{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Solution overview\n",
    "This notebook contains a collection of architecture diagrams which cover different aspects of the architecture."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overall solution architecture\n",
    "<img src=\"../design/ml-ops-solution-overview.drawio.svg\" style=\"background-color:white;\" alt=\"solution overview\" width=\"1000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## AWS account, team, and project setup\n",
    "\n",
    "<img src=\"../design/ml-ops-team-structure.drawio.svg\" style=\"background-color:white;\" alt=\"account, team, and project setup\" width=\"1000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IAM setup\n",
    "\n",
    "<img src=\"../design/ml-ops-iam.drawio.svg\" style=\"background-color:white;\" alt=\"iam setup\" width=\"1000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Infrastructure\n",
    "\n",
    "<img src=\"../design/ml-ops-vpc-infrastructure.drawio.svg\" style=\"background-color:white;\" alt=\"infrastructure setup\" width=\"1000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MLOps project template to build, train, validate model\n",
    "\n",
    "<img src=\"../design/ml-ops-model-build-train.drawio.svg\" style=\"background-color:white;\" alt=\"mlops for build, train, validate\" width=\"1000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MLOps project template for multi-account model deployment\n",
    "\n",
    "<img src=\"../design/ml-ops-model-deploy.drawio.svg\" style=\"background-color:white;\" alt=\"mlops for multi-account deployment\" width=\"1000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Release resources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<p><b>Shutting down your kernel for this notebook to release resources.</b></p>\n",
       "<button class=\"sm-command-button\" data-commandlinker-command=\"kernelmenu:shutdown\" style=\"display:none;\">Shutdown Kernel</button>\n",
       "        \n",
       "<script>\n",
       "try {\n",
       "    els = document.getElementsByClassName(\"sm-command-button\");\n",
       "    els[0].click();\n",
       "}\n",
       "catch(err) {\n",
       "    // NoOp\n",
       "}    \n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%html\n",
    "\n",
    "<p><b>Shutting down your kernel for this notebook to release resources.</b></p>\n",
    "<button class=\"sm-command-button\" data-commandlinker-command=\"kernelmenu:shutdown\" style=\"display:none;\">Shutdown Kernel</button>\n",
    "        \n",
    "<script>\n",
    "try {\n",
    "    els = document.getElementsByClassName(\"sm-command-button\");\n",
    "    els[0].click();\n",
    "}\n",
    "catch(err) {\n",
    "    // NoOp\n",
    "}    \n",
    "</script>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (Data Science)",
   "language": "python",
   "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east-1:081325390199:image/datascience-1.0"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}