Cosmos DB Setup

You are an Azure cloud infrastructure engineer. The user wants to set up Azure Cosmos DB with proper configuration, connection, and data initialization.

What to check first

• Run az account show to verify you're authenticated to the correct Azure subscription
• Run az cosmosdb list --output table to see if a Cosmos DB account already exists
• Verify the Azure CLI is installed: az --version

Steps

1. Create a resource group with az group create --name myResourceGroup --location eastus
2. Create a Cosmos DB account using az cosmosdb create --resource-group myResourceGroup --name mycosmosdb --kind GlobalDocumentDB (this takes 5-10 minutes)
3. Get the primary connection string: az cosmosdb keys list --resource-group myResourceGroup --name mycosmosdb --type connection-strings --query connectionStrings[0].connectionString
4. Create a database within the account using az cosmosdb sql database create --resource-group myResourceGroup --account-name mycosmosdb --name myDatabase
5. Create a container (collection) with az cosmosdb sql container create --resource-group myResourceGroup --account-name mycosmosdb --database-name myDatabase --name myContainer --partition-key-path "/id"
6. Set throughput (RUs) for the container: az cosmosdb sql container throughput update --resource-group myResourceGroup --account-name mycosmosdb --database-name myDatabase --name myContainer --throughput 400
7. Store the connection string as an environment variable for your application to consume
8. Test connectivity by initializing a client connection and performing a read operation

Code

import os
from azure.cosmos import CosmosClient, PartitionKey

# Retrieve connection string from environment or Azure Key Vault
connection_string = os.getenv("COSMOS_CONNECTION_STRING")
database_name = "myDatabase"
container_name = "myContainer"

# Initialize Cosmos DB client
client = CosmosClient.from_connection_string(connection_string)

# Get or create database
database = client.create_database_if_not_exists(id=database_name)
print(f"Database '{database_name}' ready")

# Get or create container with partition key
container = database.create_container_if_not_exists(
    id=container_name,
    partition_key=PartitionKey(path="/id"),
    offer_throughput=400
)
print(f"Container '{container_name}' ready")

# Insert sample document
sample_item = {
    "id": "item-001",
    "name": "Sample Item",
    "category": "example",
    "price": 29.99
}

created_item = container.create_item(body=sample_item)
print(f"Inserted document: {created_item['id']}")

# Query documents
query = "SELECT * FROM c WHERE c.category = @category"

Note: this example was truncated in the source. See the GitHub repo for the latest full version.

Common Pitfalls

• Treating this skill as a one-shot solution — most workflows need iteration and verification
• Skipping the verification steps — you don't know it worked until you measure
• Applying this skill without understanding the underlying problem — read the related docs first

When NOT to Use This Skill

• When a simpler manual approach would take less than 10 minutes
• On critical production systems without testing in staging first
• When you don't have permission or authorization to make these changes

How to Verify It Worked

• Run the verification steps documented above
• Compare the output against your expected baseline
• Check logs for any warnings or errors — silent failures are the worst kind

Production Considerations

• Test in staging before deploying to production
• Have a rollback plan — every change should be reversible
• Monitor the affected systems for at least 24 hours after the change