06-model-deployment.ipynb

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   "source": [
    "# 06 - Model Deployment\n",
    "\n",
    "The purpose of this notebook is to execute a CI/CD routine to test and deploy the trained model to `Vertex AI` as an `Endpoint` for online prediction serving. The notebook covers the following steps:\n",
    "1. Run the test steps locally.\n",
    "2. Execute the model deployment `CI/CD` steps using `Cloud Build`.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0da8290c",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4873f8cf",
   "metadata": {},
   "source": [
    "### Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "59085129",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import logging\n",
    "\n",
    "logging.getLogger().setLevel(logging.INFO)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e37fb189",
   "metadata": {},
   "source": [
    "### Setup Google Cloud project"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e45be804",
   "metadata": {},
   "outputs": [],
   "source": [
    "PROJECT = '[your-project-id]' # Change to your project id.\n",
    "REGION = 'europe-west1' # Change to your region.\n",
    "BUCKET =  '[your-bucket-name]' # Change to your bucket name.\n",
    "SERVICE_ACCOUNT = \"[your-service-account]\"\n",
    "\n",
    "if PROJECT == \"\" or PROJECT is None or PROJECT == \"[your-project-id]\":\n",
    "    # Get your GCP project id from gcloud\n",
    "    shell_output = !gcloud config list --format 'value(core.project)' 2>/dev/null\n",
    "    PROJECT = shell_output[0]\n",
    "    \n",
    "if SERVICE_ACCOUNT == \"\" or SERVICE_ACCOUNT is None or SERVICE_ACCOUNT == \"[your-service-account]\":\n",
    "    # Get your GCP project id from gcloud\n",
    "    shell_output = !gcloud config list --format 'value(core.account)' 2>/dev/null\n",
    "    SERVICE_ACCOUNT = shell_output[0]\n",
    "    \n",
    "if BUCKET == \"\" or BUCKET is None or BUCKET == \"[your-bucket-name]\":\n",
    "    # Get your bucket name to GCP project id\n",
    "    BUCKET = PROJECT\n",
    "    # Try to create the bucket if it doesn't exists\n",
    "    ! gsutil mb -l $REGION gs://$BUCKET\n",
    "    print(\"\")\n",
    "    \n",
    "print(\"Project ID:\", PROJECT)\n",
    "print(\"Region:\", REGION)\n",
    "print(\"Bucket name:\", BUCKET)\n",
    "print(\"Service Account:\", SERVICE_ACCOUNT)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1574964f",
   "metadata": {},
   "source": [
    "### Set configurations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a01278c",
   "metadata": {},
   "outputs": [],
   "source": [
    "VERSION = 'v01'\n",
    "DATASET_DISPLAY_NAME = 'chicago-taxi-tips'\n",
    "MODEL_DISPLAY_NAME = f'{DATASET_DISPLAY_NAME}-classifier-{VERSION}'\n",
    "ENDPOINT_DISPLAY_NAME = f'{DATASET_DISPLAY_NAME}-classifier'\n",
    "\n",
    "CICD_IMAGE_NAME = 'cicd:latest'\n",
    "CICD_IMAGE_URI = f\"gcr.io/{PROJECT}/{CICD_IMAGE_NAME}\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e6bc4a0-d34c-43f5-a5fe-607825c6e9af",
   "metadata": {},
   "source": [
    "## 1. Run CI/CD steps locally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f15556fb-b76f-4b0b-b3ab-82ea6c444c42",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.environ['PROJECT'] = PROJECT\n",
    "os.environ['REGION'] = REGION\n",
    "os.environ['MODEL_DISPLAY_NAME'] = MODEL_DISPLAY_NAME\n",
    "os.environ['ENDPOINT_DISPLAY_NAME'] = ENDPOINT_DISPLAY_NAME"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6546ac1",
   "metadata": {},
   "source": [
    "### Run the model artifact testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "74c0f8a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "!py.test src/tests/model_deployment_tests.py::test_model_artifact -s"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77885b24",
   "metadata": {},
   "source": [
    "### Run create endpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0efe73b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "!python build/utils.py \\\n",
    "    --mode=create-endpoint\\\n",
    "    --project={PROJECT}\\\n",
    "    --region={REGION}\\\n",
    "    --endpoint-display-name={ENDPOINT_DISPLAY_NAME}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3eb28c6f",
   "metadata": {},
   "source": [
    "### Run deploy model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9cb3f19d",
   "metadata": {},
   "outputs": [],
   "source": [
    "!python build/utils.py \\\n",
    "    --mode=deploy-model\\\n",
    "    --project={PROJECT}\\\n",
    "    --region={REGION}\\\n",
    "    --endpoint-display-name={ENDPOINT_DISPLAY_NAME}\\\n",
    "    --model-display-name={MODEL_DISPLAY_NAME}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee492355",
   "metadata": {},
   "source": [
    "### Test deployed model endpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "43277aa8-f374-48bd-977c-296577c7d5d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "!py.test src/tests/model_deployment_tests.py::test_model_endpoint"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37b150c9",
   "metadata": {},
   "source": [
    "## 2. Execute the Model Deployment CI/CD routine in Cloud Build\n",
    "\n",
    "The CI/CD routine is defined in the [model-deployment.yaml](model-deployment.yaml) file, and consists of the following steps:\n",
    "1. Load and test the the trained model interface.\n",
    "2. Create and endpoint in Vertex AI if it doesn't exists.\n",
    "3. Deploy the model to the endpoint.\n",
    "4. Test the endpoint."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "839e540c",
   "metadata": {},
   "source": [
    "### Build CI/CD container Image for Cloud Build\n",
    "\n",
    "This is the runtime environment where the steps of testing and deploying model will be executed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a7f9bf4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "!echo $CICD_IMAGE_URI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3855daae",
   "metadata": {},
   "outputs": [],
   "source": [
    "!gcloud builds submit --tag $CICD_IMAGE_URI build/. --timeout=15m"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90fbd4b9",
   "metadata": {},
   "source": [
    "### Run CI/CD from model deployment using Cloud Build"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1aec70c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#REPO_URL = \"https://github.com/GoogleCloudPlatform/mlops-with-vertex-ai.git\" # Change to your github repo.\n",
    "REPO_URL = \"https://github.com/javiergp/mlops-with-vertex-ai.git\"\n",
    "BRANCH = \"main\" "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "01995fa5",
   "metadata": {},
   "outputs": [],
   "source": [
    "SUBSTITUTIONS=f\"\"\"\\\n",
    "_REPO_URL='{REPO_URL}',\\\n",
    "_BRANCH={BRANCH},\\\n",
    "_CICD_IMAGE_URI={CICD_IMAGE_URI},\\\n",
    "_PROJECT={PROJECT},\\\n",
    "_REGION={REGION},\\\n",
    "_MODEL_DISPLAY_NAME={MODEL_DISPLAY_NAME},\\\n",
    "_ENDPOINT_DISPLAY_NAME={ENDPOINT_DISPLAY_NAME},\\\n",
    "_GCS_BUCKET={BUCKET}/cloudbuild,\\\n",
    "_SERVICE_ACCOUNT={SERVICE_ACCOUNT}\\\n",
    "\"\"\"\n",
    "\n",
    "!echo $SUBSTITUTIONS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8849d3e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "!gcloud builds submit --no-source --config build/model-deployment.yaml --substitutions {SUBSTITUTIONS} --timeout=30m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "01831724",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4418b01e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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