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Zorluk: KolayHigh-Performing Data Ingestion and Transformation Solutions

A retail company wants to track real-time inventory updates from 100100 physical stores. Each store publishes an inventory update XML payload (averaging 10 KB10\text{ KB} each) every 55 seconds. The company wants to ingest this data with minimal operational overhead, automatically convert the XML payload to JSON format, and write the JSON data to an Amazon S3 bucket for downstream analytics.

Which two AWS services or features should the solutions architect combine to build this solution? (Select two.)

  1. Amazon Data Firehose to ingest the incoming stream and deliver the transformed data to Amazon S3.Cevap
  2. An AWS Lambda function integrated with Amazon Data Firehose to perform the XML-to-JSON transformation.Cevap
  3. C
    Amazon Kinesis Data Streams with provisioned shards to ingest the incoming stream.
  4. D
    Amazon SQS standard queue to store the incoming XML payloads.
  5. E
    Amazon Managed Streaming for Apache Kafka (Amazon MSK) to ingest and store the stream.

Cevap

The solutions architect should combine Amazon Data Firehose and an integrated AWS Lambda function to ingest the data stream, convert the XML payloads to JSON, and deliver the output to Amazon S3 with minimal operational overhead.
Combining Amazon Data Firehose with an integrated AWS Lambda function provides a completely serverless, high-performing data ingestion and transformation pipeline. Amazon Data Firehose manages the ingestion and automatically scales to deliver the transformed data to the destination Amazon S3 bucket. The integrated AWS Lambda function executes the custom logic to convert the XML payloads to JSON format inline as the data flows through the stream, requiring no server provisioning or management.

Adım Adım Çözüm

1
Select Amazon Data Firehose to serve as the streaming delivery stream.
This provides an auto-scaling, serverless ingestion service that natively integrates with Amazon S3 as a destination, minimizing operational management.
Firehose handles high-throughput stream ingestion and handles S3 delivery out of the box.
2
Create an AWS Lambda function with the logic to parse XML payloads and output JSON format.
A serverless transformation function is defined that can run on small batches of records.
Lambda scales automatically with Firehose invocations and performs the required transformation without requiring dedicated servers.
3
Enable the Data Transformation feature in the Amazon Data Firehose stream and associate the Lambda function.
Incoming data is buffered, passed to Lambda for inline conversion, and then written as JSON to the target S3 bucket.
This configuration connects ingestion and transformation into a single managed pipeline.

Anahtar Kavram

Serverless real-time data ingestion and inline transformation using Amazon Data Firehose and AWS Lambda.
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High-Performing Data Ingestion and Transformation Solutions

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