DynamoDB Configuration

This document explains the DynamoDB table configuration for the serverless lab.

Overview

DynamoDB is a fully managed NoSQL database service that provides:

• Single-digit millisecond latency
• Automatic scaling
• Built-in security
• Global tables

Table Configuration

Events Table

Table Name: {project-name}-{environment}-events

Primary Key:

• event_id (String) - Hash key

Global Secondary Index:

• timestamp-index - Hash key: timestamp

Billing Mode: PAY_PER_REQUEST (On-demand)

Features:

• Point-in-time recovery enabled
• Encryption at rest
• Auto-scaling

Data Model

{
  "event_id": "s3-abc123",
  "event_type": "s3",
  "source": "my-bucket",
  "key": "path/to/file.txt",
  "event_name": "ObjectCreated:Put",
  "size": 1024,
  "content_type": "text/plain",
  "timestamp": "2024-01-01T00:00:00Z",
  "processed_at": "2024-01-01T00:00:01Z"
}

Usage

Put Item

import boto3

dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('devops-studio-dev-events')

table.put_item(
    Item={
        'event_id': 'test-123',
        'event_type': 'test',
        'timestamp': '2024-01-01T00:00:00Z'
    }
)

Query by Event ID

response = table.get_item(
    Key={'event_id': 'test-123'}
)

Query by Timestamp (GSI)

response = table.query(
    IndexName='timestamp-index',
    KeyConditionExpression='timestamp = :ts',
    ExpressionAttributeValues={
        ':ts': '2024-01-01T00:00:00Z'
    }
)

Best Practices

1. Partition Keys - Choose high-cardinality keys
2. GSI - Use for different query patterns
3. On-Demand - Use for variable workloads
4. Point-in-Time Recovery - Enable for production
5. Monitoring - Monitor read/write capacity

Cost Optimization

• Use on-demand billing for variable workloads
• Right-size read/write capacity (if using provisioned)
• Use DynamoDB Streams for change capture
• Enable auto-scaling (if using provisioned)