Explore and run Linux and PostgreSQL workloads

45 minutes

In this unit, you will:

Deploy an Azure Blob Storage account by using a Bicep template.
Create a Blob Storage container.
Migrate images to the Blob Storage account.
Upload tailwind.sql to the Blob Storage account.
Connect to the Azure virtual machine by using the Azure CLI.
Download the file from the storage account.
Connect to the PostgreSQL server by using psql and import a SQL file.
Run the application interactively via the command line.
Confirm that the application runs correctly.

Deploy a storage account by using deploy/vm-postgres.bicep

Run the following command on your local machine:

az deployment group create \
    --resource-group 240900-linux-postgres \
    --template-file deploy/vm-postgres.bicep \
    --parameters \
        deployVm=false \
        deployPostgres=false \
        deployStorage=true

Add the current user to the Storage Blob Data Owner role

STORAGE_ACCOUNT_ID=$(az storage account list \
    --resource-group 240900-linux-postgres \
    --query '[0].id' \
    -o tsv)

USER_ID=$(az ad signed-in-user show \
    --query id \
    -o tsv)

az role assignment create \
    --role "Storage Blob Data Owner" \
    --assignee $USER_ID \
    --scope $STORAGE_ACCOUNT_ID

Create a container called container1 in the storage account

STORAGE_ACCOUNT_NAME=$(az storage account list \
    --resource-group 240900-linux-postgres \
    --query '[0].name' \
    -o tsv)

echo "STORAGE_ACCOUNT_NAME: $STORAGE_ACCOUNT_NAME"

az storage container create \
    --account-name $STORAGE_ACCOUNT_NAME \
    --auth-mode login \
    --name container1

Migrate images to the storage account into a subfolder

az storage blob upload-batch \
    --account-name $STORAGE_ACCOUNT_NAME \
    --auth-mode login \
    --overwrite \
    --destination container1/images \
    --source app/data/images

The following output appears:

[
  {
    "Blob": "https://storageji2dbe.blob.core.windows.net/container1/images/wrench_set.jpg",
    "Last Modified": "...",
    "Type": "image/jpeg",
    "eTag": "\"0x8DCE0CA938AF41B\""
  },
  {
    "Blob": "https://storageji2dbe.blob.core.windows.net/container1/images/planer.jpg",
    "Last Modified": "...",
    "Type": "image/jpeg",
    "eTag": "\"0x8DCE0CA939DF18B\""
  },
  ...
]

Upload app/data/postgres/tailwind.sql to the storage account

az storage blob upload \
    --account-name $STORAGE_ACCOUNT_NAME \
    --auth-mode login \
    --container-name container1 \
    --file app/data/postgres/tailwind.sql \
    --name tailwind.sql

Connect to the Azure virtual machine by using the az ssh command

az ssh vm \
    --resource-group 240900-linux-postgres \
    --name vm-1

Download the tailwind.sql file from the storage account

Set the Bash variable STORAGE_ACCOUNT_NAME to the storage account name:

STORAGE_ACCOUNT_NAME=$(az storage account list \
    --resource-group 240900-linux-postgres \
    --query '[0].name' \
    -o tsv)

echo "STORAGE_ACCOUNT_NAME: $STORAGE_ACCOUNT_NAME"

Download tailwind.sql to the Azure virtual machine by using the az storage blob download command:

az storage blob download \
    --account-name $STORAGE_ACCOUNT_NAME \
    --auth-mode login \
    --container-name container1 \
    --file tailwind.sql \
    --name tailwind.sql

Set the environment variables for psql on the remote machine

MANAGED_IDENTITY_NAME=240900-linux-postgres-identity
export AZURE_CLIENT_ID=$(az identity show --resource-group 240900-linux-postgres --name $MANAGED_IDENTITY_NAME --query "clientId" -o tsv)
PG_NAME=$(az postgres flexible-server list --resource-group 240900-linux-postgres --query "[0].name" -o tsv)

# Set psql environment variables
export PGHOST="${PG_NAME}.privatelink.postgres.database.azure.com"
export PGPASSWORD=$(curl -s "http://169.254.169.254/metadata/identity/oauth2/token?api-version=2018-02-01&resource=https%3A%2F%2Fossrdbms-aad.database.windows.net&client_id=${AZURE_CLIENT_ID}" -H Metadata:true | jq -r .access_token)
export PGUSER=$MANAGED_IDENTITY_NAME
export PGDATABASE=postgres

Import tailwind.sql by using psql

psql -f tailwind.sql

Connect to the Postgres server to confirm that the import was successful

psql

List the tables

\dt

The following output appears:

postgres=> \dt
                           List of relations
 Schema |         Name         | Type  |             Owner              
--------+----------------------+-------+--------------------------------
 public | cart_items           | table | 240900-linux-postgres-identity
 public | checkouts            | table | 240900-linux-postgres-identity
 public | collections          | table | 240900-linux-postgres-identity
 public | collections_products | table | 240900-linux-postgres-identity
 public | customers            | table | 240900-linux-postgres-identity
 public | delivery_methods     | table | 240900-linux-postgres-identity
 public | product_types        | table | 240900-linux-postgres-identity
 public | products             | table | 240900-linux-postgres-identity
 public | shipment_items       | table | 240900-linux-postgres-identity
 public | shipments            | table | 240900-linux-postgres-identity
 public | store_inventory      | table | 240900-linux-postgres-identity
 public | stores               | table | 240900-linux-postgres-identity
 public | suppliers            | table | 240900-linux-postgres-identity
 public | supply_orders        | table | 240900-linux-postgres-identity
(14 rows)

Run a SQL query that lists the tables

SELECT table_name
FROM information_schema.tables
WHERE table_schema = 'public';

The following output appears:

postgres=> SELECT table_name
FROM information_schema.tables
WHERE table_schema = 'public';
      table_name      
----------------------
 collections
 stores
 customers
 cart_items
 product_types
 products
 suppliers
 collections_products
 checkouts
 shipments
 delivery_methods
 shipment_items
 store_inventory
 supply_orders
(14 rows)

Turn on expanded mode and select from the products table

At the postgres=> prompt, turn on expanded mode:

\x

Select from the products table:

select * from products;

The following prompt appears:

postgres=> \x
Expanded display is on.
postgres=> select * from products;

A listing of products appears:

id                 | 1
product_type_id    | 1
supplier_id        | 2
sku                | brush_cleaner
name               | Meltdown Brush Cleaner
price              | 12.99
description        | We all leave our brushes sitting around, full of old dry paint. Don't worry! The Meltdown Brush Cleaner can remove just about anything.
image              | brush_cleaner.jpg
digital            | f
unit_description   | 1 - 10oz Jar
package_dimensions | 4x8x2
weight_in_pounds   | 3.2
reorder_amount     | 10
status             | in-stock
requires_shipping  | t
warehouse_location | Zone 1, Shelf 12, Slot 6
created_at         | ...
updated_at         | ...
...

Select the Spacebar to page through the results. Enter q to exit the pager.

Exit psql

\q

Run the application interactively via the command line

On the remote machine, change to the directory that contains the application:

cd tailwind-traders-go/app

Run the application interactively from the command line:

go run main.go app:serve

The following output appears:

$ go run main.go app:serve
Listening on :8080

Find the public IP address of the VM

Get the public IP address of the virtual machine:

IP_ADDRESS=$(az network public-ip show \
    --resource-group 240900-linux-postgres \
    --name vm-1-ip \
    --query ipAddress \
    --out tsv)

Output the URL to the terminal:

echo "Your URL is: http://${IP_ADDRESS}:8080"

This unit uses port 8080 for interactive dev/test purposes. In production, you would use port 443 and require a TLS certificate to help secure traffic to the endpoint.

Browse the public API endpoint

Open the URL in a web browser. The following output appears:

{
  "id": 5,
  "product_type_id": 1,
  "supplier_id": 2,
  "sku": "drafting_tools",
  "name": "Bespoke Drafting Set",
  "price": 45,
  "description": "Build your next bridge (or tunnel) using our Bespoke Drafting Set. Everyone drives across *regular* bridges everyday - but they'll rememeber yours - because it's _bespoke_.",
  "image": "drafting_tools.jpg",
  "digital": false,
  "unit_description": "Tools and carrying case",
  "package_dimensions": "5x10x3",
  "weight_in_pounds": "1.2",
  "reorder_amount": 10,
  "status": "in-stock",
  "requires_shipping": true,
  "warehouse_location": "Zone 1, Shelf 4, Slot 1",
  "created_at": "...",
  "updated_at": "..."
}

Alternatively, you can make a request to the API endpoint by using curl:

curl "http://${IP_ADDRESS}:8080"

This endpoint displays a random product from the database.

View requests logged to the terminal

Return to the terminal where you're running the application interactively. The output shows the request to the API endpoint:

{"time":"...","level":"INFO","msg":"httpLog","remoteAddr":"[::1]:58592","method":"GET","url":"/"}
{"time":"...","level":"INFO","msg":"httpLog","remoteAddr":"[::1]:59414","method":"GET","url":"/"}
{"time":"...","level":"INFO","msg":"httpLog","remoteAddr":"[::1]:59414","method":"GET","url":"/favicon.ico"}

If these requests are successful, you successfully migrated the application workload to an Azure virtual machine and Azure Database for PostgreSQL (Flexible Server).

Clean up Azure resources

After you finish exploring the Linux and PostgreSQL workloads, clean up the resources to save costs.

You can delete the resource group 240900-linux-postgres manually via the Azure portal, or run the following Azure CLI command:

az group delete \
    --name 240900-linux-postgres \
    --yes \
    --no-wait

Another option is to use the empty.bicep template to delete the resources that the vm-postgres.bicep file created. Running az deployment group create with --mode Complete removes any resources that the template doesn't define. Because empty.json has no resources, the command deletes every resource.

az deployment group create \
    --resource-group 240900-linux-postgres \
    --template-file deploy/empty.bicep \
    --mode Complete

Deploying empty.json leaves the 240900-linux-postgres resource group intact, so you can deploy the resources again by using a single command.

Explore and run Linux and PostgreSQL workloads

Deploy a storage account by using deploy/vm-postgres.bicep

Add the current user to the Storage Blob Data Owner role

Create a container called container1 in the storage account

Migrate images to the storage account into a subfolder

Upload app/data/postgres/tailwind.sql to the storage account

Connect to the Azure virtual machine by using the az ssh command

Download the tailwind.sql file from the storage account

Set the environment variables for psql on the remote machine

Import tailwind.sql by using psql

Connect to the Postgres server to confirm that the import was successful

List the tables

Run a SQL query that lists the tables

Turn on expanded mode and select from the products table

Exit psql

Run the application interactively via the command line

Find the public IP address of the VM

Browse the public API endpoint

View requests logged to the terminal

Clean up Azure resources

Resources

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