Lambda Retry Handling

Lambda Retry Handling Overview

Lambda Retry Handling is a building block you will reach for often in DynamoDB. It keeps related logic together and makes your intent obvious to reviewers and future maintainers.

When you learn lambda retry handling properly, you avoid the guesswork that leads to bugs and rework. The example below shows the shape you will use in most real DynamoDB projects.

export const handler = async (event) => {
  for (const record of event.Records) {
    if (record.eventName === 'INSERT') {
      const newItem = record.dynamodb.NewImage;
      console.log('new item', newItem);
    }
  }
};

A Lambda triggered by DynamoDB Streams reacts to item-level INSERT, MODIFY, and REMOVE events.

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

Amazon DynamoDB Cheatsheet

Handy DynamoDB (AWS SDK v3) reference related to lambda retry handling.

How Lambda Retry Handling Works in DynamoDB

Lambda Retry Handling 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.

A Lambda triggered by DynamoDB Streams reacts to item-level INSERT, MODIFY, and REMOVE events.

• 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 Lambda Retry Handling

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

Common Mistakes

• Copying lambda retry handling snippets without understanding what each line does.
• Skipping error handling and edge cases when wiring up lambda retry handling.
• Leaving lambda retry handling untested, so regressions slip into production.
• Over-engineering lambda retry handling before you actually need the extra flexibility.

Key Takeaways

• Lambda Retry Handling is a core part of working effectively with DynamoDB.
• Start small and keep lambda retry handling focused on a single responsibility.
• Apply consistent patterns so lambda retry handling scales across your project.
• Test and document lambda retry handling to keep it maintainable over time.