A logistics platform tracks real-time location updates from delivery couriers. The platfor… — AWS Certified Solutions Architect - Associate

A logistics platform tracks real-time location updates from delivery couriers. The platform must ingest high-velocity data, preserve the exact chronological order of updates per courier to avoid mapping errors, and automatically store the data in Amazon S3 in Apache Parquet format for historical analysis. The peak throughput is $8\text{ MB/s}$ and $6,000$ records per second. The solutions architect wants to minimize operational overhead and prevent ingestion throttling. Which combination of actions should the solutions architect take to meet these requirements? (Select two.)

Ingest the location updates using an Amazon Kinesis data stream, using the courier ID as the partition key.Cevap
Configure Amazon Data Firehose to read from the Kinesis data stream, and enable format conversion to Apache Parquet using the AWS Glue Data Catalog.Cevap
C
Ingest the location updates using an Amazon SQS standard queue to buffer messages, then use AWS Lambda to write the files to Amazon S3.
D
Provision an Amazon Kinesis data stream with exactly $4$ shards in provisioned mode to ingest the incoming telemetry.
E
Write a custom AWS Lambda function triggered directly by Kinesis Data Streams to batch, format, and convert the JSON payloads to Apache Parquet before writing them to Amazon S3.

Cevap

Ingest the location updates using an Amazon Kinesis data stream partitioned by courier ID, and configure Amazon Data Firehose to consume from this stream and perform format conversion to Apache Parquet using the AWS Glue Data Catalog.

Ingesting data using Amazon Kinesis Data Streams with a partition key based on the courier ID ensures that data from the same courier is mapped to the same shard, guaranteeing sequential processing. Utilizing Amazon Data Firehose allows serverless integration to read from the Kinesis stream and automatically convert JSON to Parquet format using schemas defined in the AWS Glue Data Catalog, delivering files to S3 with minimum operational management.

Adım Adım Çözüm

Select an ingestion service that guarantees ordering per entity.

Amazon Kinesis Data Streams is chosen with the courier ID designated as the partition key.

Routing events by the courier ID partition key ensures that all updates for a specific courier are sent to the same shard, preserving strict order of arrival.

Calculate the shard capacity requirements for Kinesis Data Streams.

A minimum of

8

shards is required to support the peak throughput of

8\text{ MB/s}

and

6,000

records per second.

Since one shard provides a maximum of

1\text{ MB/s}

1,000

records per second of write throughput,

4

shards would cause throttling exceptions.

Identify the option that transforms data with the lowest operational overhead.

Amazon Data Firehose is integrated to read from Kinesis Data Streams and convert data format via the AWS Glue Data Catalog.

This is a fully managed configuration that natively transforms JSON to Apache Parquet before storing it in S3, avoiding custom Lambda scripts or cluster management.

Anahtar Kavram

Real-time streaming ingestion pipelines requiring sequence preservation and serverless format conversion.

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Cevap

Adım Adım Çözüm

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