Stream processing patterns in DynamoDB - Mini Project: Build & Apply

Stream Processing Patterns with DynamoDB

📖 Scenario: You are working on a simple inventory management system that tracks product stock levels. Whenever a product's stock changes, the update is recorded in a DynamoDB table. You want to process these changes in real-time using DynamoDB Streams to keep another table updated with the latest stock status.

🎯 Goal: Build a DynamoDB stream processing setup that captures changes from a Products table and updates a StockStatus table accordingly.

📋 What You'll Learn

Create a DynamoDB table called Products with a primary key ProductID and an attribute Stock.

Enable DynamoDB Streams on the Products table to capture item updates.

Create a configuration variable stream_arn to hold the stream ARN of the Products table.

Write a Lambda function that processes stream records and updates the StockStatus table with the latest stock for each product.

Ensure the Lambda function uses the stream_arn to connect to the stream.

💡 Why This Matters

🌍 Real World

Real-time inventory tracking systems use DynamoDB Streams and Lambda to keep stock data synchronized across services.

💼 Career

Understanding stream processing patterns with DynamoDB is valuable for backend developers and cloud engineers working on scalable, event-driven applications.

1

Create the Products table with stock attribute

Create a DynamoDB table named Products with a primary key called ProductID (string type). Add an attribute called Stock to store the stock quantity (number type). Use AWS CLI or AWS SDK commands to define this table.

DynamoDB

# Your AWS CLI or SDK command to create the Products table with ProductID as primary key and Stock attribute

Hint

Use the AWS CLI create-table command with --attribute-definitions and --key-schema to define the primary key.

2

Enable DynamoDB Streams and set stream ARN variable

Enable DynamoDB Streams on the Products table with the view type set to NEW_IMAGE. Create a variable called stream_arn that stores the stream ARN of the Products table.

DynamoDB

aws dynamodb update-table \
    --table-name Products \
    --stream-specification StreamEnabled=true,StreamViewType=NEW_IMAGE

# Create a variable called stream_arn to hold the stream ARN
# Your code here

Hint

Use update-table to enable streams and describe-table to get the stream ARN.

3

Write Lambda function to process stream records

Write a Lambda function in Python named process_stream_records that takes event and context as parameters. For each record in event['Records'], extract the ProductID and Stock from the NewImage. Use these values to update the StockStatus table with the latest stock quantity.

DynamoDB

import boto3

dynamodb = boto3.resource('dynamodb')
stock_table = dynamodb.Table('StockStatus')

def process_stream_records(event, context):
    # Your code here

Hint

Loop through event['Records'], extract ProductID and Stock from NewImage, then update StockStatus table.

4

Configure Lambda to use stream ARN and complete setup

Configure the Lambda function to use the stream_arn variable as the event source. Add the necessary permissions and complete the setup so that the Lambda function triggers on changes in the Products table stream.

DynamoDB

# Use AWS CLI or SDK to create event source mapping for Lambda with stream_arn
# Your code here

Hint

Use create-event-source-mapping AWS CLI command to connect the Lambda function to the DynamoDB stream using stream_arn.

Practice

1. What is the main purpose of using DynamoDB Streams in stream processing patterns?

easy

A. To capture and react to data changes in real time

B. To store large amounts of data permanently

C. To create backups of the database

D. To improve query speed by indexing

Solution

1. Step 1: Understand DynamoDB Streams role

   DynamoDB Streams capture data changes like inserts, updates, and deletes as they happen.

2. Step 2: Identify the purpose in stream processing

   Streams allow applications to react immediately to these changes, enabling real-time processing.

3. Final Answer:

   To capture and react to data changes in real time -> Option A

4. Quick Check:

   Streams = real-time data reaction [OK]

Hint: Streams track changes instantly for real-time reactions [OK]

Common Mistakes:

• Confusing Streams with data storage
• Thinking Streams create backups
• Assuming Streams speed up queries

2. Which of the following is the correct way to enable a DynamoDB Stream on a table?

easy

A. Create a global secondary index with Streams enabled

B. Add a Lambda trigger without enabling Streams

C. Set StreamSpecification with StreamEnabled = true and StreamViewType

D. Use the UpdateItem API to activate Streams

Solution

1. Step 1: Recall how to enable Streams

   Streams are enabled by setting the StreamSpecification property on the table with StreamEnabled set to true and choosing a StreamViewType.

2. Step 2: Evaluate options

   Set StreamSpecification with StreamEnabled = true and StreamViewType correctly describes enabling Streams. The other options do not enable Streams properly.

3. Final Answer:

   Set StreamSpecification with StreamEnabled = true and StreamViewType -> Option C

4. Quick Check:

   Enable Streams via StreamSpecification [OK]

Hint: Enable Streams in table settings, not via Lambda or indexes [OK]

Common Mistakes:

• Trying to enable Streams via Lambda triggers
• Confusing Streams with indexes
• Using UpdateItem API to enable Streams

3. Given a DynamoDB Stream enabled with NEW_IMAGE view type, what will a Lambda function receive when an item is updated?

medium

A. Only the old item image before the update

B. Only the new item image after the update

C. Both old and new item images

D. No item images, only keys

Solution

1. Step 1: Understand StreamViewType NEW_IMAGE

   NEW_IMAGE means the stream records contain the item as it appears after the change.

2. Step 2: Determine what Lambda receives on update

   Lambda gets the new item image only, not the old one or both.

3. Final Answer:

   Only the new item image after the update -> Option B

4. Quick Check:

   NEW_IMAGE = new item data only [OK]

Hint: NEW_IMAGE streams send updated item data only [OK]

Common Mistakes:

• Confusing NEW_IMAGE with OLD_IMAGE or BOTH_IMAGES
• Expecting both old and new images
• Assuming keys only are sent

4. A developer wrote a Lambda function triggered by DynamoDB Streams but it never processes any records. What is the most likely cause?

medium

A. The DynamoDB table does not have Streams enabled

B. The Lambda function code has a syntax error

C. The table has no data at all

D. The Lambda function timeout is too long

Solution

1. Step 1: Check Stream enablement

   If Streams are not enabled on the table, no events trigger Lambda.

2. Step 2: Evaluate other options

   Syntax errors cause failures but do not prevent invocation. No data means no changes, but usually there are some. Timeout too long does not stop invocation.

3. Final Answer:

   The DynamoDB table does not have Streams enabled -> Option A

4. Quick Check:

   Streams must be enabled for Lambda triggers [OK]

Hint: Check if Streams are enabled before debugging Lambda code [OK]

Common Mistakes:

• Assuming code errors stop Lambda from triggering
• Ignoring Streams enablement
• Thinking timeout affects event triggering

5. You want to build a system that sends notifications only when a specific attribute "status" changes in DynamoDB items. Which stream processing pattern best fits this requirement?

hard

A. Use Streams with OLD_IMAGE view type only

B. Disable Streams and poll the table periodically

C. Enable Streams with KEYS_ONLY view type and check keys in Lambda

D. Filter and transform stream records in Lambda to detect "status" changes

Solution

1. Step 1: Understand the need to detect attribute changes

   To detect changes in "status", you need both old and new values to compare.

2. Step 2: Choose the right pattern

   Filtering and transforming stream records in Lambda lets you compare old and new images and trigger notifications only on "status" changes.

3. Step 3: Evaluate other options

   OLD_IMAGE alone lacks new data, KEYS_ONLY lacks attribute data, polling is inefficient and not real-time.

4. Final Answer:

   Filter and transform stream records in Lambda to detect "status" changes -> Option D

5. Quick Check:

   Filter stream records in Lambda for attribute changes [OK]

Hint: Compare old and new images in Lambda to detect attribute changes [OK]

Common Mistakes:

• Using KEYS_ONLY which lacks attribute data
• Relying on OLD_IMAGE without new data
• Polling instead of using Streams