This Guidance uses DynamoDB Streams to automatically stream changes from your DynamoDB table to Lambda . This eliminates the need for you to build and maintain custom data streaming pipelines. Plus, with logging and monitoring in Amazon CloudWatch , you can quickly identify and troubleshoot any issues that may arise.

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By using DynamoDB and Lambda , you benefit from robust security features built into these AWS services. Specifically, DynamoDB offers encryption for data at rest, while Lambda provides a secure, isolated execution environment. Together, these services help ensure your sensitive data is protected from unauthorized access or tampering. Additionally, this Guidance follows the principle of least privilege, granting only the necessary permissions to the Lambda function to access and process the DynamoDB data, further strengthening the overall security posture.

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DynamoDB , DynamoDB Streams , and Lambda are all fully managed services provided by AWS. Lambda includes features such as automatic retries and error handling mechanisms to manage issues that arise while processing incoming data from the streams. All the services used throughout this Guidance can automatically scale under high loads, don't require downtime for patching, and are fault-tolerant by design with retry mechanisms built in.

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This Guidance uses DynamoDB Streams to invoke Lambda functions. Utilizing these services allows you to access aggregated data efficiently without the need for costly table scans, which can be time-consuming and impact system latency. Invoking Lambda functions through DynamoDB Streams not only improves data retrieval efficiency but also addresses potential latency issues that arise from scanning large datasets, enhancing the overall performance of your system.

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With DynamoDB and Lambda , you pay only for the resources you use, eliminating the need to manage hardware. And since DynamoDB Streams is a built-in feature of DynamoDB , streaming data incurs no extra charge. This approach of streaming data from DynamoDB Streams , aggregating it through Lambda functions, and writing the aggregated data back to DynamoDB is more cost-effective compared to performing full table scans for aggregations. It's also more economical than streaming data to a separate database for such calculations.

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This Guidance supports sustainable workloads through the serverless architecture of Lambda , which optimizes resource allocation and reduces the need to maintain physical hardware. The Lambda functions are only invoked when there is a change in the data in the base DynamoDB table, thus reducing the compute resource run times and the number of executions. This approach helps eliminate the need to maintain physical infrastructure, contributing to more sustainable workloads.

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