create and places into the\n",
    "# user's home folder\n",
    "#\n",
    "# Installing the server side extension does not require Internet connection (as all the dependencies are stored in the\n",
    "# install tarball) and can be done via VPCOnly mode.\n",
    "\n",
    "set -eux\n",
    "\n",
    "# timeout in minutes\n",
    "export TIMEOUT_IN_MINS=60\n",
    "\n",
    "# Should already be running in user home directory, but just to check:\n",
    "cd /home/sagemaker-user\n",
    "\n",
    "# By working in a directory starting with \".\", we won't clutter up users' Jupyter file tree views\n",
    "mkdir -p .auto-shutdown\n",
    "\n",
    "# Create the command-line script for setting the idle timeout\n",
    "cat > .auto-shutdown/set-time-interval.sh << EOF\n",
    "#!/opt/conda/bin/python\n",
    "import json\n",
    "import requests\n",
    "TIMEOUT=${TIMEOUT_IN_MINS}\n",
    "session = requests.Session()\n",
    "# Getting the xsrf token first from Jupyter Server\n",
    "response = session.get(\"http://localhost:8888/jupyter/default/tree\")\n",
    "# calls the idle_checker extension's interface to set the timeout value\n",
    "response = session.post(\"http://localhost:8888/jupyter/default/sagemaker-studio-autoshutdown/idle_checker\",\n",
    "            json={\"idle_time\": TIMEOUT, \"keep_terminals\": False},\n",
    "            params={\"_xsrf\": response.headers['Set-Cookie'].split(\";\")[0].split(\"=\")[1]})\n",
    "if response.status_code == 200:\n",
    "    print(\"Succeeded, idle timeout set to {} minutes\".format(TIMEOUT))\n",
    "else:\n",
    "    print(\"Error!\")\n",
    "    print(response.status_code)\n",
    "EOF\n",
    "chmod +x .auto-shutdown/set-time-interval.sh\n",
    "\n",
    "# \"wget\" is not part of the base Jupyter Server image, you need to install it first if needed to download the tarball\n",
    "sudo yum install -y wget\n",
    "# You can download the tarball from GitHub or alternatively, if you're using VPCOnly mode, you can host on S3\n",
    "wget -O .auto-shutdown/extension.tar.gz https://github.com/aws-samples/sagemaker-studio-auto-shutdown-extension/raw/main/sagemaker_studio_autoshutdown-0.1.5.tar.gz\n",
    "\n",
    "# Or instead, could serve the tarball from an S3 bucket in which case \"wget\" would not be needed:\n",
    "# aws s3 --endpoint-url [S3 Interface Endpoint] cp s3://[tarball location] .auto-shutdown/extension.tar.gz\n",
    "\n",
    "# Installs the extension\n",
    "cd .auto-shutdown\n",
    "tar xzf extension.tar.gz\n",
    "cd sagemaker_studio_autoshutdown-0.1.5\n",
    "\n",
    "# Activate studio environment just for installing extension\n",
    "export AWS_SAGEMAKER_JUPYTERSERVER_IMAGE=\"${AWS_SAGEMAKER_JUPYTERSERVER_IMAGE:-'jupyter-server'}\"\n",
    "if [ \"$AWS_SAGEMAKER_JUPYTERSERVER_IMAGE\" = \"jupyter-server-3\" ] ; then\n",
    "    eval \"$(conda shell.bash hook)\"\n",
    "    conda activate studio\n",
    "fi;\n",
    "pip install --no-dependencies --no-build-isolation -e .\n",
    "jupyter serverextension enable --py sagemaker_studio_autoshutdown\n",
    "if [ \"$AWS_SAGEMAKER_JUPYTERSERVER_IMAGE\" = \"jupyter-server-3\" ] ; then\n",
    "    conda deactivate\n",
    "fi;\n",
    "\n",
    "# Restarts the jupyter server\n",
    "nohup supervisorctl -c /etc/supervisor/conf.d/supervisord.conf restart jupyterlabserver\n",
    "\n",
    "# Waiting for 30 seconds to make sure the Jupyter Server is up and running\n",
    "sleep 30\n",
    "\n",
    "# Calling the script to set the idle-timeout and active the extension\n",
    "/home/sagemaker-user/.auto-shutdown/set-time-interval.sh"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9c4f441-d8e1-4ff9-8553-46272974547d",
   "metadata": {},
   "source": [
    "We can now create a new lifecycle configuration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe4704df-af6a-4c38-8c74-bb690c9f1066",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "%%bash -s \"$DOMAIN_ID\" \"$USER_PROFILE\" \"$CODE_FOLDER\"\n",
    "\n",
    "DOMAIN_ID=$(echo \"$1\")\n",
    "USER_PROFILE=$(echo \"$2\")\n",
    "\n",
    "LCC_CONTENT=`openssl base64 -A -in $3/autoshutdown.sh`\n",
    "\n",
    "aws sagemaker delete-studio-lifecycle-config \\\n",
    "    --studio-lifecycle-config-name autoshutdown 2> /dev/null\n",
    "\n",
    "response=$(aws sagemaker create-studio-lifecycle-config \\\n",
    "    --studio-lifecycle-config-name autoshutdown \\\n",
    "    --studio-lifecycle-config-content $LCC_CONTENT \\\n",
    "    --studio-lifecycle-config-app-type JupyterServer) \n",
    "\n",
    "arn=$(echo \"${response}\" | python3 -c \"import sys, json; print(json.load(sys.stdin)['StudioLifecycleConfigArn'])\")\n",
    "echo \"${arn}\"\n",
    "\n",
    "aws sagemaker update-user-profile --domain-id $DOMAIN_ID \\\n",
    "    --user-profile-name $USER_PROFILE \\\n",
    "    --user-settings '{\n",
    "        \"JupyterServerAppSettings\": {\n",
    "            \"DefaultResourceSpec\": {\n",
    "                \"LifecycleConfigArn\": \"'$arn'\",\n",
    "                \"InstanceType\": \"system\"\n",
    "            },\n",
    "            \"LifecycleConfigArns\": [\"'$arn'\"]\n",
    "        }\n",
    "    }'"
   ]
  }
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