Real-Time Data Search with DynamoDB and Amazon OpenSearch Using AWS CDK: A Zero-ETL Solution

Introduction to Zero-ETL Integration Between DynamoDB and OpenSearch

In modern data architecture, minimizing data transformation overhead is crucial for enhancing efficiency. Zero-ETL (Extract, Transform, Load) integration provides a solution by streamlining data ingestion directly between systems without complex processing steps. One such powerful example is the integration of Amazon DynamoDB and Amazon OpenSearch Service, which allows for real-time indexing and querying of DynamoDB data without needing traditional ETL pipelines. This blog post explores how to implement this seamless integration using AWS Cloud Development Kit (CDK).

Understanding the Need for Seamless Data Integration

Businesses often need to extract data from DynamoDB to perform full-text searches, analytics, or other operations that aren’t native to the database. Traditionally, this requires creating and managing complex ETL pipelines to move data from DynamoDB to Amazon OpenSearch Service, which can be time-consuming, costly, and prone to delays. We can eliminate these complexities by leveraging Zero-ETL integration, providing real-time data availability in OpenSearch without additional transformation or transfer layers.

Overview of AWS CDK for Infrastructure Deployment

AWS CDK (Cloud Development Kit) is a framework that allows developers to define their cloud infrastructure using familiar programming languages such as TypeScript, Python, or JavaScript. It simplifies infrastructure-as-code (IaC) by abstracting AWS resources into high-level constructs. For this integration, AWS CDK helps to deploy DynamoDB, OpenSearch, and the required infrastructure components like IAM roles and Lambda functions, automating linking these services for real-time data ingestion.

Solution Architecture: Components and Their Interactions

The solution architecture for Zero-ETL integration between DynamoDB and OpenSearch consists of the following key components:

Amazon DynamoDB: This is the primary NoSQL database for storing operational data.
Amazon OpenSearch Service: Provides powerful search and analytical capabilities on the ingested DynamoDB data.
AWS Lambda is the trigger function that streams DynamoDB changes (using DynamoDB Streams) to OpenSearch in near real-time.
Amazon Kinesis Data Streams (Optional): Kinesis can buffer and process large volumes of data before indexing it into OpenSearch.
AWS CDK: Automates the provisioning of these resources, including configuring the DynamoDB stream, Lambda function, and OpenSearch ingestion.

Deploying the Zero-ETL Integration Solution with AWS CDK

Using AWS CDK, we can define and deploy the entire stack with minimal manual intervention. Here’s a high-level step-by-step guide:

Set up the CDK project: Initialize a new AWS CDK project in the language of your choice (e.g., TypeScript).
cdk init app –language=typescript
Define DynamoDB and OpenSearch resources: Use AWS CDK to declare the DynamoDB table and OpenSearch domain.
const dynamoTable = new dynamodb.Table(this, ‘MyTable’, { /* table properties */ });

const openSearchDomain = new opensearch.Domain(this, ‘MyOpenSearch’, { /* domain properties */ });

Create the Lambda function: Define the one that will be triggered by DynamoDB Streams and send data to OpenSearch.
const lambdaFunction = new lambda.Function(this, ‘DynamoToOpenSearch’, {

code: lambda.Code.fromAsset(‘lambda’),

handler: ‘index.handler’,

runtime: lambda.Runtime.NODEJS_14_X,

});

Set up DynamoDB Streams and Lambda trigger: Enable DynamoDB Streams and link the Lambda function to capture and process data changes.
dynamoTable.addStream(dynamodb.StreamViewType.NEW_IMAGE);

lambdaFunction.addEventSource(new DynamoEventSource(dynamoTable, { /* event source properties */ }));

Deploy the stack: Use CDK CLI to deploy the solution to your AWS account.
cdk deploy

Configuring OpenSearch Ingestion for DynamoDB Data

Once the infrastructure is in place, configure the Lambda function to process DynamoDB stream records and send them to OpenSearch for indexing. In the Lambda function, ensure that the following key steps are performed:

Extract DynamoDB records from the event trigger.
Transform records into a format that OpenSearch can index (e.g., JSON).
Send the records to OpenSearch using the OpenSearch SDK.

Here’s a basic outline of how to configure this in the Lambda function:

const { Client } = require(‘@opensearch-project/opensearch’);

const client = new Client({ node: ‘https://my-opensearch-domain’ });

exports.handler = async (event) => {

for (const record of event.Records) {

if (record.eventName === ‘INSERT’) {

const document = record.dynamodb.NewImage;

await client.index({

index: ‘dynamodb-data’,

body: document

});

}

};

Monitoring and Verifying the Integration Process

To ensure that the integration is functioning as expected, it’s essential to set up monitoring:

Amazon CloudWatch: Monitor the Lambda function’s performance, track invocation times, and catch errors or timeouts.
OpenSearch Dashboards: Verify that data from DynamoDB is being indexed correctly by querying the OpenSearch domain using OpenSearch Dashboards.
AWS CDK Outputs: For easy monitoring, use CDK to output relevant information, such as OpenSearch domain URLs and CloudWatch log links.

Conclusion: Enhancing Data Accessibility with Zero-ETL Integration

By leveraging AWS CDK, the integration of DynamoDB with Amazon OpenSearch becomes a highly efficient and scalable solution for real-time data search and analytics. The Zero-ETL approach eliminates the overhead of traditional data pipelines, enabling faster access to critical data insights with minimal latency.