Amazon S3 Object Lambda

• Amazon S3 Object Lambda modifies content stored in Amazon S3 on the fly without the need to download, modify, and re-upload objects.
• It integrates with AWS Lambda for real-time data processing when an object is accessed.

Key Concepts

• S3 Object Lambda Access Point acts as an interface between an S3 bucket and a Lambda function.
• The access point performs operations before objects are delivered to the requester.
• Read requests to an object trigger Lambda functions that modify or filter data before returning it.
• A Lambda function is invoked upon object access via an S3 Object Lambda Access Point.
• The Lambda function can transform data (e.g., resizing images, filtering logs, adding metadata).
• Lambda functions can be written in Python, Node.js, Go, or Java.
• Object Lambda transforms data that doesn't need permanent transformation.
• It is useful for resizing images, decrypting documents, or converting CSV to JSON upon access.
• Transformed versions of objects need not be stored separately, reducing storage costs.

How it Works

• First, an S3 Object Lambda Access Point is created, pointing to an S3 bucket.
• The access point links to a Lambda function that gets called upon object access.
• When a request is made to retrieve an object (e.g., using GetObject), S3 sends the object data to the Lambda function.
• The Lambda function processes the object data.
• The transformed data is returned to the requester.
• The requester receives the processed content without manual transformation.

Common Use Cases

• Images can be resized on the fly without storing multiple versions.
• Custom content filters can be applied before serving the object.
• Log files can be dynamically processed (e.g., CSV to JSON).
• Structured data can be transformed to another format (e.g., CSV to JSON).
• Metadata associated with the object can be modified, or dynamic data can be injected.

Example Flow

• An S3 bucket contains raw CSV data.
• An S3 Object Lambda Access Point points to the bucket and connects to a Lambda function.
• The Lambda function converts the CSV to JSON, filters columns, and adds custom metadata.
• A client requests the CSV file from the Object Lambda Access Point.
• The S3 service invokes the Lambda function, which returns transformed JSON data to the client.

Benefits

• It reduces storage costs because there is no need to store multiple transformed copies; transformations occur in real-time.
• It allows for modified data to be delivered dynamically, allowing for customized and scalable data access patterns.
• It is secure because sensitive data can be filtered or masked before being served.
• It offers a streamlined workflow because S3 Object Lambda can be incorporated into existing workflows without needing to manually download, process, and upload modified versions of objects.
• It leverages Lambda's ecosystem to enhance data manipulation and integration.

Limitations

• Latency introduced by Lambda execution can increase the time it takes to serve data
• Lambda function execution limits (e.g., 15 minutes max execution time) limit large-scale transformations
• Costs for Lambda invocations and data processing might increase
• Transformed versions of your data will not be saved

How to Set It Up

• Develop and deploy the Lambda function to process the object data
• Create an Object Lambda Access Point in the S3 console, linking it to the Lambda function
• Any GetObject request triggers the Lambda function, which returns the transformed data.

Amazon S3 Object Lambda modifies content on the fly using AWS Lambda, without altering the original stored objects. It uses S3 Object Lambda Access Points as interfaces, triggering Lambda functions upon object access. The Lambda function transforms data, such as resizing images or converting file formats, before delivery.