Lambda & DynamoDB Integration
Develop Lambda functions that interact with DynamoDB to perform CRUD operations, building data-driven serverless backends.
Lambda & DynamoDB Integration is a free Serverless Backend with AWS Lambda & API Gateway lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Serverless Backend with AWS Lambda & API Gateway learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Lambda & DynamoDB: The Power Duo
Welcome to integrating AWS Lambda with DynamoDB! This combination is a cornerstone for building powerful, serverless backends.
AWS Lambda provides the compute power to run your code without managing servers, while DynamoDB offers a fast, flexible NoSQL database that scales automatically.
Together, they allow you to create data-driven applications that handle create, read, update, and delete (CRUD) operations efficiently.
Granting Lambda DynamoDB Access
Before your Lambda function can interact with DynamoDB, it needs permission. This is managed through an IAM Role attached to your Lambda function.
The IAM role must have a policy that grants specific DynamoDB actions, such as:
dynamodb:PutItem(for creating/updating)dynamodb:GetItem(for reading)dynamodb:UpdateItem(for modifying parts of an item)dynamodb:DeleteItem(for removing items)
Always follow the principle of least privilege: grant only the permissions necessary.
Connecting from Lambda with Boto3
In a Python Lambda function, you'll use the AWS SDK for Python, Boto3, to interact with DynamoDB. First, you need to initialize a DynamoDB client or resource.
The boto3.resource('dynamodb') approach is often preferred as it provides a higher-level, object-oriented interface.
Try running this example to see how to initialize the client:
import boto3
import json
def lambda_handler(event, context):
# Initialize DynamoDB resource
dynamodb = boto3.resource('dynamodb')
table_name = 'my-coddykit-table' # Placeholder
table = dynamodb.Table(table_name)
print(f"Connected to table: {table_name}")
return {
'statusCode': 200,
'body': json.dumps('DynamoDB client initialized!')
}
# For local testing/runnable snippet
if __name__ == '__main__':
print("Running handler locally...")
lambda_handler({}, {})Creating & Replacing Items (PutItem)
The put_item() method is used to create a new item or completely replace an existing item in a DynamoDB table.
- If an item with the same primary key already exists,
put_item()will overwrite it entirely. - If no item with that primary key exists, it will create a new one.
This operation is useful when you want to ensure an item exists with specific attributes, or you need to replace all its attributes.
PutItem in Action
Here's a Lambda function demonstrating how to use put_item() to add or update an item. We'll use a placeholder table name and item details from the event.
Run the code to see the simulated item creation!
import boto3
import json
def lambda_handler(event, context):
dynamodb = boto3.resource('dynamodb')
# Use a placeholder table name
table = dynamodb.Table('my-coddykit-table')
item_id = event.get('itemId', 'P001')
item_name = event.get('itemName', 'New Product')
table.put_item(
Item={
'itemId': item_id,
'itemName': item_name,
'category': 'Electronics'
}
)
print(f"Added/updated item: {item_id}")
return {
'statusCode': 200,
'body': json.dumps(f'Item {item_id} processed!')
}
# For local testing/runnable snippet
if __name__ == '__main__':
mock_event = {'itemId': 'P002', 'itemName': 'Coddy Phone'}
lambda_handler(mock_event, {})Reading Items (GetItem)
To retrieve a single item from a DynamoDB table, you use the get_item() method. This operation requires you to provide the full primary key of the item.
If your table has a simple primary key (only a Partition Key), you'll provide just that value. If it has a composite primary key (Partition Key and Sort Key), you must provide both.
get_item() is highly efficient for direct lookups.
GetItem in Action
This Lambda function shows how to retrieve an item using its itemId (assuming it's our primary key). The response will contain the item's attributes if found.
Run this example to see how get_item() works.
import boto3
import json
def lambda_handler(event, context):
dynamodb = boto3.resource('dynamodb')
# Use a placeholder table name
table = dynamodb.Table('my-coddykit-table')
item_id = event.get('itemId', 'P001') # Assume 'itemId' is the primary key
response = table.get_item(
Key={'itemId': item_id}
)
item = response.get('Item')
if item:
print(f"Found item: {item}")
return {
'statusCode': 200,
'body': json.dumps(item)
}
else:
print(f"Item {item_id} not found.")
return {
'statusCode': 404,
'body': json.dumps(f'Item {item_id} not found.')
}
# For local testing/runnable snippet
if __name__ == '__main__':
mock_event = {'itemId': 'P002'} # Try to get an item
lambda_handler(mock_event, {})Modifying Parts of an Item (UpdateItem)
The update_item() method allows you to modify specific attributes of an existing item without replacing the entire item.
This is more efficient than put_item() if you only need to change a few attributes. It requires an UpdateExpression to specify which attributes to modify and how.
Update expressions can add, set, remove, or delete attributes.
Removing Items (DeleteItem)
To delete an item from a DynamoDB table, you use the delete_item() method. Similar to get_item(), you must provide the full primary key of the item you wish to remove.
Once an item is deleted, it cannot be recovered through this operation. Be cautious when using delete_item(), especially in production environments.
Quick Check: DynamoDB Operations
You need to create a new user profile in your DynamoDB Users table. If a user with the same ID already exists, you want to completely overwrite their old profile with the new data. Which Boto3 method should your Lambda function use?
Recap: Lambda & DynamoDB Integration
Great job! You've learned how to integrate AWS Lambda with DynamoDB to build data-driven serverless applications.
- We covered the importance of IAM permissions for secure access.
- You saw how to use the Boto3 SDK to connect from Python Lambda.
- We explored the core CRUD operations:
put_item()(create/replace),get_item()(read),update_item()(modify), anddelete_item()(remove).
This knowledge is crucial for developing robust serverless backends!
Frequently asked questions
Is the “Lambda & DynamoDB Integration” lesson free?
Yes — the full text of “Lambda & DynamoDB Integration” is free to read here on the web, and the Serverless Backend with AWS Lambda & API Gateway course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Serverless Backend with AWS Lambda & API Gateway course, upgrade to CoddyKit PRO.
What will I learn in “Lambda & DynamoDB Integration”?
Develop Lambda functions that interact with DynamoDB to perform CRUD operations, building data-driven serverless backends. You practise Serverless Backend with AWS Lambda & API Gateway with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Serverless Backend with AWS Lambda & API Gateway?
No prior experience is required. Serverless Backend with AWS Lambda & API Gateway on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Lambda & DynamoDB Integration” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Serverless Backend with AWS Lambda & API Gateway lesson?
Yes. Every Serverless Backend with AWS Lambda & API Gateway lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Introduction to DynamoDB
- Designing DynamoDB Tables
- Lambda & DynamoDB Integration
- Querying with Secondary Indexes: GSIs and LSIs