Disaster Recovery

Disaster Recovery Overview

At its core, disaster recovery is about doing one thing well inside your DynamoDB project. Once you understand the pattern, you can apply it consistently across features and teams.

Good disaster recovery pays off across the whole codebase: fewer surprises, easier testing, and smoother onboarding. The snippet below is a solid starting point.

import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocumentClient, GetCommand, PutCommand } from '@aws-sdk/lib-dynamodb';

const client = new DynamoDBClient({});
const docClient = DynamoDBDocumentClient.from(client);

// reuse docClient across the module for efficient, typed access
await docClient.send(new PutCommand({ TableName: 'Orders', Item: { pk: '1' } }));

The DynamoDBDocumentClient maps plain JavaScript objects to DynamoDB item format for you.

Disaster Recovery Example

import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocumentClient } from '@aws-sdk/lib-dynamodb';

const docClient = DynamoDBDocumentClient.from(new DynamoDBClient({}));
// docClient.send(new PutCommand(...)) etc.

• Start from a minimal Disaster Recovery example and grow it only as needed.
• Keep configuration explicit so Disaster Recovery behaves the same in every environment.
• Name things clearly so teammates understand your Disaster Recovery at a glance.
• Add tests around Disaster Recovery early to lock in expected behaviour.

Amazon DynamoDB Cheatsheet

Handy DynamoDB (AWS SDK v3) reference related to disaster recovery.

How Disaster Recovery Works in DynamoDB

Disaster Recovery builds on DynamoDB's key-value and document model, where every item lives in a partition chosen by its partition key and is optionally ordered by a sort key.

The DynamoDBDocumentClient maps plain JavaScript objects to DynamoDB item format for you.

• Design access patterns first, then model keys around them.
• Prefer Query over Scan for predictable performance.
• Use expressions to read and write only what you need.
• Keep items small and avoid hot partitions.

Practical Guidance for Disaster Recovery

In production, disaster recovery should be cost-aware and resilient. Right-size capacity, handle throttling with retries, and lean on indexes to support your query patterns.

Common Mistakes

• Skipping error handling and edge cases when wiring up disaster recovery.
• Leaving disaster recovery untested, so regressions slip into production.
• Over-engineering disaster recovery before you actually need the extra flexibility.
• Ignoring documentation, which makes disaster recovery hard for the next developer to change.

Key Takeaways

• Disaster Recovery is a core part of working effectively with DynamoDB.
• Start small and keep disaster recovery focused on a single responsibility.
• Apply consistent patterns so disaster recovery scales across your project.
• Test and document disaster recovery to keep it maintainable over time.