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Repo"}},"flexible_column_cont":{"id":"flexible-column-container-514979222a","propertiesId":"quickstart-template-main-flexible-container","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-934a4199ef",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"contentfragment":{"id":"contentfragment-9defad81ad","paragraphs":["<!-- ------------------------ -->\n","\u003Ch2\u003EOverview\u003C/h2\u003E\n","\u003Cp\u003ESnowflake is a terrific platform on which to build data applications. The unique characteristics and cloud-based design allow for building applications that scale with data and workload. This tutorial will go through how to build and deploy both the Processing Layer and the User Interface Layer paired with Snowflake as the Persistence Layer.\u003C/p\u003E\n","\u003Cp\u003EOur example will be using a fictional food truck franchise website, Tasty Bytes. We will be building a graphical user interface with charts and graphs for franchisees to be able to examine sales data related to their franchise of food trucks. After logging in via a login page, each franchisee will have one page that will show metrics at the franchise level, and another that will show metrics around the food truck brands for that franchise.\u003C/p\u003E\n","\u003Cp\u003EThe Processing and User Interface Layers will be built using Node.js. The dataset is an orders history for Tasty Bytes.\u003C/p\u003E\n","\u003Cp\u003EThe application itself will be built using containers and deployed to Snowflake. Snowpark Container Services (SPCS) allows the running of containerized workloads directly within Snowflake, ensuring that data doesn’t need to be moved out of the Snowflake environment for processing.\u003C/p\u003E\n","\u003Cp\u003EThis lab builds directly on the same code and solution as the \u003Ca href=\"/en/developers/guides/build-a-data-app-with-snowflake/\"\u003EBuild a Data App with Snowflake\u003C/a\u003E quickstart, for in depth walk-through of the use case and the data, and how the application is built using Node Express and React you can review each step in that guide as well.\u003C/p\u003E\n","\u003Ch3\u003EPrerequisites\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EA Snowflake account, and familiarity with the Snowsight interface\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EPrivileges necessary to create a user, database, and warehouse in Snowflake\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EBasic experience using git\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EIntermediate knowledge of Node.js and React JS\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EIntermediate knowledge of containerised applications\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EGitHub Codespaces -or- Ability to install and run software on your computer\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ESnowpark Container Services availability\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003ESnowpark Container Services is currently available across a \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowpark-container-services/overview#label-snowpark-containers-overview-available-regions\"\u003Erange of cloud providers and regions\u003C/a\u003E. For this lab ensure that you have an account in one of the supported regions.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EWhat You’ll Learn\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to configure and build a custom API Powered by Snowflake, written in Node.js\u003C/li\u003E\u003Cli\u003EHow to configure and build a custom frontend website to communicate with the API, written in React and Node.js\u003C/li\u003E\u003Cli\u003EHow to deploy a containerised application to Snowpark Container Services\u003C/li\u003E\u003Cli\u003EHow to run and test the frontend and API on your machine\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You’ll Need\u003C/h3\u003E\n","\u003Ch4\u003EOption 1, using GitHub Codespaces:\u003C/h4\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://github.com/\"\u003EGitHub Codespaces\u003C/a\u003E GitHub Account with credits for GitHub Codespaces\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch4\u003EOption 2, local build:\u003C/h4\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://code.visualstudio.com/download\"\u003EVSCode\u003C/a\u003E Installed\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.docker.com/get-docker/\"\u003EDocker\u003C/a\u003E Installed\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://git-scm.com/book/en/v2/Getting-Started-Installing-Git\"\u003EGit\u003C/a\u003E Installed\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://nodejs.org/en/download/\"\u003ENodeJS\u003C/a\u003E Installed\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.npmjs.com/downloading-and-installing-node-js-and-npm\"\u003ENPM\u003C/a\u003E Installed\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You’ll Build\u003C/h3\u003E\n","\u003Cp\u003EIn this quickstart we will build and deploy a Data Application running on Snowpark Container Services.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/build-a-data-app-spcs-overview.png\" alt=\"Service Overview\"\u003E\u003C/p\u003E\n","\u003Cp\u003EThe solution consists of two services hosted on Snowpark Container Services:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EThe backend service\u003C/strong\u003E - which hosts the API built on Node Express - API Powered by Snowflake built in Node.js\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EThe frontend service\u003C/strong\u003E - which hosts the React JS Web Application that connects to that API, and a router service in NGINX that allows calls from the browser-based React frontend to be routed to the backend services also.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EWithout the router part of the frontend service, CORS would actually prevent the browser from talking to the backend service, even if we opened up a public endpoint for it. This is due to the fact that we cannot add our own headers to requests coming to the service endpoints - for security reasons Snowpark Container Services networking strips out any headers (but adds a few useful ones that we will use for authentication later).\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ESet up the Data\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EIn this part of the lab we'll set up our Snowflake account, create database structures to house our data, create a Virtual Warehouse to use for data loading and finally load our Tasty Bytes Food Truck orders data into our ORDERS table and run a few queries to get familiar with the data.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EThe sample data for the quickstart that we load will only cover the dates between 2022-01-01 to 2022-10-31. Don't be alarmed if a query on a data later or earlier than that returns an empty response\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EStep 2.1 Initial Snowflake Setup\u003C/h3\u003E\n","\u003Cp\u003EFor this part of the lab we will want to ensure we run all steps as the ACCOUNTADMIN role\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--change role to accountadmin\nuse role accountadmin;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EFirst we can create a \u003Ca href=\"https://docs.snowflake.com/en/user-guide/warehouses-overview\"\u003EVirtual Warehouse\u003C/a\u003E that can be used for data exploration and general querying in this lab.  We'll create this warehouse with a size of \u003Ccode\u003EMedium\u003C/code\u003E which is right sized for that use case in this lab.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--create a virtual warehouse for data exploration\ncreate or replace warehouse query_wh with \n\twarehouse_size = 'medium' \n\twarehouse_type = 'standard' \n\tauto_suspend = 300 \n\tauto_resume = true \n\tmin_cluster_count = 1 \n\tmax_cluster_count = 1;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EStep 2.2 Load Data\u003C/h3\u003E\n","\u003Cp\u003ENext we will create a database and schema that will house the tables that store our application data.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--create the application database and schema\ncreate or replace database frostbyte_tasty_bytes;\ncreate or replace schema app;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis DDL will create the structure for the ORDERS table which is the main source of data for our application in this lab.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--create table structure for order data \ncreate or replace table orders (\n\torder_id number(38,0),\n\ttruck_id number(38,0),\n\torder_ts timestamp_ntz(9),\n\torder_detail_id number(38,0),\n\tline_number number(38,0),\n\ttruck_brand_name varchar(16777216),\n\tmenu_type varchar(16777216),\n\tprimary_city varchar(16777216),\n\tregion varchar(16777216),\n\tcountry varchar(16777216),\n\tfranchise_flag number(38,0),\n\tfranchise_id number(38,0),\n\tfranchisee_first_name varchar(16777216),\n\tfranchisee_last_name varchar(16777216),\n\tlocation_id number(19,0),\n\tcustomer_id number(38,0),\n\tfirst_name varchar(16777216),\n\tlast_name varchar(16777216),\n\te_mail varchar(16777216),\n\tphone_number varchar(16777216),\n\tchildren_count varchar(16777216),\n\tgender varchar(16777216),\n\tmarital_status varchar(16777216),\n\tmenu_item_id number(38,0),\n\tmenu_item_name varchar(16777216),\n\tquantity number(5,0),\n\tunit_price number(38,4),\n\tprice number(38,4),\n\torder_amount number(38,4),\n\torder_tax_amount varchar(16777216),\n\torder_discount_amount varchar(16777216),\n\torder_total number(38,4)\n);\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EFor loading data into the ORDERS table we will create a new Virtual Warehouse sized as a \u003Ccode\u003ELarge\u003C/code\u003E to help us quickly ingest the data we have stored in an S3 bucket.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--create a virtual warehouse for data loading\ncreate or replace warehouse load_wh with \n\twarehouse_size = 'large' \n\twarehouse_type = 'standard' \n\tauto_suspend = 300 \n\tauto_resume = true \n\tmin_cluster_count = 1 \n\tmax_cluster_count = 1;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ENext we have to create a \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-load-overview\"\u003ESTAGE\u003C/a\u003E which is a Snowflake object that points to a cloud storage location Snowflake can access to both ingest and query data.  In this lab the data is stored in a publicly accessible AWS S3 bucket which we are referencing when creating the Stage object.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--create stage for loading orders data\ncreate or replace stage tasty_bytes_app_stage\n\turl = 's3://sfquickstarts/frostbyte_tastybytes/app/orders/';\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EOnce we've created both the Virtual Warehouse we want to use for loading data and the Stage which points to where the data resides in cloud storage we can simply \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/copy-into-table\"\u003ECOPY\u003C/a\u003E the data from that Stage into our ORDERS table.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--copy data into orders table using the load wh\n copy into orders from @tasty_bytes_app_stage;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EStep 2.3 Explore Data\u003C/h3\u003E\n","\u003Cp\u003ENow that we've loaded our data into the ORDERS table we can run a few queries to get familiar with it - but first we will want to change the Virtual Warehouse we're using from the \u003Ccode\u003ELOAD_WH\u003C/code\u003E back to the \u003Ccode\u003EQUERY_WH\u003C/code\u003E created earlier in the lab.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--change our Virtual Warehouse context to use our query_wh\n use warehouse query_wh;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ETo begin with we can simply look at a sample of the entire table.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--simple query to look at 10 rows of data \nselect * from orders limit 10;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ENext we can see how many records we've loaded into the table.  Notice how quickly the query executes - this is due to Snowflake's unique architecture which enables a certain class of queries like this one to pull results from metadata instead of requiring compute to generate the result.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--query to count all records in the table\nselect count(*) from orders;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EFinally we can run a more complex query to look at the total revenue by month where we will use a couple of \u003Ca href=\"https://docs.snowflake.com/en/sql-reference-functions\"\u003Efunctions\u003C/a\u003E to parse the month number and name from the ORDER_TS column in the ORDERS table.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--sales by month\nselect month(order_ts),monthname(order_ts), sum(price)\nfrom orders \ngroup by month(order_ts), monthname(order_ts)\norder by month(order_ts);\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EStep 2.4 Further explore the Data\u003C/h3\u003E\n","\u003Cp\u003ETo understand and explore the data even more, you can look through the \u003Ca href=\"/en/developers/guides/build-a-data-app-with-snowflake/\"\u003EQuickstart for Building a Data Application - Lab 2: Queries\u003C/a\u003E that offers a number of steps to explore it.\u003C/p\u003E\n","\u003Cp\u003EIf you already have done that, you can move directly to the next step in this guide. If not, you can continue below and explore the data further.\u003C/p\u003E\n","\u003Cp\u003EOur queries will be broken into two groups - \u003Ccode\u003EFranchise\u003C/code\u003E queries and \u003Ccode\u003ETruck Brand\u003C/code\u003E level queries.  For the sake of ease we will focus on the following Franchise, Truck Brand and Date Range for this part of the lab.\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EFranchise:  \u003Ccode\u003E1\u003C/code\u003E\u003C/li\u003E\u003Cli\u003ETruck Brand: \u003Ccode\u003EGuac 'n Roll\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EDate Range: \u003Ccode\u003E1/1/2023 - 3/31/2023\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ESetting Snowsight Context\u003C/h3\u003E\n","\u003Cp\u003ETo ensure the correct context is use for these queries we will set our database, schema and Virtual Warehouse using the following SQL:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--set query context\nuse database frostbyte_tasty_bytes;\nuse schema app;\nuse warehouse query_wh;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EFranchise Queries\u003C/h3\u003E\n","\u003Cp\u003ETo answer the business questions about how our overall Franchise business is doing we'll need to create the three following queries.  All of the columns required for these exist in the ORDERS table and no joining of tables are required.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003ETop 10 Countries Based on Revenue in a Time Window\u003C/li\u003E\u003Cli\u003ETop 10 Truck Brands Based on Revenue in a Time Window\u003C/li\u003E\u003Cli\u003EYear-to-Date Revenue, by Month, per Truck Brand\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EYou can spend some time creating the queries for each of these and then check your answers against the provided queries below by expanding each section.\u003C/p\u003E\n","\u003Cp\u003E<strong>Top 10 Countries Based on Revenue in a Time Window</strong>\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E    SELECT\n        TOP 10 country,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n        date(order_ts) >= '2023-01-01'\n        AND date(order_ts) <= '2023-03-31'\n        AND franchise_id = 1\n    GROUP BY\n        country\n    ORDER BY\n        sum(price) desc;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E<strong>Top 10 Truck Brands Based on Revenue in a Time Window</strong>\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E    SELECT\n        TOP 10 truck_brand_name,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n        date(order_ts) >= '2023-01-01'\n        AND date(order_ts) <= '2023-03-31'\n        AND franchise_id = 1\n    GROUP BY\n        truck_brand_name\n    ORDER BY\n        sum(price) desc;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E<strong>Year-to-Date Revenue, by Month, per Truck Brand</strong>\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E    SELECT\n        country,\n        month(order_ts) as date,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n         year(order_ts) = 2023\n        AND franchise_id = 1\n    GROUP BY\n        country,\n        month(order_ts)\n    ORDER BY\n        sum(price) desc;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003ETruck Brand Queries\u003C/h3\u003E\n","\u003Cp\u003ETo answer the business questions about how our overall Franchise business is doing we'll need to create the three following queries.  All of the columns required for these exist in the ORDERS table and no joining of tables are required.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003ETotal Sales by Day-of-Week\u003C/li\u003E\u003Cli\u003ETop Selling Items\u003C/li\u003E\u003Cli\u003ETop Selling items by Day-of-Week\u003C/li\u003E\u003Cli\u003E\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EYou can spend some time creating the queries for each of these and then check your answers against the provided queries below by expanding each section.\u003C/p\u003E\n","\u003Cp\u003E<strong>Top 10 Countries Based on Revenue in a Time Window</strong>\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E    SELECT\n        TOP 10 country,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n        date(order_ts) >= '2023-01-01'\n        AND date(order_ts) <= '2023-03-31'\n        AND franchise_id = 1\n    GROUP BY\n        country\n    ORDER BY\n        sum(price) desc;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E<strong>Top 10 Truck Brands Based on Revenue in a Time Window</strong>\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E    SELECT\n        TOP 10 truck_brand_name,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n        date(order_ts) >= '2023-01-01'\n        AND date(order_ts) <= '2023-03-31'\n        AND franchise_id = 1\n    GROUP BY\n        truck_brand_name\n    ORDER BY\n        sum(price) desc;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E<strong>Total Sales by City and Day-of-Week</strong>\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E    SELECT\n        country,\n        month(order_ts) as date,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n         year(order_ts) = 2023\n        AND franchise_id = 1\n    GROUP BY\n        country,\n        month(order_ts)\n    ORDER BY\n        sum(price) desc;\n\u003C/code\u003E\u003C/pre\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ESetup Snowflake\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003ENow that we've created our database, loaded data and developed the queries needed to answer our business questions, the last step before getting into application code is setting up the necessary objects so that the application can connect to Snowflake securely and query data on its own Virtual Warehouse. We will also set up the objects required to create and run services. The objects we will look at are:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/developer-guide/snowpark-container-services/working-with-compute-pool\"\u003ECompute Pools\u003C/a\u003E that are responsible for providing compute to the services once they run.\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/developer-guide/snowpark-container-services/working-with-registry-repository\"\u003EImage Repositories\u003C/a\u003E that can hold docker images used by the services we create\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowpark-container-services/working-with-services?utm_source=legacy&utm_medium=serp&utm_term=snowservices_ingress#ingress-using-a-service-from-outside-snowflake\"\u003EServices Ingress Security Integration\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EStep 3.1 Creating roles, permissions and virtual warehouse for running the application\u003C/h3\u003E\n","\u003Cp\u003EMuch like we created separate Virtual Warehouses for exploring and loading data, we will create one specifically for our service to use when executing queries on Snowflake.\u003C/p\u003E\n","\u003Cp\u003EWe start by creating a role that can be responsible for administering the setup of the services and everything else. There are a number of permissions that can be granted, and in a production build environment, these permissions may instead be granted to different roles with different responsibilities.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE ROLE accountadmin;\nUSE DATABASE frostbyte_tasty_bytes;\nUSE SCHEMA APP;\n\nCREATE ROLE tasty_app_admin_role;\n\nGRANT ALL ON DATABASE frostbyte_tasty_bytes TO ROLE tasty_app_admin_role;\nGRANT ALL ON SCHEMA frostbyte_tasty_bytes.app TO ROLE tasty_app_admin_role;\nGRANT SELECT ON ALL TABLES IN SCHEMA frostbyte_tasty_bytes.app TO ROLE tasty_app_admin_role;\nGRANT SELECT ON FUTURE TABLES IN SCHEMA frostbyte_tasty_bytes.app TO ROLE tasty_app_admin_role;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWe can now create a Virtual Warehouse that the application will use to execute queries.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ECREATE OR REPLACE WAREHOUSE tasty_app_warehouse WITH\nWAREHOUSE_SIZE='X-SMALL'\nAUTO_SUSPEND = 180\nAUTO_RESUME = true\nINITIALLY_SUSPENDED=false;\n\nGRANT ALL ON WAREHOUSE tasty_app_warehouse TO ROLE tasty_app_admin_role;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EStep 3.2 Creating Compute Pools for service to run on\u003C/h3\u003E\n","\u003Cp\u003EThe Compute Pools are used to run the services. We can create different pools for different purposes. In this example we create two different pools to run the services, one for the backend and one for the frontend. We could technically allow both services to use the same Compute Pool, in fact for this demo it would work very well, but in many scenarios the scaling requirements for the frontend and a backend may be different. Here we can see that the backend is given a pool of compute nodes that is slightly more scaled up than the nodes for the compute pool used for the frontend. There are multiple options for choosing the right instance family for a Compute Pool \u003Ca href=\"https://docs.snowflake.com/sql-reference/sql/create-compute-pool\"\u003ECreate Compute Pool\u003C/a\u003E. This would be even more relevant if the backend needed to do some more compute heavy work, even to the point where it needed to have GPU enabled nodes.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ECREATE COMPUTE POOL tasty_app_backend_compute_pool\nMIN_NODES = 1\nMAX_NODES = 1\nINSTANCE_FAMILY = CPU_X64_S;\n\nGRANT USAGE ON COMPUTE POOL tasty_app_backend_compute_pool TO ROLE tasty_app_admin_role;\nGRANT MONITOR ON COMPUTE POOL tasty_app_backend_compute_pool TO ROLE tasty_app_admin_role;\n\nCREATE COMPUTE POOL tasty_app_frontend_compute_pool\nMIN_NODES = 1\nMAX_NODES = 1\nINSTANCE_FAMILY = CPU_X64_XS;\n\nGRANT USAGE ON COMPUTE POOL tasty_app_frontend_compute_pool TO ROLE tasty_app_admin_role;\nGRANT MONITOR ON COMPUTE POOL tasty_app_frontend_compute_pool TO ROLE tasty_app_admin_role;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe \u003Ccode\u003Etasty_app_admin_role\u003C/code\u003E role must also be given the permission to bind service endpoints for services.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EGRANT BIND SERVICE ENDPOINT ON ACCOUNT TO ROLE tasty_app_admin_role;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EStep 3.3 Set up docker image repositories and stage for service specifications\u003C/h3\u003E\n","\u003Cp\u003EWe can now ensure that the current user can use the admin role.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESET sql = ('GRANT ROLE tasty_app_admin_role TO USER ' || CURRENT_USER() || '');\nEXECUTE IMMEDIATE $sql;\nUSE ROLE tasty_app_admin_role;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EHere we create the \u003Ca href=\"https://docs.snowflake.com/developer-guide/snowpark-container-services/working-with-registry-repository\"\u003E\u003Ccode\u003EIMAGE REPOSITORY\u003C/code\u003E\u003C/a\u003E to hold images for services.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E-- Create image repository  \nCREATE OR REPLACE IMAGE REPOSITORY tasty_app_repository;\n-- Show the repo we just created\nSHOW IMAGE REPOSITORIES;\n-- List images in repo (can be called later to verify that images have been pushed to the repo)\nSHOW IMAGES IN IMAGE REPOSITORY TASTY_APP_REPOSITORY;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWe can also create a stage to hold service specification files, although for this guide we will provide the specifications inline with the service creation.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E-- Create a stage to hold service specification files\nCREATE STAGE tasty_app_stage DIRECTORY = ( ENABLE = true );\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EStep 3.4 Create external users role and users for the external access\u003C/h3\u003E\n","\u003Cp\u003EIn order to allow the application users to access the application we can create dedicated \u003Ccode\u003EUSERS\u003C/code\u003E for each user. In the guide \u003Ca href=\"/en/developers/guides/build-a-data-app-with-snowflake/\"\u003EBuild a Data App with Snowflake\u003C/a\u003E users were actually stored in a \u003Ccode\u003EUSERS\u003C/code\u003E table that was created, where hashed passwords were stored and could be used to check the login from the frontend. Create that table by running the following SQL:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E-- Create Users table for the Website\ncreate or replace table users (\n\tuser_id number(38,0) autoincrement,\n\tuser_name varchar(16777216) not null,\n\thashed_password varchar(16777216),\n\tfranchise_id number(38,0),\n\tpassword_date timestamp_ntz(9),\n\tstatus boolean,\n\tunique (user_name)\n);\n\n -- Add Franchisee logins \ninsert into users\n    values\n    (1,'user1','$2b$10$v0IoU/pokkiM13e.eayf1u3DkgtIBMGO1uRO2O.mlb2K2cLztV5vy',1,current_timestamp,TRUE), \n    (2,'user2','$2b$10$e2TXM/kLlazbH1xl31SeOe6RTyfL3E9mE8sZZsU33AE52rO.u44JC',120,current_timestamp,TRUE),\n    (3,'user3','$2b$10$WX4e1LAC.rAabBJV58RuKerEK4T/U4htgXrmedTa5oiGCWIRHwe0e',271,current_timestamp,TRUE);\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EIn this guide, we will create those users as actual Snowflake Users and give them a role that is allowed to access the services we later create. This allows us to utilize the OAuth sign-in we created earlier to authenticate users.\u003C/p\u003E\n","\u003Cp\u003EWe can create the users like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE ROLE ACCOUNTADMIN;\nCREATE ROLE tasty_app_ext_role;\n\nGRANT USAGE ON DATABASE frostbyte_tasty_bytes TO ROLE tasty_app_ext_role;\nGRANT USAGE ON SCHEMA app TO ROLE tasty_app_ext_role;\n\nCREATE USER IF NOT EXISTS user1 PASSWORD='password1' MUST_CHANGE_PASSWORD=TRUE DEFAULT_ROLE=tasty_app_ext_role;\nGRANT ROLE tasty_app_ext_role TO USER user1;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ENot that we force the user to change the password on the first login here. When testing it you can choose to set \u003Ccode\u003EMUST_CHANGE_PASSWORD=FALSE\u003C/code\u003E, but in a real scenario these passwords should be changed on first login.\u003C/p\u003E\n","\u003Cp\u003EJust for reference, the users that were created in the earlier database set up lab are the following:\u003C/p\u003E\n\u003Ctable\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EUser name\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EHashed password\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EFranchise id\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EPlaintext password\u003C/th\u003E\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003Euser1\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$2b$10$3/teX....iH7NI1SjoTjhi74a\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E1\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003Epassword1\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003Euser2\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$2b$10$9wdGi....U8qeK/nX3c9HV8VW\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E120\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003Epassword120\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003Euser3\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$2b$10$CNZif....IXZFepwrGtZbGqIO\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E271\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003Epassword271\u003C/td\u003E\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n","\u003Cp\u003EWe can create all the users this way:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ECREATE USER IF NOT EXISTS user2 PASSWORD='password120' MUST_CHANGE_PASSWORD=TRUE DEFAULT_ROLE=tasty_app_ext_role;\nGRANT ROLE tasty_app_ext_role TO USER user2;\n\nCREATE USER IF NOT EXISTS user3 PASSWORD='password270' MUST_CHANGE_PASSWORD=TRUE DEFAULT_ROLE=tasty_app_ext_role;\nGRANT ROLE tasty_app_ext_role TO USER user3;\n\u003C/code\u003E\u003C/pre\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EBuilding the backend code\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EWe now look at the code for the backend and frontend to adapt it to run in Snowpark Container Services.\u003C/p\u003E\n","\u003Ch4\u003EOption 1 - Build using GitHub Codespaces\u003C/h4\u003E\n","\u003Cp\u003EIf you have access to GitHub and credits on an account that let's you run GitHub Codespaces, you can directly build the entire code and push the containerized images to the image repository in the cloud environment.\u003C/p\u003E\n","\u003Cp\u003EIf you don't have access to this, or prefer to build this locally, go to Option 2 instead.\u003C/p\u003E\n","\u003Cp\u003EFirst, create your own fork of the main repository, go to the GitHub repository at \u003Ca href=\"https://github.com/Snowflake-Labs/sfguide-tasty-bytes-zero-to-app-with-spcs.git\"\u003EGitHub: Snowflake-Labs/sfguide-tasty-bytes-zero-to-app-with-spcs\u003C/a\u003E and create your own fork of the repo.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/fork_repository.png\" alt=\"Fork Repository\"\u003E\u003C/p\u003E\n","\u003Cp\u003EOnce you have your own fork, go to the '<> CODE' button and select 'Codespaces' and create a new codespace.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/create_codespace.png\" alt=\"Create Codespace\"\u003E\u003C/p\u003E\n","\u003Ch4\u003EOption 2 - Build locally\u003C/h4\u003E\n","\u003Cp\u003EThe code for this lab is hosted on GitHub. Start by cloning the repository into a separate folder. Note that we are cloning a specific branch \u003Ccode\u003Espcs\u003C/code\u003E here that contains the code adapted for this guide.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Egit clone https://github.com/Snowflake-Labs/sfguide-tasty-bytes-zero-to-app-with-spcs.git zero-to-app-spcs\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EChange directory to the \u003Ccode\u003Ezero-to-app-spcs/\u003C/code\u003E directory that is created in the clone above. You should now have a directory with a \u003Ccode\u003E/src\u003C/code\u003E subdirectory that contains \u003Ccode\u003E/backend\u003C/code\u003E and \u003Ccode\u003E/frontend\u003C/code\u003E directories.\u003C/p\u003E\n","\u003Ch3\u003EStep 4.1 The backend service\u003C/h3\u003E\n","\u003Cp\u003ELet's start with looking at the backend code. Open a terminal and go to the \u003Ccode\u003E/src/backend\u003C/code\u003E directory.\u003C/p\u003E\n","\u003Cp\u003EFirst ensure that you have Docker installed on you environment:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Edocker --version\n-- Docker version 24.0.6, build ed223bc\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EFor local testing, we can then let the backend connect to the Snowflake account using credentials we supply in the environment variables. Copy the \u003Ccode\u003E.env.example\u003C/code\u003E file to \u003Ccode\u003E.env\u003C/code\u003E and fill out the details for your account there.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Ecd .../zero-to-app-spcs/src/backend\ncp .env.example .env\nsed -i -e "s/{INSERT A RANDOM STRING HERE}/$(openssl rand -base64 12)/" .env\nsed -i -e "s/{INSERT ANOTHER RANDOM STRING HERE}/$(openssl rand -base64 12)/" .env\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003ESNOWFLAKE_ACCOUNT={INSERT_ACCOUNT_NAME_HERE}\nSNOWFLAKE_USERNAME={INSERT_USER_NAME_HERE}\nSNOWFLAKE_PASSWORD={INSERT_PASSWORD_HERE}\nSNOWFLAKE_ROLE=TASTY_APP_ADMIN_ROLE\nSNOWFLAKE_WAREHOUSE=TASTY_APP_WAREHOUSE\nSNOWFLAKE_DATABASE=frostbyte_tasty_bytes\nSNOWFLAKE_SCHEMA=app\n\nACCESS_TOKEN_SECRET=a1to.....9wlnNq\nREFRESH_TOKEN_SECRET=KVDq9.....icVNh\n\nPORT=3000\n\nCLIENT_VALIDATION=Dev \n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThere is a \u003Ccode\u003Edocker-compose.yaml\u003C/code\u003E file in this folder that we will use to spin up a local service using this environment:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Edocker compose up\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ETry to access the API by calling the endpoint now. If you are in GitHub Codespaces, you will be offered a unique URL that is generated for you, like 'https://<random-generated-identifier>-3000.app.github.dev/' that you can access, if you are on your local environment, it will be a localhost URL, like 'http://localhost:3000/'\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/forwarded_port_host.png\" alt=\"Forwarded ports\"\u003E\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Ecurl https://<random-generated-identifier>-3000.app.github.dev/franchise/1\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003Eor, open up a new terminal and access it (this will also work inside Codespaces)\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Ecurl http://localhost:3000/franchise/1\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis should return the following JSON response:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-json\"\u003E{\n   "TRUCK_BRAND_NAMES":[\n      "The Mac Shack",\n      "Smoky BBQ",\n      "Freezing Point",\n      "Guac n' Roll",\n      "The Mega Melt",\n      "Plant Palace",\n      "Tasty Tibs",\n      "Nani's Kitchen",\n      "Better Off Bread",\n      "Peking Truck",\n      "Kitakata Ramen Bar",\n      "Cheeky Greek",\n      "Le Coin des Crêpes",\n      "Revenge of the Curds",\n      "Not the Wurst Hot Dogs"\n   ],\n   "START_DATE":"2022-01-01 08:00:01.000",\n   "END_DATE":"2022-10-31 22:59:29.000"\n}\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EStep 4.2 Authenticating and authorizing service users\u003C/h3\u003E\n","\u003Cp\u003ECurrently there is no authentication of the user calling this endpoint. We will change that to take advantage of the mechanism built into Snowflake Container Services.\u003C/p\u003E\n","\u003Cp\u003EIn the earlier guide \u003Ca href=\"/en/developers/guides/build-a-data-app-with-snowflake/\"\u003EBuild a Data App with Snowflake\u003C/a\u003E authentication was implemented using JWT tokens, where the client frontend called a login endpoint and provided user name and password, and the service looked that up in the database (the \u003Ccode\u003EUSERS\u003C/code\u003E table that is also created for this lab.) and then supplied the client with an accesstoken that could be passed along with future calls to the API. With SPCS this will not work because the environment strips any request headers from calls to the public endpoints as they are routed to the service, meaning we cannot evaluate a Bearer Authentication token in calls from the client to the backend. Remember, with a React application, the frontend is running directly as javascript in the client's browser, even if the code is served from the frontend service, so calls to the API are coming from the end users' browsers, not from the internal service hosting the frontend.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EWhile React.js mainly relies on Client-Side Rendering, other frontend frameworks may rely on Server-Side Rendering, which changes this a little bit. CSR is very lightweight and makes it easy for the frontend service to serve static content to the end users, so for this solution it works well.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003EWhat Snowpark Container Services offers is a different authentication model. Any user accessing the public endpoints for the services, needs to log in with a \u003Ccode\u003EUSER\u003C/code\u003E to the Snowflake interface.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/authenticating_with_snowservices_ingress.png\" alt=\"User authentication\"\u003E\u003C/p\u003E\n","\u003Cp\u003EIn this example, one of the users we created in the earlier steps (\u003Ccode\u003Euser1\u003C/code\u003E, \u003Ccode\u003Euser2\u003C/code\u003E, \u003Ccode\u003Euser3\u003C/code\u003E,...) can now log in here. Once the user is authenticated, Snowpark Container Services adds that user name as a special header \u003Ccode\u003ESf-Context-Current-User\u003C/code\u003E to any request to the public endpoints. Since the environment strips away any other headers, there is no risk that the client can tamper with the value of this either, so from the perspective of the backend service, we can trust that the value in that header represents the user that authenticated with Snowflake.\u003C/p\u003E\n","\u003Cp\u003EThe request headers reaching the service endpoint will look something like this for a normal call:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Ehost: 'backend-service:3000'\nreferer: 'https://randomlygeneratedendpointname.snowflakecomputing.app/login'\ncontent-type: 'application/json'\nuser-agent: 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36'\naccept: '*/*'\n'sf-context-current-user': 'USER1'\n...\n...\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWith this we can then look up that user and ensure that they have access to the application.\u003C/p\u003E\n","\u003Cp\u003EGo to the code for \u003Ccode\u003Eauth.js\u003C/code\u003E, it contains code to validate this header and look up the user in the database, in order to check its association with a franchise. The following code does that:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-js\"\u003Efunction lookupUser(user_name) {\n    return new Promise(async function (result, error) {\n        snowflake.getConnection().then(conn =>\n            conn.execute({\n                sqlText: sql_queries.verify_user,\n                binds: [user_name],\n                complete: (err, stmt, rows) => {\n                    if (err) {\n                        error({result: false, message: 'Unable to lookup user', error:err});\n                    } else {\n                        if (rows.length == 0) {\n                            result({message: 'User does not exist'});\n                        } else {\n                            user_row = rows[0]\n                            user_name = user_row.USER_NAME;\n                            franchise_id = user_row.FRANCHISE_ID;\n                            hashed_password = user_row.HASHED_PASSWORD;\n                            data = {result: true, validation: 'Snowflake', user_name: user_name, franchise_id: franchise_id, hashed_password: hashed_password };\n                            result(data);\n                        }\n                    }\n                },\n            }));\n    });\n}\n\n...\n\nfunction validateSnowflakeHeader(req, res, next) {\n\n    if (!req.headers['sf-context-current-user']) {\n        console.warn('Validation mode is Snowflake but sf-context-current-user header is missing - user is not validated');\n        res.status(422).send("Incorrect data");\n        return\n    }\n\n    const login_user = req.headers['sf-context-current-user']\n    console.log('sf-context-current-user: ' + login_user);\n    lookupUser(login_user).then(result => {\n        if (result.result === true){\n            console.log('Authorizing user ' + result.user_name + ' for franchise: ' + result.franchise_id);\n            req.user = { validation: 'Snowflake', user: result.user_name, franchise: result.franchise_id };\n            next();\n        } else {\n            console.warn('User does not exist: ' + login_user);\n            res.status(401).json('Invalid user or password');\n            return\n        }\n    }, error => {\n        console.error(error.message, error.error);\n        res.status(500).json({ error: error.message });\n        return\n    });\n};\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EComparing this to the code that validates a JWT access token it is similar, but we here also have to look up the user in a database call, because unlike the JWT we cannot securely pass any additional information (like the \u003Ccode\u003Efranchise_id\u003C/code\u003E in the token), the only value we can trust here is the user header, since it is securely set by the SPCS environment and cannot be tampered with by a javascript client. The rest of the code in that file is supporting the authentication using other methods, but this is the only one that will be used in this guide and when we deploy the services to Snowflake.\u003C/p\u003E\n","\u003Cp\u003EAlso review the file \u003Ccode\u003E/routes/login.js\u003C/code\u003E that introduces a new endpoint \u003Ccode\u003E/authorize\u003C/code\u003E that responds with an accesstoken containing the \u003Ccode\u003Euser id\u003C/code\u003E and \u003Ccode\u003Efranchise id\u003C/code\u003E when called with a header of \u003Ccode\u003ESf-Context-Current-User\u003C/code\u003E. This can be used by the frontend later on to check what franchise to set in the UI. Note that this endpoint also returns a JWT token, but we are only using that format to keep the code in the frontend as similar to the original code as possible, we are not using the JWT access token for future authorization of calls from the frontend to the backend.\u003C/p\u003E\n","\u003Cp\u003EThis endpoint is similar to the code in \u003Ccode\u003Eauth.js\u003C/code\u003E for validating a user.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-js\"\u003Erouter.get("/authorize", async (req, res) => {\n\n    console.log('Authorize with request headers:')\n    if (!req.headers['sf-context-current-user']) {\n        res.status(422).send("Incorrect data");\n        return\n    }\n\n    const login_user = req.headers['sf-context-current-user']\n    console.log(`Authorizing user ${login_user} from context header`);\n    auth.lookupUser(login_user).then(result => {\n        if (result.result === true) {            \n            console.log('Authorizing user ' + result.user_name + ' for franchise: ' + result.franchise_id);\n            const accessToken = auth.generateAccessToken({ user: result.user_name, franchise: result.franchise_id, preauthorized: true });\n            const refreshToken = auth.generateRefreshToken({ user: result.user_name, franchise: result.franchise_id, preauthorized: true });\n            res.status(200).json({ accessToken: accessToken, refreshToken: refreshToken });\n            return\n        } else {\n            console.warn('User does not exist: ' + login_user);\n            res.status(401).json('Invalid user or password');\n            return\n        }\n    }, error => {\n        console.error(error.message, error.error);\n        res.status(500).json({ error: error.message });\n        return\n    });\n});\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWith this we test run the application locally and simulate the SPCS environment. Change the \u003Ccode\u003E.env\u003C/code\u003E file to use Snowflake authentication instead:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003ECLIENT_VALIDATION=Snowflake\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ERestart the service running by pressing \u003Ccode\u003ECTRL+c\u003C/code\u003E in the terminal where you started the docker service. Restart it again with \u003Ccode\u003Edocker compose up\u003C/code\u003E again. Once running you should now see the output:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Ebackend-backend_service-1  | Starting up Node Express, build version 00013\nbackend-backend_service-1  | Server running on port 3000\nbackend-backend_service-1  | Environment: development\nbackend-backend_service-1  | CORS origin allowed: http://localhost:4000\nbackend-backend_service-1  | Client validation: Snowflake\nbackend-backend_service-1  | Using warehouse: TASTY_APP_WAREHOUSE\nbackend-backend_service-1  | Using role: TASTY_APP_ADMIN_ROLE\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ECalling one of the endpoints now results in a \u003Ccode\u003EHTTP 422\u003C/code\u003E response and the test \u003Ccode\u003EIncorrect data\u003C/code\u003E (which is what we expect from the \u003Ccode\u003EvalidateSnowflakeHeader\u003C/code\u003E in \u003Ccode\u003Eauth.js\u003C/code\u003E). If we provide a header that looks like the SPCS authentication header it now uses that to validate the user:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Ecurl --header "Sf-Context-Current-User:user1"  http://localhost:3000/franchise/1\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis now responds with a the expected \u003Ccode\u003EHTTP 200\u003C/code\u003E response:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-json\"\u003E{\n   "TRUCK_BRAND_NAMES":["The Mac Shack","Smoky BBQ","Freezing Point","Guac n' Roll","The Mega Melt","Plant Palace","Tasty Tibs","Nani's Kitchen","Better Off Bread","Peking Truck","Kitakata Ramen Bar","Cheeky Greek","Le Coin des Crêpes","Revenge of the Curds","Not the Wurst Hot Dogs"\n   ],\n   "START_DATE":"2022-01-01 08:00:01.000",\n   "END_DATE":"2022-10-31 22:59:29.000"\n}\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou can now terminate the service with \u003Ccode\u003ECTRL+c\u003C/code\u003E and we can then destroy the local Docker service and images we just used for testing:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Edocker rm backend-backend_service-1\ndocker image rm backend-backend_service\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EStep 4.3 Connecting to Snowflake data\u003C/h3\u003E\n","\u003Cp\u003EWith this update, we can now look at how the backend service can access the data in the Snowflake tables and views. In the self hosted version of the code (as in the \u003Ca href=\"/en/developers/guides/build-a-data-app-with-snowflake/\"\u003EBuild a Data App with Snowflake\u003C/a\u003E) we use a key pair authentication schema to connect the service to Snowflake. For a service running on Snowpark Container Services, we can benefit from the service already running on Snowflake and we can use a provided and pre-loaded authentication model based on OAuth. This is available for every service running on SPCS.\u003C/p\u003E\n","\u003Cp\u003EOpen the file \u003Ccode\u003Econnect.js\u003C/code\u003E and look at how the code is sending the options for the connection to Snowflake:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-js\"\u003E    const options = {\n        database: process.env.SNOWFLAKE_DATABASE,\n        schema: process.env.SNOWFLAKE_SCHEMA,\n        warehouse: process.env.SNOWFLAKE_WAREHOUSE,\n    };\n\n    if (fs.existsSync('/snowflake/session/token')) {\n        options.token = fs.readFileSync('/snowflake/session/token', 'ascii');\n        options.authenticator = "OAUTH";\n        options.account = process.env.SNOWFLAKE_ACCOUNT;\n        options.accessUrl = 'https://' + process.env.SNOWFLAKE_HOST;\n    } else {\n        options.account = process.env.SNOWFLAKE_ACCOUNT;\n        options.username = process.env.SNOWFLAKE_USERNAME;\n        options.role = process.env.SNOWFLAKE_ROLE;\n        options.password = process.env.SNOWFLAKE_PASSWORD;\n    };\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWhen the service is running on SPCS, the file located at \u003Ccode\u003E/snowflake/session/token\u003C/code\u003E will contain an OAuth token that is pre-validated for accessing Snowflake. This means we don't need to supply a user and password for the connection. This token is authenticated for a temporary user that is given the same role as the \u003Ccode\u003EOWNER\u003C/code\u003E for the Service being called. This is an important detail, as the service will be connecting as the very role that created it (here it will be \u003Ccode\u003Etasty_app_admin_role\u003C/code\u003E), so think of it as a service account type of user that is connecting. This is analogous to how the original solution worked, but in there we created a dedicated user that the service connected as.\u003C/p\u003E\n","\u003Cp\u003EOnce connected, the rest of the backend code is working the same, regardless if it is running in the SPCS environment or somewhere else, like a local testing environment.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EBuilding the frontend code\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EWe can now look at how the frontend has been updated to take advantage of the changes and for us to be able to run it on SPCS.\u003C/p\u003E\n","\u003Cp\u003EThere are two areas that is updated here to allow it to run in the new environment:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EAuthentication - by placing the service behind a public endpoint that forces users to login, it no longer makes sense to keep the login form in the client, the required authentication is already captured by the Snowflake OAuth login form\u003C/li\u003E\u003Cli\u003ERouting from client to the backend API, we can no longer directly control the CORS directives for the services, and calls from the client are actually made directly from the users' browsers.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EThe routing is something that changes somewhat significantly from the original solution. Instead of adding a CORS directive to the backend (e.g. allowing calls from another origin), we introduce a router service that takes calls from the public endpoint and \u003Cem\u003Eroutes\u003C/em\u003E them to either the frontend service, or the backend service, allowing us to maintain a single public endpoint.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EThe frontend service and backend service are here hosted as two separate services, with a router bundled together with the frontend. For this simple application that may not be a necessary requirement to fulfill, but in a more complex and demanding application, it would be a good approach to separate the frontend and backend as they would have different non-functional requirements.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003EThe router ensures that calls made to routes starting with \u003Ccode\u003E/api\u003C/code\u003E are forwarded to the \u003Ccode\u003Ebackend-service\u003C/code\u003E, whereas any other calls \u003Ccode\u003E/*\u003C/code\u003E are routed to the frontend container running in the same service as the router:\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/frontend-routing.png\" alt=\"Routing\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EStep 5.1 Building the router\u003C/h3\u003E\n","\u003Cp\u003EThe router is a simple service based on \u003Ca href=\"https://www.nginx.com/\"\u003E\u003Cem\u003ENGINX\u003C/em\u003E\u003C/a\u003E. The code is very simple and serves a NGINX server that is given a configuration that defines the different routes, open \u003Ccode\u003E/src/frontend/router/nginx.conf.template\u003C/code\u003E:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-yaml\"\u003Eevents {\n  worker_connections  1024;\n}\nhttp {\n  server {\n    listen 8000;\n    listen [::]:8000;\n    server_name localhost;\n\n    location / {\n      proxy_pass  http://$FRONTEND_SERVICE/;\n    }\n\n    location /api {\n        rewrite     /api/(.*) /$1  break;\n        proxy_pass  http://$BACKEND_SERVICE/;\n    }\n\n    location /test {\n        add_header Content-Type text/html;\n\n        return 200 '<html><body><h1>This is the router testpage</h1><li>Sf-Context-Current-User: $http_sf_context_current_user</li><li>Host: $http_host</li><li>Frontend Server: $FRONTEND_SERVICE</li><li>Backend Server: $BACKEND_SERVICE</li></body></html>';\n    }\n  } \n}\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThere are three routes in here, \u003Ccode\u003E/\u003C/code\u003E, \u003Ccode\u003E/api\u003C/code\u003E \u003Ccode\u003E/test\u003C/code\u003E. The last one simply outputs debug information and can help to understand that the setup is correct (it should be removed when not testing out the services).\u003C/p\u003E\n","\u003Cp\u003EThe \u003Ccode\u003E/api\u003C/code\u003E route means that anything prefixed with that gets rewritten to remove the "\u003Ccode\u003E/api\u003C/code\u003E" part and then passed forward to the backend service URL. For all other calls they should be forwarded directly to the frontend service URL (which should be running on the same service as the router, in a different container).\u003C/p\u003E\n","\u003Cp\u003EThe \u003Ccode\u003E$FRONTEND_SERVICE\u003C/code\u003E and \u003Ccode\u003E$BACKEND_SERVICE\u003C/code\u003E variables allow us to dynamically replace these values when the Docker image is being used. If we look at the Dockerfile:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003EFROM nginx:alpine\n\nARG required FRONTEND_SERVICE\nARG required BACKEND_SERVICE\n\nRUN apk update && apk add bash\n\nEXPOSE 8000\n\nCOPY nginx.conf.template /nginx.conf.template\n\nCMD ["/bin/sh" , "-c" , "envsubst '$FRONTEND_SERVICE $BACKEND_SERVICE' < /nginx.conf.template > /etc/nginx/nginx.conf && exec nginx -g 'daemon off;'"]\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe last line substitutes these variables for values taken from the \u003Ccode\u003Eenvironment\u003C/code\u003E it is running in, before copying the contents into the \u003Ccode\u003Enginx.conf\u003C/code\u003E file and starting up the server.\u003C/p\u003E\n","\u003Cp\u003EYou can test the router by running the container locally. From \u003Ccode\u003E/src/frontend\u003C/code\u003E run the following:\nbash\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003Edocker compose --env-file .env.local.example up\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis should run the router and the frontend on local ports. Test it out by running:\nbash\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003Ecurl http://localhost:8888/test\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EIt should return HTLM, like:\nhtml\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003E<html><body><h1>This is the router testpage</h1><li>Sf-Context-Current-User: </li><li>Host: localhost:8888</li><li>Frontend Server: localhost:4000</li><li>Backend Server: localhost:3000</li></body></html>\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ETerminate the running containers byt pressing \u003Ccode\u003Ectrl+c\u003C/code\u003E in the terminal again.\u003C/p\u003E\n","\u003Ch3\u003EStep 5.2 Updating the frontend code\u003C/h3\u003E\n","\u003Cp\u003EThe frontend code itself needs fewer changes to adapt to the new environment. Primarily here we are looking at removing the actual login form and user management in favor of using the built in login capability.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/tasty-app-ui.png\" alt=\"Tasty App UI\"\u003E\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EThe original React code is actually built on older package dependencies. In order to keep this guide as similar to the original guide no changes to the React framework have been introduced, only minor changes are done as part of this guide. There are many ways to update the general React code to later standards, but this guide will focus on the core parts of connecting the services,\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003EIn a commonly shared file \u003Ccode\u003EUtils.js\u003C/code\u003E we can provide some methods that will help check how to communicate with the backend and to verify if the login button should be visible.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-js\"\u003Eexport function enableLogin() {\n    if (clientValidation === 'JWT') {\n        return true;\n    } else if (clientValidation === 'Snowflake') {\n        return false;\n    }\n    console.log(` - Login disabled`);\n    return false;\n}\n\nexport function isLoggedIn(state) {\n    if (clientValidation === 'JWT') {\n        if (state){\n            return (state.accessToken != null);\n        }\n    } else if (clientValidation === 'Snowflake') {\n        if (state){\n            return (state.accessToken != null);\n        }\n    } else if (clientValidation === 'Dev') {\n        if (state){\n            return (state.franchise != null);\n        }\n    }\n    return false;\n}\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWe can then use these functions to decide if the Login button should be visible or not:\u003C/p\u003E\n","\u003Cp\u003EE.g. in \u003Ccode\u003EHome.js\u003C/code\u003E, the logout button is conditionally shown using the above function:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-html\"\u003E            <div className='home-header'>\n                <Image src='bug-sno-R-blue.png' className='homeLogo' />\n                <h1 className="homeTitle"> Tasty App</h1>\n\n                <Button className='backBtn' onClick={gotoDetails}>  🚚 Truck Details</Button>\n                { enableLogin() &&\n                    <Button className='home-logoutBtn' onClick={logout}>⎋ Logout</Button>\n                }\n            </div>\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAnd in the \u003Ccode\u003EApp.js\u003C/code\u003E routing we can use the same functions to conditionally route the user depending on if they are logged in or not.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-js\"\u003Efunction App() {\n\n  const LoginWrapper = () => {\n    const location = useLocation();\n    return isLoggedIn(location.state) ? <Outlet /> : <Navigate to="/login" replace />;\n  };\n\n  return (\n    // Routing for the App.\n    <BrowserRouter>\n      <Routes>\n        <Route path="/login" element={ <Login />  } />\n        <Route element={<LoginWrapper />}>\n          <Route path="/" element={ <Home /> } />\n          <Route path="/home" element={ <Home /> } />\n          <Route path="/details" element={ <Details /> } />\n        </Route>\n      </Routes>\n    </BrowserRouter>\n  );\n}\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EFinally we add a call in \u003Ccode\u003ELogin.js\u003C/code\u003E to check the \u003Ccode\u003E/authenticate\u003C/code\u003E endpoint of the backend.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-js\"\u003Econst clientValidation = process.env.REACT_APP_CLIENT_VALIDATION;\n\n...\n\n    function checkAuthentication() {\n        if (clientValidation === 'JWT') {\n            //console.log(` - Validation enabled`);\n        } else if (clientValidation === 'Snowflake') {\n            console.log(`Checking client validation ${clientValidation} - Checking authorize endpoint of API`);\n            const requestOptions = {\n                method: 'GET',\n                headers: { 'Content-Type': 'application/json', 'Sf-Context-Current-User': 'user1' }\n            };\n            fetch(backendURL + '/authorize', requestOptions)\n                .then((result) => {\n                    if (result.ok) {\n                        result.json()\n                            .then((data) => {\n                                const token = decodeToken(data.accessToken);\n                                data.franchise = token.franchise;\n                                navigate("/", { state: data });\n                            });\n                    } else {\n                        console.warn('Current user is not authorized to use the application');\n                    }\n\n                });\n        } else {\n            console.warn(`Checking client validation ${clientValidation} - Validation disabled - hard coding franchise "1"`);\n            const data = { franchise: 1 };\n            navigate("/", { state: data });\n        }\n        return false;\n\n    };\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWhen the \u003Ccode\u003E/login\u003C/code\u003E page shows, this call is run and if the result is that a user context is returned then it navigates to the default route \u003Ccode\u003E/\u003C/code\u003E. This all ensures that the same code runs both in the SPCS environment and in another hosting environment. By setting the \u003Ccode\u003EENVIRONMENT\u003C/code\u003E variable \u003Ccode\u003EREACT_APP_CLIENT_VALIDATION\u003C/code\u003E to \u003Ccode\u003ESnowflake\u003C/code\u003E when deploying this we ensure the method is called and evaluated.\u003C/p\u003E\n","\u003Cp\u003ERemember, the \u003Ccode\u003E/authorize\u003C/code\u003E endpoint of the backend service should return a JWT access token containing the user name and franchise when called from an authenticated context in SPCS, like the following result:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-json\"\u003E{\n    "accessToken": "eyJhbGc....goa_RUCl85NeM",\n    "refreshToken": "eyJhbGc.....VR5fnViRksNI"\n}\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAnd when decoded, that token should look something like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-json\"\u003E{\n  "user": "user1",\n  "franchise": 1,\n  "preauthorized": true,\n  "iat": 1705924945,\n  "exp": 1705946545\n}\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou can try this if you like, by starting up the backend again in a new Terminal window:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Ecd src/backend\ndocker compose up\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAnd then directly call the \u003Ccode\u003Eauthorize\u003C/code\u003E endpoint:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Ecurl --header "Sf-Context-Current-User:user1" http://localhost:3000/authorize\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ECopy the content of the \u003Ccode\u003EaccessToken\u003C/code\u003E attribute in the JSON response, and then go to \u003Ca href=\"https://jwt.io/\"\u003Ehttps://jwt.io/\u003C/a\u003E and paste the response there. This should decode the token for you and show an output like above.\u003C/p\u003E\n","\u003Cp\u003EAdditionally, if you want to verify this token, you can supply the random string we added to the \u003Ccode\u003E.env\u003C/code\u003E file for the backend.\u003C/p\u003E\n","\u003Cp\u003EThroughout the \u003Ccode\u003EHome.js\u003C/code\u003E and \u003Ccode\u003EDetails.js\u003C/code\u003E we then update all call to the backend to use the common helper function from \u003Ccode\u003EUtils.js\u003C/code\u003E to call the backend, like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-js\"\u003Econst url = `${backendURL}/franchise/${franchise}/trucks?start=${fromDate}&end=${toDate}`;\nfetch(url, getRequestOptions(location.state))\n    .then((result) => result.json())\n        .then((data) => {\n            setTop10Trucks(data)\n            let t = [];\n\n            for (let i=0; i<data.length; i++) {\n                t.push(data[i].TRUCK_BRAND_NAME);\n            }\n            setTrucks(t);\n    })\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWith those changes, the code should be ready to be Dockerized and then deployed in Snowpark Container Services.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EContainerize the Application\u003C/h2\u003E\n","\u003Cp\u003ENow we can prepare the services for deployment, and we will do that by building Docker container images for each service to deploy.\u003C/p\u003E\n","\u003Cp\u003EEnsure that you have Docker installed on you environment:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Edocker --version\n-- Docker version 24.0.6, build ed223bc\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EStep 6.1 Defining Dockerfiles for services\u003C/h3\u003E\n","\u003Cp\u003EEach service that we will spin up consists of one or more containers, and each container is built on a Docker image.\u003C/p\u003E\n","\u003Cp\u003ELet's start with the Dockerfile for the backend service. In the \u003Ccode\u003E/backend/Dockerfile\u003C/code\u003E we are exposing the port this service is exposed on. By putting it in as a variable \u003Ccode\u003E${PORT}\u003C/code\u003E we can set it through the service definition.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003EFROM node:18\n\nARG PORT\n\nWORKDIR /src/app\nCOPY package.json /src/app/package.json\n\nRUN npm install\n\nENV PORT=${PORT}\nEXPOSE ${PORT}\n\nCOPY . /src/app\n\nCMD ["npm", "run", "serve"]\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EEnsure that there is a \u003Ccode\u003E.env\u003C/code\u003E file there that will be picked up by the Docker build. It should look like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003ESNOWFLAKE_WAREHOUSE=TASTY_APP_WAREHOUSE\nSNOWFLAKE_DATABASE=FROSTBUTE_TASTY_BYTES\nSNOWFLAKE_SCHEMA=APP\n\nACCESS_TOKEN_SECRET={INSERT A RANDOM STRING HERE}\nREFRESH_TOKEN_SECRET={INSERT A RANDOM STRING HERE}\n\nPORT=3000\n\nCLIENT_VALIDATION=Snowflake \n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe frontend service will contain two containers, so we will have two Dockerfiles, one for each image we are building.\u003C/p\u003E\n","\u003Cp\u003EThe frontend itself is here \u003Ccode\u003E/frontend/frontend/Dockerfile\u003C/code\u003E:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003EFROM node:latest\n\nARG FRONTEND_SERVICE_PORT\nARG REACT_APP_BACKEND_SERVICE_URL\n\nWORKDIR /src/\nCOPY package.json /src/package.json\n\nRUN npm install\n\nENV REACT_APP_BACKEND_SERVICE_URL=${REACT_APP_BACKEND_SERVICE_URL}\n\nENV PORT=${FRONTEND_SERVICE_PORT}\nEXPOSE ${FRONTEND_SERVICE_PORT}\n\nCOPY ./src /src/src\nCOPY ./public /src/public\n\nCMD ["npm", "start"]\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EHere we also allow the service to expose a port that is set through an environment variable \u003Ccode\u003E${FRONTEND_SERVICE_PORT}\u003C/code\u003E. Additionally we inject the actual URL to the backend, i.e. what is the URL that the frontend is calling when connecting to the backend service, is also a variable \u003Ccode\u003E${REACT_APP_BACKEND_SERVICE_URL}\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EThe router that accompanies the frontend is built from a simple Dockerfile, \u003Ccode\u003E/frontend/router/Dockerfile\u003C/code\u003E:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003EFROM nginx:alpine\n\nARG required FRONTEND_SERVICE\nARG required BACKEND_SERVICE\n\nRUN apk update && apk add bash\n\nEXPOSE 8000\n\nCOPY nginx.conf.template /nginx.conf.template\n\nCMD ["/bin/sh" , "-c" , "envsubst '$FRONTEND_SERVICE $BACKEND_SERVICE' < /nginx.conf.template > /etc/nginx/nginx.conf && exec nginx -g 'daemon off;'"]\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe last line is where the \u003Ccode\u003E$FRONTEND_SERVICE\u003C/code\u003E and \u003Ccode\u003E$BACKEND_SERVICE\u003C/code\u003E variables are replaced into the configuration for the NGINX server.\u003C/p\u003E\n","\u003Ch3\u003EStep 6.2 Login to the repo\u003C/h3\u003E\n","\u003Cp\u003EWe need to connect our local Docker to the remote \u003Ca href=\"https://docs.snowflake.com/developer-guide/snowpark-container-services/working-with-registry-repository\"\u003EImage repository\u003C/a\u003E that we created in Step 4. Start by grabbing the url for the repository by running the following SQL:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE DATABASE FROSTBYTE_TASTY_BYTES;\nUSE SCHEMA APP;\nUSE ROLE tasty_app_admin_role;\n\nSHOW IMAGE REPOSITORIES;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ENow copy the value from the \u003Ccode\u003Erepository_url\u003C/code\u003E for the row for \u003Ccode\u003ETASTY_APP_REPOSITORY\u003C/code\u003E (there should only be one row). The URL should look something like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E<ACCOUNT_NAME>.registry.snowflakecomputing.com/frostbyte_tasty_bytes/app/tasty_app_repository\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EOpen up a terminal now and enter:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Eexport repo_url=<insert repo url here>\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe user then you will use to login to this Docker image repository should be a user that is granted the role \u003Ccode\u003Etasty_app_admin_role\u003C/code\u003E:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E# Snowflake user name\nexport admin_user= <your user name>\n# login to the repo.  You'll need this for the push later.\ndocker login ${repo_url} --username ${admin_user}\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EType in the password for that user when prompted.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003EPassword: \nLogin Succeeded\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWith this, you can now push Docker images to this repository.\u003C/p\u003E\n","\u003Ch3\u003EStep 6.3 Build and push up the image\u003C/h3\u003E\n","\u003Cp\u003EWhen building and pushing an image to the repo, we do a number of steps to ensure we build the image locally, tag it and then push it to the remote repository. Here is how the backend service is build in the \u003Ccode\u003E./build-all.sh\u003C/code\u003E file:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Eexport image_name=backend_service_image\ndocker image rm ${image_name}:${tag}\ndocker build --rm --platform linux/amd64 -t ${image_name}:${tag} ./backend\ndocker image rm ${repo_url}/${image_name}:${tag}\ndocker tag ${image_name}:${tag} ${repo_url}/${image_name}:${tag}\ndocker push ${repo_url}/${image_name}:${tag}\necho ${repo_url}/${image_name}:${tag}\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ENote here that we are specifying to build the image directly for the \u003Ccode\u003Elinux/amd64\u003C/code\u003E architecture, this is needed for running it on the nodes in the compute pool for Snowpark Container Services. This may not be an image that can then be run on your local system, depending on the CPU architecture on that. It is important that we build it using this flag, otherwise it will not run on SPCS.\u003C/p\u003E\n","\u003Cp\u003EWe can now build and push all images to the Snowflake repository, from \u003Ccode\u003E/src\u003C/code\u003E run:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E./build-all.sh \n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EOnce that finishes, you can verify in a Snowflake worksheet that the images have been pushed to the repository:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESHOW IMAGES IN IMAGE REPOSITORY TASTY_APP_REPOSITORY;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe output should be similar to this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-json\"\u003E{\n   "images":[\n      "backend_service_image",\n      "frontend_service_image",\n      "router_service_image"\n   ]\n}\n\u003C/code\u003E\u003C/pre\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ECreate the Services\u003C/h2\u003E\n","\u003Ch3\u003EStep 7.1 Creating the Service in Snowflake\u003C/h3\u003E\n","\u003Cp\u003EThe services can now be created in Snowflake. Go back to Snowflake and open a worksheet. Enter the following to create the backend service. The \u003Ccode\u003ECREATE SERVICE\u003C/code\u003E command creates a new service.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE DATABASE FROSTBYTE_TASTY_BYTES;\nUSE SCHEMA APP;\nUSE ROLE tasty_app_admin_role;\n\nCREATE SERVICE backend_service\n  IN COMPUTE POOL tasty_app_backend_compute_pool\n  FROM SPECIFICATION $$\nspec:\n  container:\n  - name: backend\n    image: /frostbyte_tasty_bytes/app/tasty_app_repository/backend_service_image:tutorial\n    env:\n      PORT: 3000\n      ACCESS_TOKEN_SECRET: {INSERT A RANDOM STRING HERE}\n      REFRESH_TOKEN_SECRET: {INSERT ANOTHER RANDOM STRING HERE}\n      CLIENT_VALIDATION: Snowflake\n  endpoint:\n  - name: apiendpoint\n    port: 3000\n    public: true\n$$\n  MIN_INSTANCES=1\n  MAX_INSTANCES=1\n;\nGRANT SERVICE ROLE backend_service!ALL_ENDPOINTS_USAGE TO ROLE tasty_app_ext_role;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis creates the backend service using the image \u003Ccode\u003Ebackend_service_image:tutorial\u003C/code\u003E that we should now have pushed to the repository. Note how we can supply overriding environment variables to the services.\u003C/p\u003E\n","\u003Cp\u003EWe also set this service to use the \u003Ccode\u003Etasty_app_backend_compute_pool\u003C/code\u003E as the \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowpark-container-services/working-with-compute-pool\"\u003ECOMPUTE POOL\u003C/a\u003E to run the service on. At the end we can set the scaling behavior of this service in the pool. In order to test this service we don't need any additional scaling setup here, but in a real scenario we may want to increase the number of instances available in case the load on the service goes up.\u003C/p\u003E\n","\u003Cp\u003ELastly we call \u003Ccode\u003EGRANT USAGE ON SERVICE\u003C/code\u003E to allow the \u003Ccode\u003Etasty_app_ext_role\u003C/code\u003E role and users with that role granted access to the service.\u003C/p\u003E\n","\u003Cp\u003EWe can then call \u003Ccode\u003ESHOW SERVICES\u003C/code\u003E to look at the services created. In order to check the status of the newly created service we can call:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESHOW SERVICE CONTAINERS IN SERVICE backend_service;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWhich will return the status of the service. After a few moments the service should report status \u003Ccode\u003EREADY\u003C/code\u003E and that it is running:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-json\"\u003E[\n   {\n      "status":"READY",\n      "message":"Running",\n      "containerName":"backend",\n      "instanceId":"0",\n      "serviceName":"BACKEND_SERVICE",\n      "image":"<ACCOUNT_NAME>.registry.snowflakecomputing.com/frostbyte_tasty_bytes/app/tasty_app_repository/backend_service_image:tutorial",\n      "restartCount":0,\n      "startTime":"<CREATE TIME>"\n   }\n]\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWe can also look directly at the \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowpark-container-services/working-with-services#accessing-local-container-logs\"\u003Elogs from the service itself\u003C/a\u003E, anything that is written to the standard logging can be retrieved from the service logs:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ECALL SYSTEM$GET_SERVICE_LOGS('backend_service', '0', 'backend', 50);\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EShould show a log looking like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E> serve\n> node app.js\n\nStarting up Node Express, build version 00014\nServer running on port 3000\nEnvironment: development\nClient validation: Snowflake\nUsing warehouse: tasty_app_warehouse\nUsing role: TASTY_APP_ADMIN_ROLE\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe frontend service can now be created in a similar fashion. The difference here is that it will contain two different containers, we are using both the image for the router and the frontend React app inside the same service.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ECREATE SERVICE frontend_service\n  IN COMPUTE POOL tasty_app_frontend_compute_pool\n  FROM SPECIFICATION $$\nspec:\n  container:\n  - name: frontend\n    image: /frostbyte_tasty_bytes/app/tasty_app_repository/frontend_service_image:tutorial\n    env:    \n      PORT: 4000\n      FRONTEND_SERVICE_PORT: 4000\n      REACT_APP_BACKEND_SERVICE_URL: /api\n      REACT_APP_CLIENT_VALIDATION: Snowflake\n  - name: router\n    image: /frostbyte_tasty_bytes/app/tasty_app_repository/router_service_image:tutorial\n    env:\n      FRONTEND_SERVICE: localhost:4000\n      BACKEND_SERVICE: backend-service:3000\n  endpoint:\n  - name: routerendpoint\n    port: 8000\n    public: true\n$$\n  MIN_INSTANCES=1\n  MAX_INSTANCES=1\n;\nGRANT SERVICE ROLE frontend_service!ALL_ENDPOINTS_USAGE TO ROLE tasty_app_ext_role;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EIn the same way we can check the status of the service and read the logs. Note that there are two logs to read, one for each container in the service.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESHOW SERVICE CONTAINERS IN SERVICE frontend_service;\nCALL SYSTEM$GET_SERVICE_LOGS('frontend_service', '0', 'frontend', 50);\nCALL SYSTEM$GET_SERVICE_LOGS('frontend_service', '0', 'router', 50);\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe log for the \u003Ccode\u003Efrontend\u003C/code\u003E container in the \u003Ccode\u003Efrontend_service\u003C/code\u003E should look something like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E> tasty_app@0.1.0 start\n> react-scripts start\n  \nCompiled successfully!\n\nYou can now view tasty_app in the browser.\n\n  Local:            http://localhost:4000\n  On Your Network:  http://10.244.2.15:4000\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EStep 7.2 Testing the service\u003C/h3\u003E\n","\u003Cp\u003EWe are now finally ready to test the application in a browser. In order to do that we need the public endpoint exposed by the frontend_service. Call \u003Ccode\u003ESHOW ENDPOINTS\u003C/code\u003E to retrieve that:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESHOW ENDPOINTS IN SERVICE frontend_service;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe \u003Ccode\u003Eingress_url\u003C/code\u003E in the response is the public endpoint URL, it should look similar to this, the first part is randomly generated for each endpoint and service:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E<RANDOM>-<ACCOUNT NAME>.snowflakecomputing.app\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ENow open up that URL in a browser. You will be prompted for a login, and here we can choose any of the users created earlier. You can use \u003Ccode\u003Euser1\u003C/code\u003E with password \u003Ccode\u003Epassword1\u003C/code\u003E. Note that you will be forced to change this on first login.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/authenticating_with_snowservices_ingress.png\" alt=\"Tasty App UI\"\u003E\u003C/p\u003E\n","\u003Cp\u003EOnce logged in, the application loads the authorization status, and then redirects the user to the logged in \u003Ccode\u003EHome\u003C/code\u003E page. After a few moments the data is loaded also and the charts for the current franchise (Franchise 1, if you logged in with user1) is shown.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/tasty-app-ui.png\" alt=\"Tasty App UI\"\u003E\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EClean up resources\u003C/h2\u003E\n","\u003Cp\u003EOnce we have tested the application we can tear down any resources that we have created. The following resouces should be removed:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EServices\u003C/li\u003E\u003Cli\u003ECompute Pools\u003C/li\u003E\u003Cli\u003EWarehouses\u003C/li\u003E\u003Cli\u003EImage Repositories\u003C/li\u003E\u003Cli\u003EDatabase and Schema\u003C/li\u003E\u003Cli\u003ESecurity Integration (NOTE: this may be used by other services, you can only have one active per ACCOUNT)\u003C/li\u003E\u003Cli\u003ERoles\u003C/li\u003E\u003Cli\u003EUsers\u003C/li\u003E\u003Cli\u003ELocal Docker images\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EOpen a worksheet in Snowflake and run the following SQL:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE DATABASE FROSTBYTE_TASTY_BYTES;\nUSE SCHEMA APP;\nUSE ROLE tasty_app_admin_role;\n\n-- Delete services\nSHOW SERVICE;\nDROP SERVICE BACKEND_SERVICE;\nDROP SERVICE FRONTEND_SERVICE;\n\n-- Delete compute pools\nSHOW COMPUTE POOLS;\nUSE ROLE ACCOUNTADMIN;\nDROP COMPUTE POOL TASTY_APP_BACKEND_COMPUTE_POOL;\nDROP COMPUTE POOL TASTY_APP_FRONTEND_COMPUTE_POOL;\n\n-- Delete warehouses\nSHOW WAREHOUSES;\nDROP WAREHOUSE LOAD_WH;\nDROP WAREHOUSE QUERY_WH;\nDROP WAREHOUSE TASTY_APP_WAREHOUSE;\n\n-- Delete the Image repository\nUSE ROLE tasty_app_admin_role;\nSHOW IMAGE REPOSITORIES;\nDROP IMAGE REPOSITORY TASTY_APP_REPOSITORY;\n\n-- Delete the database\nUSE ROLE ACCOUNTADMIN;\nSHOW DATABASES;\nDROP DATABASE FROSTBYTE_TASTY_BYTES;\n\n-- Delete the roles\nUSE ROLE ACCOUNTADMIN;\nSHOW ROLES;\nDROP ROLE TASTY_APP_ADMIN_ROLE;\nDROP ROLE TASTY_APP_EXT_ROLE;\n\n-- Delete the users\nSHOW USERS;\nDROP USER USER1;\nDROP USER USER2;\nDROP USER USER3;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EFrom a terminal, we can now also remove the built images:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Edocker image prune --all\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EWarning, the above removes \u003Cem\u003Eall\u003C/em\u003E unused Docker images. If you have other Docker images that you don't want to remove, then manually remove the images created in this guide using \u003Ccode\u003Edocker image rm <IMAGE NAME>\u003C/code\u003E.\u003C/p\u003E\n\u003C/blockquote\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EConclusion and Resources\u003C/h2\u003E\n","\u003Cp\u003EGood work! You have now successfully built, deployed and run a data application on Snowpark Container Services.\u003C/p\u003E\n","\u003Ch3\u003EWhat You Learned\u003C/h3\u003E\n","\u003Cp\u003EYou now have gone through the basic concepts of building a a Data Application that can run directly on Snowflake, we have looked through how to adapt existing code to cover:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EAuthentication and Authorization and user management\u003C/li\u003E\u003Cli\u003EPublic endpoints for service\u003C/li\u003E\u003Cli\u003EService to service communication\u003C/li\u003E\u003Cli\u003EServices connecting to Snowflake accounts\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EUsing this you should be able to build your own Data Application and run it directly on Snowpark Container Services, directly connected to your data.\u003C/p\u003E\n","\u003Cp\u003EWe would love your feedback on this QuickStart Guide! Please submit your feedback using this Feedback Form.\u003C/p\u003E\n","\u003Ch3\u003ERelated Resources\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://github.com/Snowflake-Labs/sfguide-tasty-bytes-zero-to-app-with-spcs\"\u003ESource Code on GitHub\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowpark-container-services/overview\"\u003ESnowpark Container Services documentation\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowpark-container-services/overview-tutorials\"\u003ESnowpark Container Services tutorials\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"/en/developers/guides/build-a-data-app-with-snowflake/\"\u003EQuickstart: Build a Data App with Snowflake\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E\n<!-- ------------------------ -->"],"description":"Build and deploy data applications on Snowpark Container Services for secure, scalable app hosting within your Snowflake account.","title":"Build a Data App and run it on Snowpark Container Services","isDeveloperGuidesPage":false,":type":"snowflake-site/components/contentfragment",":items":{},":itemsOrder":[],"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],"elements":{"quickstartArticleBody":{"dataType":"string","title":"Quickstart Article Body","value":"\u003C!-- ------------------------ --\u003E\n## Overview \n\nSnowflake is a terrific platform on which to build data applications. The unique characteristics and cloud-based design allow for building applications that scale with data and workload. This tutorial will go through how to build and deploy both the Processing Layer and the User Interface Layer paired with Snowflake as the Persistence Layer.\n\nOur example will be using a fictional food truck franchise website, Tasty Bytes. We will be building a graphical user interface with charts and graphs for franchisees to be able to examine sales data related to their franchise of food trucks. After logging in via a login page, each franchisee will have one page that will show metrics at the franchise level, and another that will show metrics around the food truck brands for that franchise.\n\nThe Processing and User Interface Layers will be built using Node.js. The dataset is an orders history for Tasty Bytes. \n\nThe application itself will be built using containers and deployed to Snowflake. Snowpark Container Services (SPCS) allows the running of containerized workloads directly within Snowflake, ensuring that data doesn’t need to be moved out of the Snowflake environment for processing. \n\nThis lab builds directly on the same code and solution as the [Build a Data App with Snowflake](/en/developers/guides/build-a-data-app-with-snowflake/) quickstart, for in depth walk-through of the use case and the data, and how the application is built using Node Express and React you can review each step in that guide as well. \n\n### Prerequisites\n- A Snowflake account, and familiarity with the Snowsight interface\n- Privileges necessary to create a user, database, and warehouse in Snowflake\n- Basic experience using git\n- Intermediate knowledge of Node.js and React JS\n- Intermediate knowledge of containerised applications\n\n- GitHub Codespaces -or- Ability to install and run software on your computer\n\n\n\u003E \n\u003E **Snowpark Container Services availability**\n\u003E \n\u003E  Snowpark Container Services is currently available across a [range of cloud providers and regions](https://docs.snowflake.com/en/developer-guide/snowpark-container-services/overview#label-snowpark-containers-overview-available-regions). For this lab ensure that you have an account in one of the supported regions.\n\n### What You’ll Learn \n- How to configure and build a custom API Powered by Snowflake, written in Node.js\n- How to configure and build a custom frontend website to communicate with the API, written in React and Node.js\n- How to deploy a containerised application to Snowpark Container Services\n- How to run and test the frontend and API on your machine\n\n### What You’ll Need \n#### Option 1, using GitHub Codespaces:\n- [GitHub Codespaces](https://github.com/) GitHub Account with credits for GitHub Codespaces\n#### Option 2, local build:\n- [VSCode](https://code.visualstudio.com/download) Installed\n- [Docker](https://docs.docker.com/get-docker/) Installed\n- [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) Installed\n- [NodeJS](https://nodejs.org/en/download/) Installed\n- [NPM](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) Installed\n\n### What You’ll Build \nIn this quickstart we will build and deploy a Data Application running on Snowpark Container Services.\n\n![Service Overview](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/build-a-data-app-spcs-overview.png)\n\nThe solution consists of two services hosted on Snowpark Container Services:\n- **The backend service** - which hosts the API built on Node Express - API Powered by Snowflake built in Node.js\n- **The frontend service** - which hosts the React JS Web Application that connects to that API, and a router service in NGINX that allows calls from the browser-based React frontend to be routed to the backend services also.\n\nWithout the router part of the frontend service, CORS would actually prevent the browser from talking to the backend service, even if we opened up a public endpoint for it. This is due to the fact that we cannot add our own headers to requests coming to the service endpoints - for security reasons Snowpark Container Services networking strips out any headers (but adds a few useful ones that we will use for authentication later).\n\n\n\n\n\n\n\n\u003C!-- ------------------------ --\u003E\n\n\n## Set up the Data\n\n### Overview\nIn this part of the lab we'll set up our Snowflake account, create database structures to house our data, create a Virtual Warehouse to use for data loading and finally load our Tasty Bytes Food Truck orders data into our ORDERS table and run a few queries to get familiar with the data.\n\n\u003E \n\u003E\n\u003E The sample data for the quickstart that we load will only cover the dates between 2022-01-01 to 2022-10-31. Don't be alarmed if a query on a data later or earlier than that returns an empty response\n\n\n### Step 2.1 Initial Snowflake Setup\n\nFor this part of the lab we will want to ensure we run all steps as the ACCOUNTADMIN role \n```sql\n--change role to accountadmin\nuse role accountadmin;\n```\n\nFirst we can create a [Virtual Warehouse](https://docs.snowflake.com/en/user-guide/warehouses-overview) that can be used for data exploration and general querying in this lab.  We'll create this warehouse with a size of `Medium` which is right sized for that use case in this lab.  \n```sql\n--create a virtual warehouse for data exploration\ncreate or replace warehouse query_wh with \n\twarehouse_size = 'medium' \n\twarehouse_type = 'standard' \n\tauto_suspend = 300 \n\tauto_resume = true \n\tmin_cluster_count = 1 \n\tmax_cluster_count = 1;\n```\n\n### Step 2.2 Load Data\n\nNext we will create a database and schema that will house the tables that store our application data.\n```sql\n--create the application database and schema\ncreate or replace database frostbyte_tasty_bytes;\ncreate or replace schema app;\n```\n\nThis DDL will create the structure for the ORDERS table which is the main source of data for our application in this lab. \n```sql\n--create table structure for order data \ncreate or replace table orders (\n\torder_id number(38,0),\n\ttruck_id number(38,0),\n\torder_ts timestamp_ntz(9),\n\torder_detail_id number(38,0),\n\tline_number number(38,0),\n\ttruck_brand_name varchar(16777216),\n\tmenu_type varchar(16777216),\n\tprimary_city varchar(16777216),\n\tregion varchar(16777216),\n\tcountry varchar(16777216),\n\tfranchise_flag number(38,0),\n\tfranchise_id number(38,0),\n\tfranchisee_first_name varchar(16777216),\n\tfranchisee_last_name varchar(16777216),\n\tlocation_id number(19,0),\n\tcustomer_id number(38,0),\n\tfirst_name varchar(16777216),\n\tlast_name varchar(16777216),\n\te_mail varchar(16777216),\n\tphone_number varchar(16777216),\n\tchildren_count varchar(16777216),\n\tgender varchar(16777216),\n\tmarital_status varchar(16777216),\n\tmenu_item_id number(38,0),\n\tmenu_item_name varchar(16777216),\n\tquantity number(5,0),\n\tunit_price number(38,4),\n\tprice number(38,4),\n\torder_amount number(38,4),\n\torder_tax_amount varchar(16777216),\n\torder_discount_amount varchar(16777216),\n\torder_total number(38,4)\n);\n```\n\nFor loading data into the ORDERS table we will create a new Virtual Warehouse sized as a `Large` to help us quickly ingest the data we have stored in an S3 bucket. \n```sql\n--create a virtual warehouse for data loading\ncreate or replace warehouse load_wh with \n\twarehouse_size = 'large' \n\twarehouse_type = 'standard' \n\tauto_suspend = 300 \n\tauto_resume = true \n\tmin_cluster_count = 1 \n\tmax_cluster_count = 1;\n```\nNext we have to create a [STAGE](https://docs.snowflake.com/en/user-guide/data-load-overview) which is a Snowflake object that points to a cloud storage location Snowflake can access to both ingest and query data.  In this lab the data is stored in a publicly accessible AWS S3 bucket which we are referencing when creating the Stage object. \n```sql\n--create stage for loading orders data\ncreate or replace stage tasty_bytes_app_stage\n\turl = 's3://sfquickstarts/frostbyte_tastybytes/app/orders/';\n```\nOnce we've created both the Virtual Warehouse we want to use for loading data and the Stage which points to where the data resides in cloud storage we can simply [COPY](https://docs.snowflake.com/en/sql-reference/sql/copy-into-table) the data from that Stage into our ORDERS table. \n```sql\n--copy data into orders table using the load wh\n copy into orders from @tasty_bytes_app_stage;\n```\n\n\n### Step 2.3 Explore Data\nNow that we've loaded our data into the ORDERS table we can run a few queries to get familiar with it - but first we will want to change the Virtual Warehouse we're using from the `LOAD_WH` back to the `QUERY_WH` created earlier in the lab. \n```sql\n--change our Virtual Warehouse context to use our query_wh\n use warehouse query_wh;\n```\n\nTo begin with we can simply look at a sample of the entire table.\n```sql \n--simple query to look at 10 rows of data \nselect * from orders limit 10;\n```\n\nNext we can see how many records we've loaded into the table.  Notice how quickly the query executes - this is due to Snowflake's unique architecture which enables a certain class of queries like this one to pull results from metadata instead of requiring compute to generate the result. \n```sql \n--query to count all records in the table\nselect count(*) from orders;\n```\n\nFinally we can run a more complex query to look at the total revenue by month where we will use a couple of [functions](https://docs.snowflake.com/en/sql-reference-functions) to parse the month number and name from the ORDER_TS column in the ORDERS table. \n```sql\n--sales by month\nselect month(order_ts),monthname(order_ts), sum(price)\nfrom orders \ngroup by month(order_ts), monthname(order_ts)\norder by month(order_ts);\n```\n### Step 2.4 Further explore the Data\n\nTo understand and explore the data even more, you can look through the [Quickstart for Building a Data Application - Lab 2: Queries](/en/developers/guides/build-a-data-app-with-snowflake/) that offers a number of steps to explore it.\n\nIf you already have done that, you can move directly to the next step in this guide. If not, you can continue below and explore the data further.\n\nOur queries will be broken into two groups - `Franchise` queries and `Truck Brand` level queries.  For the sake of ease we will focus on the following Franchise, Truck Brand and Date Range for this part of the lab.\n\n* Franchise:  `1`\n* Truck Brand: `Guac 'n Roll`\n* Date Range: `1/1/2023 - 3/31/2023`\n\n### Setting Snowsight Context\nTo ensure the correct context is use for these queries we will set our database, schema and Virtual Warehouse using the following SQL:\n```sql\n--set query context\nuse database frostbyte_tasty_bytes;\nuse schema app;\nuse warehouse query_wh;\n```\n\n### Franchise Queries\nTo answer the business questions about how our overall Franchise business is doing we'll need to create the three following queries.  All of the columns required for these exist in the ORDERS table and no joining of tables are required. \n\n1. Top 10 Countries Based on Revenue in a Time Window\n2. Top 10 Truck Brands Based on Revenue in a Time Window\n3. Year-to-Date Revenue, by Month, per Truck Brand\n\nYou can spend some time creating the queries for each of these and then check your answers against the provided queries below by expanding each section. \n\n\u003Cstrong\u003ETop 10 Countries Based on Revenue in a Time Window\u003C/strong\u003E\n\n```sql\n    SELECT\n        TOP 10 country,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n        date(order_ts) \u003E= '2023-01-01'\n        AND date(order_ts) \u003C= '2023-03-31'\n        AND franchise_id = 1\n    GROUP BY\n        country\n    ORDER BY\n        sum(price) desc;\n```\n\u003Cstrong\u003ETop 10 Truck Brands Based on Revenue in a Time Window\u003C/strong\u003E\n\n```sql\n    SELECT\n        TOP 10 truck_brand_name,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n        date(order_ts) \u003E= '2023-01-01'\n        AND date(order_ts) \u003C= '2023-03-31'\n        AND franchise_id = 1\n    GROUP BY\n        truck_brand_name\n    ORDER BY\n        sum(price) desc;\n```\n\u003Cstrong\u003EYear-to-Date Revenue, by Month, per Truck Brand\u003C/strong\u003E\n\n```sql\n    SELECT\n        country,\n        month(order_ts) as date,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n         year(order_ts) = 2023\n        AND franchise_id = 1\n    GROUP BY\n        country,\n        month(order_ts)\n    ORDER BY\n        sum(price) desc;\n```\n\n### Truck Brand Queries\nTo answer the business questions about how our overall Franchise business is doing we'll need to create the three following queries.  All of the columns required for these exist in the ORDERS table and no joining of tables are required. \n\n1. Total Sales by Day-of-Week\n2. Top Selling Items\n3. Top Selling items by Day-of-Week\n4. \n\nYou can spend some time creating the queries for each of these and then check your answers against the provided queries below by expanding each section. \n\n\u003Cstrong\u003ETop 10 Countries Based on Revenue in a Time Window\u003C/strong\u003E\n\n```sql\n    SELECT\n        TOP 10 country,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n        date(order_ts) \u003E= '2023-01-01'\n        AND date(order_ts) \u003C= '2023-03-31'\n        AND franchise_id = 1\n    GROUP BY\n        country\n    ORDER BY\n        sum(price) desc;\n```\n\u003Cstrong\u003ETop 10 Truck Brands Based on Revenue in a Time Window\u003C/strong\u003E\n\n```sql\n    SELECT\n        TOP 10 truck_brand_name,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n        date(order_ts) \u003E= '2023-01-01'\n        AND date(order_ts) \u003C= '2023-03-31'\n        AND franchise_id = 1\n    GROUP BY\n        truck_brand_name\n    ORDER BY\n        sum(price) desc;\n```\n\u003Cstrong\u003ETotal Sales by City and Day-of-Week\u003C/strong\u003E\n\n```sql\n    SELECT\n        country,\n        month(order_ts) as date,\n        sum(price) AS revenue\n    FROM\n        app.orders\n    WHERE\n         year(order_ts) = 2023\n        AND franchise_id = 1\n    GROUP BY\n        country,\n        month(order_ts)\n    ORDER BY\n        sum(price) desc;\n```\n\n\n\n\n\n\n\n\n\n\u003C!-- ------------------------ --\u003E\n\n## Setup Snowflake\n\n### Overview\nNow that we've created our database, loaded data and developed the queries needed to answer our business questions, the last step before getting into application code is setting up the necessary objects so that the application can connect to Snowflake securely and query data on its own Virtual Warehouse. We will also set up the objects required to create and run services. The objects we will look at are:\n\n- [Compute Pools](https://docs.snowflake.com/developer-guide/snowpark-container-services/working-with-compute-pool) that are responsible for providing compute to the services once they run.\n- [Image Repositories](https://docs.snowflake.com/developer-guide/snowpark-container-services/working-with-registry-repository) that can hold docker images used by the services we create\n- [Services Ingress Security Integration](https://docs.snowflake.com/en/developer-guide/snowpark-container-services/working-with-services?utm_source=legacy&utm_medium=serp&utm_term=snowservices_ingress#ingress-using-a-service-from-outside-snowflake)\n\n### Step 3.1 Creating roles, permissions and virtual warehouse for running the application\n\nMuch like we created separate Virtual Warehouses for exploring and loading data, we will create one specifically for our service to use when executing queries on Snowflake.\n\nWe start by creating a role that can be responsible for administering the setup of the services and everything else. There are a number of permissions that can be granted, and in a production build environment, these permissions may instead be granted to different roles with different responsibilities.\n\n```sql\nUSE ROLE accountadmin;\nUSE DATABASE frostbyte_tasty_bytes;\nUSE SCHEMA APP;\n\nCREATE ROLE tasty_app_admin_role;\n\nGRANT ALL ON DATABASE frostbyte_tasty_bytes TO ROLE tasty_app_admin_role;\nGRANT ALL ON SCHEMA frostbyte_tasty_bytes.app TO ROLE tasty_app_admin_role;\nGRANT SELECT ON ALL TABLES IN SCHEMA frostbyte_tasty_bytes.app TO ROLE tasty_app_admin_role;\nGRANT SELECT ON FUTURE TABLES IN SCHEMA frostbyte_tasty_bytes.app TO ROLE tasty_app_admin_role;\n```\n\nWe can now create a Virtual Warehouse that the application will use to execute queries.\n```sql\nCREATE OR REPLACE WAREHOUSE tasty_app_warehouse WITH\nWAREHOUSE_SIZE='X-SMALL'\nAUTO_SUSPEND = 180\nAUTO_RESUME = true\nINITIALLY_SUSPENDED=false;\n\nGRANT ALL ON WAREHOUSE tasty_app_warehouse TO ROLE tasty_app_admin_role;\n```\n\n### Step 3.2 Creating Compute Pools for service to run on\n\nThe Compute Pools are used to run the services. We can create different pools for different purposes. In this example we create two different pools to run the services, one for the backend and one for the frontend. We could technically allow both services to use the same Compute Pool, in fact for this demo it would work very well, but in many scenarios the scaling requirements for the frontend and a backend may be different. Here we can see that the backend is given a pool of compute nodes that is slightly more scaled up than the nodes for the compute pool used for the frontend. There are multiple options for choosing the right instance family for a Compute Pool [Create Compute Pool](https://docs.snowflake.com/sql-reference/sql/create-compute-pool). This would be even more relevant if the backend needed to do some more compute heavy work, even to the point where it needed to have GPU enabled nodes.\n```sql\nCREATE COMPUTE POOL tasty_app_backend_compute_pool\nMIN_NODES = 1\nMAX_NODES = 1\nINSTANCE_FAMILY = CPU_X64_S;\n\nGRANT USAGE ON COMPUTE POOL tasty_app_backend_compute_pool TO ROLE tasty_app_admin_role;\nGRANT MONITOR ON COMPUTE POOL tasty_app_backend_compute_pool TO ROLE tasty_app_admin_role;\n\nCREATE COMPUTE POOL tasty_app_frontend_compute_pool\nMIN_NODES = 1\nMAX_NODES = 1\nINSTANCE_FAMILY = CPU_X64_XS;\n\nGRANT USAGE ON COMPUTE POOL tasty_app_frontend_compute_pool TO ROLE tasty_app_admin_role;\nGRANT MONITOR ON COMPUTE POOL tasty_app_frontend_compute_pool TO ROLE tasty_app_admin_role;\n```\n\nThe `tasty_app_admin_role` role must also be given the permission to bind service endpoints for services.\n```sql \nGRANT BIND SERVICE ENDPOINT ON ACCOUNT TO ROLE tasty_app_admin_role;\n```\n\n### Step 3.3 Set up docker image repositories and stage for service specifications\n\nWe can now ensure that the current user can use the admin role.\n```sql \nSET sql = ('GRANT ROLE tasty_app_admin_role TO USER ' || CURRENT_USER() || '');\nEXECUTE IMMEDIATE $sql;\nUSE ROLE tasty_app_admin_role;\n```\n\nHere we create the [`IMAGE REPOSITORY`](https://docs.snowflake.com/developer-guide/snowpark-container-services/working-with-registry-repository) to hold images for services.\n```sql\n-- Create image repository  \nCREATE OR REPLACE IMAGE REPOSITORY tasty_app_repository;\n-- Show the repo we just created\nSHOW IMAGE REPOSITORIES;\n-- List images in repo (can be called later to verify that images have been pushed to the repo)\nSHOW IMAGES IN IMAGE REPOSITORY TASTY_APP_REPOSITORY;\n```\n\nWe can also create a stage to hold service specification files, although for this guide we will provide the specifications inline with the service creation. \n```sql\n-- Create a stage to hold service specification files\nCREATE STAGE tasty_app_stage DIRECTORY = ( ENABLE = true );\n```\n\n\n### Step 3.4 Create external users role and users for the external access\n\nIn order to allow the application users to access the application we can create dedicated `USERS` for each user. In the guide [Build a Data App with Snowflake](/en/developers/guides/build-a-data-app-with-snowflake/) users were actually stored in a `USERS` table that was created, where hashed passwords were stored and could be used to check the login from the frontend. Create that table by running the following SQL:\n\n```sql\n-- Create Users table for the Website\ncreate or replace table users (\n\tuser_id number(38,0) autoincrement,\n\tuser_name varchar(16777216) not null,\n\thashed_password varchar(16777216),\n\tfranchise_id number(38,0),\n\tpassword_date timestamp_ntz(9),\n\tstatus boolean,\n\tunique (user_name)\n);\n\n -- Add Franchisee logins \ninsert into users\n    values\n    (1,'user1','$2b$10$v0IoU/pokkiM13e.eayf1u3DkgtIBMGO1uRO2O.mlb2K2cLztV5vy',1,current_timestamp,TRUE), \n    (2,'user2','$2b$10$e2TXM/kLlazbH1xl31SeOe6RTyfL3E9mE8sZZsU33AE52rO.u44JC',120,current_timestamp,TRUE),\n    (3,'user3','$2b$10$WX4e1LAC.rAabBJV58RuKerEK4T/U4htgXrmedTa5oiGCWIRHwe0e',271,current_timestamp,TRUE);\n```\n\n\nIn this guide, we will create those users as actual Snowflake Users and give them a role that is allowed to access the services we later create. This allows us to utilize the OAuth sign-in we created earlier to authenticate users.\n\nWe can create the users like this:\n```sql\nUSE ROLE ACCOUNTADMIN;\nCREATE ROLE tasty_app_ext_role;\n\nGRANT USAGE ON DATABASE frostbyte_tasty_bytes TO ROLE tasty_app_ext_role;\nGRANT USAGE ON SCHEMA app TO ROLE tasty_app_ext_role;\n\nCREATE USER IF NOT EXISTS user1 PASSWORD='password1' MUST_CHANGE_PASSWORD=TRUE DEFAULT_ROLE=tasty_app_ext_role;\nGRANT ROLE tasty_app_ext_role TO USER user1;\n```\n\nNot that we force the user to change the password on the first login here. When testing it you can choose to set `MUST_CHANGE_PASSWORD=FALSE`, but in a real scenario these passwords should be changed on first login.\n\nJust for reference, the users that were created in the earlier database set up lab are the following:\n\n| User name | Hashed password | Franchise id | Plaintext password |\n| ------- | --------- | --------------- | ------------ |\n| user1\t| $2b$10$3/teX....iH7NI1SjoTjhi74a\t| 1\t| password1 |\n| user2\t| $2b$10$9wdGi....U8qeK/nX3c9HV8VW\t| 120\t| password120 |\n| user3\t| $2b$10$CNZif....IXZFepwrGtZbGqIO\t| 271\t| password271 |\n\nWe can create all the users this way:\n```sql\nCREATE USER IF NOT EXISTS user2 PASSWORD='password120' MUST_CHANGE_PASSWORD=TRUE DEFAULT_ROLE=tasty_app_ext_role;\nGRANT ROLE tasty_app_ext_role TO USER user2;\n\nCREATE USER IF NOT EXISTS user3 PASSWORD='password270' MUST_CHANGE_PASSWORD=TRUE DEFAULT_ROLE=tasty_app_ext_role;\nGRANT ROLE tasty_app_ext_role TO USER user3;\n```\n\n\n\n\n\n\n\n\n\n\u003C!-- ------------------------ --\u003E\n\n## Building the backend code\n\n### Overview\nWe now look at the code for the backend and frontend to adapt it to run in Snowpark Container Services.\n\n#### Option 1 - Build using GitHub Codespaces\nIf you have access to GitHub and credits on an account that let's you run GitHub Codespaces, you can directly build the entire code and push the containerized images to the image repository in the cloud environment.\n\nIf you don't have access to this, or prefer to build this locally, go to Option 2 instead.\n\nFirst, create your own fork of the main repository, go to the GitHub repository at [GitHub: Snowflake-Labs/sfguide-tasty-bytes-zero-to-app-with-spcs](https://github.com/Snowflake-Labs/sfguide-tasty-bytes-zero-to-app-with-spcs.git) and create your own fork of the repo.\n![Fork Repository](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/fork_repository.png)\n\nOnce you have your own fork, go to the '\u003C\u003E CODE' button and select 'Codespaces' and create a new codespace.\n![Create Codespace](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/create_codespace.png)\n\n#### Option 2 - Build locally\nThe code for this lab is hosted on GitHub. Start by cloning the repository into a separate folder. Note that we are cloning a specific branch `spcs` here that contains the code adapted for this guide.\n```bash\ngit clone https://github.com/Snowflake-Labs/sfguide-tasty-bytes-zero-to-app-with-spcs.git zero-to-app-spcs\n```\n\nChange directory to the `zero-to-app-spcs/` directory that is created in the clone above. You should now have a directory with a `/src` subdirectory that contains `/backend` and `/frontend` directories. \n\n### Step 4.1 The backend service\nLet's start with looking at the backend code. Open a terminal and go to the `/src/backend` directory.\n\nFirst ensure that you have Docker installed on you environment:\n```bash\ndocker --version\n-- Docker version 24.0.6, build ed223bc\n```\n\nFor local testing, we can then let the backend connect to the Snowflake account using credentials we supply in the environment variables. Copy the `.env.example` file to `.env` and fill out the details for your account there. \n```bash\ncd .../zero-to-app-spcs/src/backend\ncp .env.example .env\nsed -i -e \"s/{INSERT A RANDOM STRING HERE}/$(openssl rand -base64 12)/\" .env\nsed -i -e \"s/{INSERT ANOTHER RANDOM STRING HERE}/$(openssl rand -base64 12)/\" .env\n```\n```bash\nSNOWFLAKE_ACCOUNT={INSERT_ACCOUNT_NAME_HERE}\nSNOWFLAKE_USERNAME={INSERT_USER_NAME_HERE}\nSNOWFLAKE_PASSWORD={INSERT_PASSWORD_HERE}\nSNOWFLAKE_ROLE=TASTY_APP_ADMIN_ROLE\nSNOWFLAKE_WAREHOUSE=TASTY_APP_WAREHOUSE\nSNOWFLAKE_DATABASE=frostbyte_tasty_bytes\nSNOWFLAKE_SCHEMA=app\n\nACCESS_TOKEN_SECRET=a1to.....9wlnNq\nREFRESH_TOKEN_SECRET=KVDq9.....icVNh\n\nPORT=3000\n\nCLIENT_VALIDATION=Dev \n```\n\nThere is a `docker-compose.yaml` file in this folder that we will use to spin up a local service using this environment:\n```bash\ndocker compose up\n```\n\nTry to access the API by calling the endpoint now. If you are in GitHub Codespaces, you will be offered a unique URL that is generated for you, like 'https://\u003Crandom-generated-identifier\u003E-3000.app.github.dev/' that you can access, if you are on your local environment, it will be a localhost URL, like 'http://localhost:3000/'\n![Forwarded ports](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/forwarded_port_host.png)\n```bash\ncurl https://\u003Crandom-generated-identifier\u003E-3000.app.github.dev/franchise/1\n```\nor, open up a new terminal and access it (this will also work inside Codespaces)\n```bash\ncurl http://localhost:3000/franchise/1\n```\n\nThis should return the following JSON response:\n```json\n{\n   \"TRUCK_BRAND_NAMES\":[\n      \"The Mac Shack\",\n      \"Smoky BBQ\",\n      \"Freezing Point\",\n      \"Guac n' Roll\",\n      \"The Mega Melt\",\n      \"Plant Palace\",\n      \"Tasty Tibs\",\n      \"Nani's Kitchen\",\n      \"Better Off Bread\",\n      \"Peking Truck\",\n      \"Kitakata Ramen Bar\",\n      \"Cheeky Greek\",\n      \"Le Coin des Crêpes\",\n      \"Revenge of the Curds\",\n      \"Not the Wurst Hot Dogs\"\n   ],\n   \"START_DATE\":\"2022-01-01 08:00:01.000\",\n   \"END_DATE\":\"2022-10-31 22:59:29.000\"\n}\n```\n\n### Step 4.2 Authenticating and authorizing service users\n\nCurrently there is no authentication of the user calling this endpoint. We will change that to take advantage of the mechanism built into Snowflake Container Services.\n\nIn the earlier guide [Build a Data App with Snowflake](/en/developers/guides/build-a-data-app-with-snowflake/) authentication was implemented using JWT tokens, where the client frontend called a login endpoint and provided user name and password, and the service looked that up in the database (the `USERS` table that is also created for this lab.) and then supplied the client with an accesstoken that could be passed along with future calls to the API. With SPCS this will not work because the environment strips any request headers from calls to the public endpoints as they are routed to the service, meaning we cannot evaluate a Bearer Authentication token in calls from the client to the backend. Remember, with a React application, the frontend is running directly as javascript in the client's browser, even if the code is served from the frontend service, so calls to the API are coming from the end users' browsers, not from the internal service hosting the frontend.\n\n\u003E \n\u003E\n\u003E While React.js mainly relies on Client-Side Rendering, other frontend frameworks may rely on Server-Side Rendering, which changes this a little bit. CSR is very lightweight and makes it easy for the frontend service to serve static content to the end users, so for this solution it works well.\n\nWhat Snowpark Container Services offers is a different authentication model. Any user accessing the public endpoints for the services, needs to log in with a `USER` to the Snowflake interface. \n\n![User authentication](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/authenticating_with_snowservices_ingress.png)\n\nIn this example, one of the users we created in the earlier steps (`user1`, `user2`, `user3`,...) can now log in here. Once the user is authenticated, Snowpark Container Services adds that user name as a special header `Sf-Context-Current-User` to any request to the public endpoints. Since the environment strips away any other headers, there is no risk that the client can tamper with the value of this either, so from the perspective of the backend service, we can trust that the value in that header represents the user that authenticated with Snowflake.\n\nThe request headers reaching the service endpoint will look something like this for a normal call:\n\n```bash\nhost: 'backend-service:3000'\nreferer: 'https://randomlygeneratedendpointname.snowflakecomputing.app/login'\ncontent-type: 'application/json'\nuser-agent: 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36'\naccept: '*/*'\n'sf-context-current-user': 'USER1'\n...\n...\n```\n\nWith this we can then look up that user and ensure that they have access to the application.\n\nGo to the code for `auth.js`, it contains code to validate this header and look up the user in the database, in order to check its association with a franchise. The following code does that:\n\n```js\nfunction lookupUser(user_name) {\n    return new Promise(async function (result, error) {\n        snowflake.getConnection().then(conn =\u003E\n            conn.execute({\n                sqlText: sql_queries.verify_user,\n                binds: [user_name],\n                complete: (err, stmt, rows) =\u003E {\n                    if (err) {\n                        error({result: false, message: 'Unable to lookup user', error:err});\n                    } else {\n                        if (rows.length == 0) {\n                            result({message: 'User does not exist'});\n                        } else {\n                            user_row = rows[0]\n                            user_name = user_row.USER_NAME;\n                            franchise_id = user_row.FRANCHISE_ID;\n                            hashed_password = user_row.HASHED_PASSWORD;\n                            data = {result: true, validation: 'Snowflake', user_name: user_name, franchise_id: franchise_id, hashed_password: hashed_password };\n                            result(data);\n                        }\n                    }\n                },\n            }));\n    });\n}\n\n...\n\nfunction validateSnowflakeHeader(req, res, next) {\n\n    if (!req.headers['sf-context-current-user']) {\n        console.warn('Validation mode is Snowflake but sf-context-current-user header is missing - user is not validated');\n        res.status(422).send(\"Incorrect data\");\n        return\n    }\n\n    const login_user = req.headers['sf-context-current-user']\n    console.log('sf-context-current-user: ' + login_user);\n    lookupUser(login_user).then(result =\u003E {\n        if (result.result === true){\n            console.log('Authorizing user ' + result.user_name + ' for franchise: ' + result.franchise_id);\n            req.user = { validation: 'Snowflake', user: result.user_name, franchise: result.franchise_id };\n            next();\n        } else {\n            console.warn('User does not exist: ' + login_user);\n            res.status(401).json('Invalid user or password');\n            return\n        }\n    }, error =\u003E {\n        console.error(error.message, error.error);\n        res.status(500).json({ error: error.message });\n        return\n    });\n};\n```\n\nComparing this to the code that validates a JWT access token it is similar, but we here also have to look up the user in a database call, because unlike the JWT we cannot securely pass any additional information (like the `franchise_id` in the token), the only value we can trust here is the user header, since it is securely set by the SPCS environment and cannot be tampered with by a javascript client. The rest of the code in that file is supporting the authentication using other methods, but this is the only one that will be used in this guide and when we deploy the services to Snowflake.\n\nAlso review the file `/routes/login.js` that introduces a new endpoint `/authorize` that responds with an accesstoken containing the `user id` and `franchise id` when called with a header of `Sf-Context-Current-User`. This can be used by the frontend later on to check what franchise to set in the UI. Note that this endpoint also returns a JWT token, but we are only using that format to keep the code in the frontend as similar to the original code as possible, we are not using the JWT access token for future authorization of calls from the frontend to the backend.\n\nThis endpoint is similar to the code in `auth.js` for validating a user.\n```js\nrouter.get(\"/authorize\", async (req, res) =\u003E {\n\n    console.log('Authorize with request headers:')\n    if (!req.headers['sf-context-current-user']) {\n        res.status(422).send(\"Incorrect data\");\n        return\n    }\n\n    const login_user = req.headers['sf-context-current-user']\n    console.log(`Authorizing user ${login_user} from context header`);\n    auth.lookupUser(login_user).then(result =\u003E {\n        if (result.result === true) {            \n            console.log('Authorizing user ' + result.user_name + ' for franchise: ' + result.franchise_id);\n            const accessToken = auth.generateAccessToken({ user: result.user_name, franchise: result.franchise_id, preauthorized: true });\n            const refreshToken = auth.generateRefreshToken({ user: result.user_name, franchise: result.franchise_id, preauthorized: true });\n            res.status(200).json({ accessToken: accessToken, refreshToken: refreshToken });\n            return\n        } else {\n            console.warn('User does not exist: ' + login_user);\n            res.status(401).json('Invalid user or password');\n            return\n        }\n    }, error =\u003E {\n        console.error(error.message, error.error);\n        res.status(500).json({ error: error.message });\n        return\n    });\n});\n```\n\nWith this we test run the application locally and simulate the SPCS environment. Change the `.env` file to use Snowflake authentication instead:\n\n```bash\nCLIENT_VALIDATION=Snowflake\n```\n\nRestart the service running by pressing `CTRL+c` in the terminal where you started the docker service. Restart it again with `docker compose up` again. Once running you should now see the output:\n\n```bash\nbackend-backend_service-1  | Starting up Node Express, build version 00013\nbackend-backend_service-1  | Server running on port 3000\nbackend-backend_service-1  | Environment: development\nbackend-backend_service-1  | CORS origin allowed: http://localhost:4000\nbackend-backend_service-1  | Client validation: Snowflake\nbackend-backend_service-1  | Using warehouse: TASTY_APP_WAREHOUSE\nbackend-backend_service-1  | Using role: TASTY_APP_ADMIN_ROLE\n```\n\nCalling one of the endpoints now results in a `HTTP 422` response and the test `Incorrect data` (which is what we expect from the `validateSnowflakeHeader` in `auth.js`). If we provide a header that looks like the SPCS authentication header it now uses that to validate the user:\n\n```bash\ncurl --header \"Sf-Context-Current-User:user1\"  http://localhost:3000/franchise/1\n```\n\nThis now responds with a the expected `HTTP 200` response:\n```json\n{\n   \"TRUCK_BRAND_NAMES\":[\"The Mac Shack\",\"Smoky BBQ\",\"Freezing Point\",\"Guac n' Roll\",\"The Mega Melt\",\"Plant Palace\",\"Tasty Tibs\",\"Nani's Kitchen\",\"Better Off Bread\",\"Peking Truck\",\"Kitakata Ramen Bar\",\"Cheeky Greek\",\"Le Coin des Crêpes\",\"Revenge of the Curds\",\"Not the Wurst Hot Dogs\"\n   ],\n   \"START_DATE\":\"2022-01-01 08:00:01.000\",\n   \"END_DATE\":\"2022-10-31 22:59:29.000\"\n}\n```\n\nYou can now terminate the service with `CTRL+c` and we can then destroy the local Docker service and images we just used for testing:\n\n```bash\ndocker rm backend-backend_service-1\ndocker image rm backend-backend_service\n```\n\n### Step 4.3 Connecting to Snowflake data\n\nWith this update, we can now look at how the backend service can access the data in the Snowflake tables and views. In the self hosted version of the code (as in the [Build a Data App with Snowflake](/en/developers/guides/build-a-data-app-with-snowflake/)) we use a key pair authentication schema to connect the service to Snowflake. For a service running on Snowpark Container Services, we can benefit from the service already running on Snowflake and we can use a provided and pre-loaded authentication model based on OAuth. This is available for every service running on SPCS.\n\nOpen the file `connect.js` and look at how the code is sending the options for the connection to Snowflake:\n\n```js\n    const options = {\n        database: process.env.SNOWFLAKE_DATABASE,\n        schema: process.env.SNOWFLAKE_SCHEMA,\n        warehouse: process.env.SNOWFLAKE_WAREHOUSE,\n    };\n\n    if (fs.existsSync('/snowflake/session/token')) {\n        options.token = fs.readFileSync('/snowflake/session/token', 'ascii');\n        options.authenticator = \"OAUTH\";\n        options.account = process.env.SNOWFLAKE_ACCOUNT;\n        options.accessUrl = 'https://' + process.env.SNOWFLAKE_HOST;\n    } else {\n        options.account = process.env.SNOWFLAKE_ACCOUNT;\n        options.username = process.env.SNOWFLAKE_USERNAME;\n        options.role = process.env.SNOWFLAKE_ROLE;\n        options.password = process.env.SNOWFLAKE_PASSWORD;\n    };\n```\n\nWhen the service is running on SPCS, the file located at `/snowflake/session/token` will contain an OAuth token that is pre-validated for accessing Snowflake. This means we don't need to supply a user and password for the connection. This token is authenticated for a temporary user that is given the same role as the `OWNER` for the Service being called. This is an important detail, as the service will be connecting as the very role that created it (here it will be `tasty_app_admin_role`), so think of it as a service account type of user that is connecting. This is analogous to how the original solution worked, but in there we created a dedicated user that the service connected as.\n\nOnce connected, the rest of the backend code is working the same, regardless if it is running in the SPCS environment or somewhere else, like a local testing environment.\n\n\n\n\n\n\n\n\n\u003C!-- ------------------------ --\u003E\n\n## Building the frontend code\n\n### Overview\nWe can now look at how the frontend has been updated to take advantage of the changes and for us to be able to run it on SPCS.\n\nThere are two areas that is updated here to allow it to run in the new environment:\n\n- Authentication - by placing the service behind a public endpoint that forces users to login, it no longer makes sense to keep the login form in the client, the required authentication is already captured by the Snowflake OAuth login form\n- Routing from client to the backend API, we can no longer directly control the CORS directives for the services, and calls from the client are actually made directly from the users' browsers.\n\nThe routing is something that changes somewhat significantly from the original solution. Instead of adding a CORS directive to the backend (e.g. allowing calls from another origin), we introduce a router service that takes calls from the public endpoint and _routes_ them to either the frontend service, or the backend service, allowing us to maintain a single public endpoint.\n\n\u003E \n\u003E\n\u003E The frontend service and backend service are here hosted as two separate services, with a router bundled together with the frontend. For this simple application that may not be a necessary requirement to fulfill, but in a more complex and demanding application, it would be a good approach to separate the frontend and backend as they would have different non-functional requirements.\n\nThe router ensures that calls made to routes starting with `/api` are forwarded to the `backend-service`, whereas any other calls `/*` are routed to the frontend container running in the same service as the router:\n![Routing](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/frontend-routing.png)\n\n### Step 5.1 Building the router\n\nThe router is a simple service based on [*NGINX*](https://www.nginx.com/). The code is very simple and serves a NGINX server that is given a configuration that defines the different routes, open `/src/frontend/router/nginx.conf.template`:\n\n```yaml\nevents {\n  worker_connections  1024;\n}\nhttp {\n  server {\n    listen 8000;\n    listen [::]:8000;\n    server_name localhost;\n\n    location / {\n      proxy_pass  http://$FRONTEND_SERVICE/;\n    }\n\n    location /api {\n        rewrite     /api/(.*) /$1  break;\n        proxy_pass  http://$BACKEND_SERVICE/;\n    }\n\n    location /test {\n        add_header Content-Type text/html;\n\n        return 200 '\u003Chtml\u003E\u003Cbody\u003E\u003Ch1\u003EThis is the router testpage\u003C/h1\u003E\u003Cli\u003ESf-Context-Current-User: $http_sf_context_current_user\u003C/li\u003E\u003Cli\u003EHost: $http_host\u003C/li\u003E\u003Cli\u003EFrontend Server: $FRONTEND_SERVICE\u003C/li\u003E\u003Cli\u003EBackend Server: $BACKEND_SERVICE\u003C/li\u003E\u003C/body\u003E\u003C/html\u003E';\n    }\n  } \n}\n```\n\nThere are three routes in here, `/`, `/api` `/test`. The last one simply outputs debug information and can help to understand that the setup is correct (it should be removed when not testing out the services).\n\nThe `/api` route means that anything prefixed with that gets rewritten to remove the \"`/api`\" part and then passed forward to the backend service URL. For all other calls they should be forwarded directly to the frontend service URL (which should be running on the same service as the router, in a different container).\n\nThe `$FRONTEND_SERVICE` and `$BACKEND_SERVICE` variables allow us to dynamically replace these values when the Docker image is being used. If we look at the Dockerfile:\n\n```bash\nFROM nginx:alpine\n\nARG required FRONTEND_SERVICE\nARG required BACKEND_SERVICE\n\nRUN apk update && apk add bash\n\nEXPOSE 8000\n\nCOPY nginx.conf.template /nginx.conf.template\n\nCMD [\"/bin/sh\" , \"-c\" , \"envsubst '$FRONTEND_SERVICE $BACKEND_SERVICE' \u003C /nginx.conf.template \u003E /etc/nginx/nginx.conf && exec nginx -g 'daemon off;'\"]\n```\n\nThe last line substitutes these variables for values taken from the `environment` it is running in, before copying the contents into the `nginx.conf` file and starting up the server.\n\nYou can test the router by running the container locally. From `/src/frontend` run the following:\nbash\n```\ndocker compose --env-file .env.local.example up\n```\nThis should run the router and the frontend on local ports. Test it out by running:\nbash\n```\ncurl http://localhost:8888/test\n```\nIt should return HTLM, like:\nhtml\n```\n\u003Chtml\u003E\u003Cbody\u003E\u003Ch1\u003EThis is the router testpage\u003C/h1\u003E\u003Cli\u003ESf-Context-Current-User: \u003C/li\u003E\u003Cli\u003EHost: localhost:8888\u003C/li\u003E\u003Cli\u003EFrontend Server: localhost:4000\u003C/li\u003E\u003Cli\u003EBackend Server: localhost:3000\u003C/li\u003E\u003C/body\u003E\u003C/html\u003E\n```\nTerminate the running containers byt pressing `ctrl+c` in the terminal again.\n\n### Step 5.2 Updating the frontend code\n\nThe frontend code itself needs fewer changes to adapt to the new environment. Primarily here we are looking at removing the actual login form and user management in favor of using the built in login capability.\n\n![Tasty App UI](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/tasty-app-ui.png)\n\n\u003E \n\u003E\n\u003E The original React code is actually built on older package dependencies. In order to keep this guide as similar to the original guide no changes to the React framework have been introduced, only minor changes are done as part of this guide. There are many ways to update the general React code to later standards, but this guide will focus on the core parts of connecting the services,\n\nIn a commonly shared file `Utils.js` we can provide some methods that will help check how to communicate with the backend and to verify if the login button should be visible. \n\n```js\nexport function enableLogin() {\n    if (clientValidation === 'JWT') {\n        return true;\n    } else if (clientValidation === 'Snowflake') {\n        return false;\n    }\n    console.log(` - Login disabled`);\n    return false;\n}\n\nexport function isLoggedIn(state) {\n    if (clientValidation === 'JWT') {\n        if (state){\n            return (state.accessToken != null);\n        }\n    } else if (clientValidation === 'Snowflake') {\n        if (state){\n            return (state.accessToken != null);\n        }\n    } else if (clientValidation === 'Dev') {\n        if (state){\n            return (state.franchise != null);\n        }\n    }\n    return false;\n}\n```\n\nWe can then use these functions to decide if the Login button should be visible or not:\n\nE.g. in `Home.js`, the logout button is conditionally shown using the above function:\n```html\n            \u003Cdiv className='home-header'\u003E\n                \u003CImage src='bug-sno-R-blue.png' className='homeLogo' /\u003E\n                \u003Ch1 className=\"homeTitle\"\u003E Tasty App\u003C/h1\u003E\n\n                \u003CButton className='backBtn' onClick={gotoDetails}\u003E  🚚 Truck Details\u003C/Button\u003E\n                { enableLogin() &&\n                    \u003CButton className='home-logoutBtn' onClick={logout}\u003E⎋ Logout\u003C/Button\u003E\n                }\n            \u003C/div\u003E\n```\n\nAnd in the `App.js` routing we can use the same functions to conditionally route the user depending on if they are logged in or not.\n\n```js\nfunction App() {\n\n  const LoginWrapper = () =\u003E {\n    const location = useLocation();\n    return isLoggedIn(location.state) ? \u003COutlet /\u003E : \u003CNavigate to=\"/login\" replace /\u003E;\n  };\n\n  return (\n    // Routing for the App.\n    \u003CBrowserRouter\u003E\n      \u003CRoutes\u003E\n        \u003CRoute path=\"/login\" element={ \u003CLogin /\u003E  } /\u003E\n        \u003CRoute element={\u003CLoginWrapper /\u003E}\u003E\n          \u003CRoute path=\"/\" element={ \u003CHome /\u003E } /\u003E\n          \u003CRoute path=\"/home\" element={ \u003CHome /\u003E } /\u003E\n          \u003CRoute path=\"/details\" element={ \u003CDetails /\u003E } /\u003E\n        \u003C/Route\u003E\n      \u003C/Routes\u003E\n    \u003C/BrowserRouter\u003E\n  );\n}\n```\n\nFinally we add a call in `Login.js` to check the `/authenticate` endpoint of the backend.\n\n```js\nconst clientValidation = process.env.REACT_APP_CLIENT_VALIDATION;\n\n...\n\n    function checkAuthentication() {\n        if (clientValidation === 'JWT') {\n            //console.log(` - Validation enabled`);\n        } else if (clientValidation === 'Snowflake') {\n            console.log(`Checking client validation ${clientValidation} - Checking authorize endpoint of API`);\n            const requestOptions = {\n                method: 'GET',\n                headers: { 'Content-Type': 'application/json', 'Sf-Context-Current-User': 'user1' }\n            };\n            fetch(backendURL + '/authorize', requestOptions)\n                .then((result) =\u003E {\n                    if (result.ok) {\n                        result.json()\n                            .then((data) =\u003E {\n                                const token = decodeToken(data.accessToken);\n                                data.franchise = token.franchise;\n                                navigate(\"/\", { state: data });\n                            });\n                    } else {\n                        console.warn('Current user is not authorized to use the application');\n                    }\n\n                });\n        } else {\n            console.warn(`Checking client validation ${clientValidation} - Validation disabled - hard coding franchise \"1\"`);\n            const data = { franchise: 1 };\n            navigate(\"/\", { state: data });\n        }\n        return false;\n\n    };\n```\n\nWhen the `/login` page shows, this call is run and if the result is that a user context is returned then it navigates to the default route `/`. This all ensures that the same code runs both in the SPCS environment and in another hosting environment. By setting the `ENVIRONMENT` variable `REACT_APP_CLIENT_VALIDATION` to `Snowflake` when deploying this we ensure the method is called and evaluated.\n\nRemember, the `/authorize` endpoint of the backend service should return a JWT access token containing the user name and franchise when called from an authenticated context in SPCS, like the following result:\n```json\n{\n    \"accessToken\": \"eyJhbGc....goa_RUCl85NeM\",\n    \"refreshToken\": \"eyJhbGc.....VR5fnViRksNI\"\n}\n```\n\nAnd when decoded, that token should look something like this:\n```json\n{\n  \"user\": \"user1\",\n  \"franchise\": 1,\n  \"preauthorized\": true,\n  \"iat\": 1705924945,\n  \"exp\": 1705946545\n}\n```\n\nYou can try this if you like, by starting up the backend again in a new Terminal window:\n```bash\ncd src/backend\ndocker compose up\n```\nAnd then directly call the `authorize` endpoint:\n```bash\ncurl --header \"Sf-Context-Current-User:user1\" http://localhost:3000/authorize\n```\nCopy the content of the `accessToken` attribute in the JSON response, and then go to [https://jwt.io/](https://jwt.io/) and paste the response there. This should decode the token for you and show an output like above.\n\nAdditionally, if you want to verify this token, you can supply the random string we added to the `.env` file for the backend.\n\nThroughout the `Home.js` and `Details.js` we then update all call to the backend to use the common helper function from `Utils.js` to call the backend, like this:\n```js\nconst url = `${backendURL}/franchise/${franchise}/trucks?start=${fromDate}&end=${toDate}`;\nfetch(url, getRequestOptions(location.state))\n    .then((result) =\u003E result.json())\n        .then((data) =\u003E {\n            setTop10Trucks(data)\n            let t = [];\n\n            for (let i=0; i\u003Cdata.length; i++) {\n                t.push(data[i].TRUCK_BRAND_NAME);\n            }\n            setTrucks(t);\n    })\n```\n\nWith those changes, the code should be ready to be Dockerized and then deployed in Snowpark Container Services.\n\n\n\n\n\n\n\n\n\u003C!-- ------------------------ --\u003E\n\n## Containerize the Application\n\nNow we can prepare the services for deployment, and we will do that by building Docker container images for each service to deploy.\n\nEnsure that you have Docker installed on you environment:\n\n```bash\ndocker --version\n-- Docker version 24.0.6, build ed223bc\n```\n\n### Step 6.1 Defining Dockerfiles for services\n\nEach service that we will spin up consists of one or more containers, and each container is built on a Docker image. \n\nLet's start with the Dockerfile for the backend service. In the `/backend/Dockerfile` we are exposing the port this service is exposed on. By putting it in as a variable `${PORT}` we can set it through the service definition.\n```bash\nFROM node:18\n\nARG PORT\n\nWORKDIR /src/app\nCOPY package.json /src/app/package.json\n\nRUN npm install\n\nENV PORT=${PORT}\nEXPOSE ${PORT}\n\nCOPY . /src/app\n\nCMD [\"npm\", \"run\", \"serve\"]\n```\n\nEnsure that there is a `.env` file there that will be picked up by the Docker build. It should look like this:\n```bash\nSNOWFLAKE_WAREHOUSE=TASTY_APP_WAREHOUSE\nSNOWFLAKE_DATABASE=FROSTBUTE_TASTY_BYTES\nSNOWFLAKE_SCHEMA=APP\n\nACCESS_TOKEN_SECRET={INSERT A RANDOM STRING HERE}\nREFRESH_TOKEN_SECRET={INSERT A RANDOM STRING HERE}\n\nPORT=3000\n\nCLIENT_VALIDATION=Snowflake \n```\n\nThe frontend service will contain two containers, so we will have two Dockerfiles, one for each image we are building.\n\nThe frontend itself is here `/frontend/frontend/Dockerfile`:\n```bash\nFROM node:latest\n\nARG FRONTEND_SERVICE_PORT\nARG REACT_APP_BACKEND_SERVICE_URL\n\nWORKDIR /src/\nCOPY package.json /src/package.json\n\nRUN npm install\n\nENV REACT_APP_BACKEND_SERVICE_URL=${REACT_APP_BACKEND_SERVICE_URL}\n\nENV PORT=${FRONTEND_SERVICE_PORT}\nEXPOSE ${FRONTEND_SERVICE_PORT}\n\nCOPY ./src /src/src\nCOPY ./public /src/public\n\nCMD [\"npm\", \"start\"]\n```\nHere we also allow the service to expose a port that is set through an environment variable `${FRONTEND_SERVICE_PORT}`. Additionally we inject the actual URL to the backend, i.e. what is the URL that the frontend is calling when connecting to the backend service, is also a variable `${REACT_APP_BACKEND_SERVICE_URL}`.\n\nThe router that accompanies the frontend is built from a simple Dockerfile, `/frontend/router/Dockerfile`:\n```bash\nFROM nginx:alpine\n\nARG required FRONTEND_SERVICE\nARG required BACKEND_SERVICE\n\nRUN apk update && apk add bash\n\nEXPOSE 8000\n\nCOPY nginx.conf.template /nginx.conf.template\n\nCMD [\"/bin/sh\" , \"-c\" , \"envsubst '$FRONTEND_SERVICE $BACKEND_SERVICE' \u003C /nginx.conf.template \u003E /etc/nginx/nginx.conf && exec nginx -g 'daemon off;'\"]\n```\nThe last line is where the `$FRONTEND_SERVICE` and `$BACKEND_SERVICE` variables are replaced into the configuration for the NGINX server.\n\n### Step 6.2 Login to the repo\n\nWe need to connect our local Docker to the remote [Image repository](https://docs.snowflake.com/developer-guide/snowpark-container-services/working-with-registry-repository) that we created in Step 4. Start by grabbing the url for the repository by running the following SQL:\n\n```sql\nUSE DATABASE FROSTBYTE_TASTY_BYTES;\nUSE SCHEMA APP;\nUSE ROLE tasty_app_admin_role;\n\nSHOW IMAGE REPOSITORIES;\n```\nNow copy the value from the `repository_url` for the row for `TASTY_APP_REPOSITORY` (there should only be one row). The URL should look something like this:\n```bash\n\u003CACCOUNT_NAME\u003E.registry.snowflakecomputing.com/frostbyte_tasty_bytes/app/tasty_app_repository\n```\n\nOpen up a terminal now and enter:\n```bash\nexport repo_url=\u003Cinsert repo url here\u003E\n```\n\nThe user then you will use to login to this Docker image repository should be a user that is granted the role `tasty_app_admin_role`:\n```bash\n# Snowflake user name\nexport admin_user= \u003Cyour user name\u003E\n# login to the repo.  You'll need this for the push later.\ndocker login ${repo_url} --username ${admin_user}\n```\nType in the password for that user when prompted.\n```bash\nPassword: \nLogin Succeeded\n```\n\nWith this, you can now push Docker images to this repository.\n\n### Step 6.3 Build and push up the image\n\nWhen building and pushing an image to the repo, we do a number of steps to ensure we build the image locally, tag it and then push it to the remote repository. Here is how the backend service is build in the `./build-all.sh` file:\n\n```bash\nexport image_name=backend_service_image\ndocker image rm ${image_name}:${tag}\ndocker build --rm --platform linux/amd64 -t ${image_name}:${tag} ./backend\ndocker image rm ${repo_url}/${image_name}:${tag}\ndocker tag ${image_name}:${tag} ${repo_url}/${image_name}:${tag}\ndocker push ${repo_url}/${image_name}:${tag}\necho ${repo_url}/${image_name}:${tag}\n```\n\nNote here that we are specifying to build the image directly for the `linux/amd64` architecture, this is needed for running it on the nodes in the compute pool for Snowpark Container Services. This may not be an image that can then be run on your local system, depending on the CPU architecture on that. It is important that we build it using this flag, otherwise it will not run on SPCS.\n\nWe can now build and push all images to the Snowflake repository, from `/src` run:\n```bash\n./build-all.sh \n```\n\nOnce that finishes, you can verify in a Snowflake worksheet that the images have been pushed to the repository:\n```sql\nSHOW IMAGES IN IMAGE REPOSITORY TASTY_APP_REPOSITORY;\n```\n\nThe output should be similar to this:\n```json\n{\n   \"images\":[\n      \"backend_service_image\",\n      \"frontend_service_image\",\n      \"router_service_image\"\n   ]\n}\n```\n\n\n\n\n\n\n\n\n\u003C!-- ------------------------ --\u003E\n\n## Create the Services\n\n### Step 7.1 Creating the Service in Snowflake\n\nThe services can now be created in Snowflake. Go back to Snowflake and open a worksheet. Enter the following to create the backend service. The `CREATE SERVICE` command creates a new service.\n\n```sql\nUSE DATABASE FROSTBYTE_TASTY_BYTES;\nUSE SCHEMA APP;\nUSE ROLE tasty_app_admin_role;\n\nCREATE SERVICE backend_service\n  IN COMPUTE POOL tasty_app_backend_compute_pool\n  FROM SPECIFICATION $$\nspec:\n  container:\n  - name: backend\n    image: /frostbyte_tasty_bytes/app/tasty_app_repository/backend_service_image:tutorial\n    env:\n      PORT: 3000\n      ACCESS_TOKEN_SECRET: {INSERT A RANDOM STRING HERE}\n      REFRESH_TOKEN_SECRET: {INSERT ANOTHER RANDOM STRING HERE}\n      CLIENT_VALIDATION: Snowflake\n  endpoint:\n  - name: apiendpoint\n    port: 3000\n    public: true\n$$\n  MIN_INSTANCES=1\n  MAX_INSTANCES=1\n;\nGRANT SERVICE ROLE backend_service!ALL_ENDPOINTS_USAGE TO ROLE tasty_app_ext_role;\n```\nThis creates the backend service using the image `backend_service_image:tutorial` that we should now have pushed to the repository. Note how we can supply overriding environment variables to the services.\n\nWe also set this service to use the `tasty_app_backend_compute_pool` as the [COMPUTE POOL](https://docs.snowflake.com/en/developer-guide/snowpark-container-services/working-with-compute-pool) to run the service on. At the end we can set the scaling behavior of this service in the pool. In order to test this service we don't need any additional scaling setup here, but in a real scenario we may want to increase the number of instances available in case the load on the service goes up.\n\nLastly we call `GRANT USAGE ON SERVICE` to allow the `tasty_app_ext_role` role and users with that role granted access to the service.\n\nWe can then call `SHOW SERVICES` to look at the services created. In order to check the status of the newly created service we can call:\n```sql\nSHOW SERVICE CONTAINERS IN SERVICE backend_service;\n```\nWhich will return the status of the service. After a few moments the service should report status `READY` and that it is running:\n\n```json\n[\n   {\n      \"status\":\"READY\",\n      \"message\":\"Running\",\n      \"containerName\":\"backend\",\n      \"instanceId\":\"0\",\n      \"serviceName\":\"BACKEND_SERVICE\",\n      \"image\":\"\u003CACCOUNT_NAME\u003E.registry.snowflakecomputing.com/frostbyte_tasty_bytes/app/tasty_app_repository/backend_service_image:tutorial\",\n      \"restartCount\":0,\n      \"startTime\":\"\u003CCREATE TIME\u003E\"\n   }\n]\n```\n\nWe can also look directly at the [logs from the service itself](https://docs.snowflake.com/en/developer-guide/snowpark-container-services/working-with-services#accessing-local-container-logs), anything that is written to the standard logging can be retrieved from the service logs:\n```sql\nCALL SYSTEM$GET_SERVICE_LOGS('backend_service', '0', 'backend', 50);\n```\n\nShould show a log looking like this:\n```bash\n\u003E serve\n\u003E node app.js\n\nStarting up Node Express, build version 00014\nServer running on port 3000\nEnvironment: development\nClient validation: Snowflake\nUsing warehouse: tasty_app_warehouse\nUsing role: TASTY_APP_ADMIN_ROLE\n```\n\nThe frontend service can now be created in a similar fashion. The difference here is that it will contain two different containers, we are using both the image for the router and the frontend React app inside the same service.\n\n```sql\nCREATE SERVICE frontend_service\n  IN COMPUTE POOL tasty_app_frontend_compute_pool\n  FROM SPECIFICATION $$\nspec:\n  container:\n  - name: frontend\n    image: /frostbyte_tasty_bytes/app/tasty_app_repository/frontend_service_image:tutorial\n    env:    \n      PORT: 4000\n      FRONTEND_SERVICE_PORT: 4000\n      REACT_APP_BACKEND_SERVICE_URL: /api\n      REACT_APP_CLIENT_VALIDATION: Snowflake\n  - name: router\n    image: /frostbyte_tasty_bytes/app/tasty_app_repository/router_service_image:tutorial\n    env:\n      FRONTEND_SERVICE: localhost:4000\n      BACKEND_SERVICE: backend-service:3000\n  endpoint:\n  - name: routerendpoint\n    port: 8000\n    public: true\n$$\n  MIN_INSTANCES=1\n  MAX_INSTANCES=1\n;\nGRANT SERVICE ROLE frontend_service!ALL_ENDPOINTS_USAGE TO ROLE tasty_app_ext_role;\n```\n\nIn the same way we can check the status of the service and read the logs. Note that there are two logs to read, one for each container in the service.\n```sql\nSHOW SERVICE CONTAINERS IN SERVICE frontend_service;\nCALL SYSTEM$GET_SERVICE_LOGS('frontend_service', '0', 'frontend', 50);\nCALL SYSTEM$GET_SERVICE_LOGS('frontend_service', '0', 'router', 50);\n```\n\nThe log for the `frontend` container in the `frontend_service` should look something like this:\n```bash\n\u003E tasty_app@0.1.0 start\n\u003E react-scripts start\n  \nCompiled successfully!\n\nYou can now view tasty_app in the browser.\n\n  Local:            http://localhost:4000\n  On Your Network:  http://10.244.2.15:4000\n```\n\n### Step 7.2 Testing the service\n\nWe are now finally ready to test the application in a browser. In order to do that we need the public endpoint exposed by the frontend_service. Call `SHOW ENDPOINTS` to retrieve that:\n\n```sql\nSHOW ENDPOINTS IN SERVICE frontend_service;\n```\n\nThe `ingress_url` in the response is the public endpoint URL, it should look similar to this, the first part is randomly generated for each endpoint and service:\n\n```bash\n\u003CRANDOM\u003E-\u003CACCOUNT NAME\u003E.snowflakecomputing.app\n```\n\nNow open up that URL in a browser. You will be prompted for a login, and here we can choose any of the users created earlier. You can use `user1` with password `password1`. Note that you will be forced to change this on first login.\n![Tasty App UI](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/authenticating_with_snowservices_ingress.png)\n\nOnce logged in, the application loads the authorization status, and then redirects the user to the logged in `Home` page. After a few moments the data is loaded also and the charts for the current franchise (Franchise 1, if you logged in with user1) is shown. \n\n![Tasty App UI](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/build-a-data-app-and-run-it-on-snowpark-container-services/tasty-app-ui.png)\n\n\u003C!-- ------------------------ --\u003E\n\n## Clean up resources\n\nOnce we have tested the application we can tear down any resources that we have created. The following resouces should be removed:\n\n- Services\n- Compute Pools\n- Warehouses\n- Image Repositories\n- Database and Schema\n- Security Integration (NOTE: this may be used by other services, you can only have one active per ACCOUNT)\n- Roles\n- Users\n- Local Docker images\n\nOpen a worksheet in Snowflake and run the following SQL:\n\n```sql\nUSE DATABASE FROSTBYTE_TASTY_BYTES;\nUSE SCHEMA APP;\nUSE ROLE tasty_app_admin_role;\n\n-- Delete services\nSHOW SERVICE;\nDROP SERVICE BACKEND_SERVICE;\nDROP SERVICE FRONTEND_SERVICE;\n\n-- Delete compute pools\nSHOW COMPUTE POOLS;\nUSE ROLE ACCOUNTADMIN;\nDROP COMPUTE POOL TASTY_APP_BACKEND_COMPUTE_POOL;\nDROP COMPUTE POOL TASTY_APP_FRONTEND_COMPUTE_POOL;\n\n-- Delete warehouses\nSHOW WAREHOUSES;\nDROP WAREHOUSE LOAD_WH;\nDROP WAREHOUSE QUERY_WH;\nDROP WAREHOUSE TASTY_APP_WAREHOUSE;\n\n-- Delete the Image repository\nUSE ROLE tasty_app_admin_role;\nSHOW IMAGE REPOSITORIES;\nDROP IMAGE REPOSITORY TASTY_APP_REPOSITORY;\n\n-- Delete the database\nUSE ROLE ACCOUNTADMIN;\nSHOW DATABASES;\nDROP DATABASE FROSTBYTE_TASTY_BYTES;\n\n-- Delete the roles\nUSE ROLE ACCOUNTADMIN;\nSHOW ROLES;\nDROP ROLE TASTY_APP_ADMIN_ROLE;\nDROP ROLE TASTY_APP_EXT_ROLE;\n\n-- Delete the users\nSHOW USERS;\nDROP USER USER1;\nDROP USER USER2;\nDROP USER USER3;\n```\n\nFrom a terminal, we can now also remove the built images:\n```bash\ndocker image prune --all\n```\n\n\u003E \n\u003E\n\u003E Warning, the above removes _all_ unused Docker images. If you have other Docker images that you don't want to remove, then manually remove the images created in this guide using `docker image rm \u003CIMAGE NAME\u003E`.\n\n\n\n\n\n\n\n\n\u003C!-- ------------------------ --\u003E\n\n## Conclusion and Resources\n\nGood work! You have now successfully built, deployed and run a data application on Snowpark Container Services.\n\n### What You Learned\n\nYou now have gone through the basic concepts of building a a Data Application that can run directly on Snowflake, we have looked through how to adapt existing code to cover:\n- Authentication and Authorization and user management\n- Public endpoints for service\n- Service to service communication\n- Services connecting to Snowflake accounts\n\nUsing this you should be able to build your own Data Application and run it directly on Snowpark Container Services, directly connected to your data.\n\nWe would love your feedback on this QuickStart Guide! Please submit your feedback using this Feedback Form.\n\n### Related Resources\n- [Source Code on GitHub](https://github.com/Snowflake-Labs/sfguide-tasty-bytes-zero-to-app-with-spcs)\n- [Snowpark Container Services documentation](https://docs.snowflake.com/en/developer-guide/snowpark-container-services/overview)\n- [Snowpark Container Services tutorials](https://docs.snowflake.com/en/developer-guide/snowpark-container-services/overview-tutorials)\n- [Quickstart: Build a Data App with Snowflake](/en/developers/guides/build-a-data-app-with-snowflake/)\n\n\u003C!-- ------------------------ --\u003E\n",":type":"text/x-markdown","multiValue":false},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image",":type":"text/plain","multiValue":false}},"model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-8412641ec7","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"none","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-5269305d6f",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-94f5de60bb","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2025-12-20",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-ff44ee2e7e","additionalClasses":"qs-disclaimer-text","text":"\u003Cp\u003E\u003Cspan style=\"color: #666;\"\u003EThis content is provided as is, and is not maintained on an ongoing basis. 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