A company launched a service that produces millions of messages every day and uses Amazon Kinesis Data Streams as the streaming service.
The company uses the Kinesis SDK to write data to Kinesis Data Streams. A few months after launch, a data analyst found that write performance is significantly reduced. The data analyst investigated the metrics and determined that Kinesis is throttling the write requests. The data analyst wants to address this issue without significant changes to the architecture. Which actions should the data analyst take to resolve this issue? (Choose two.)

Question

A company launched a service that produces millions of messages every day and uses Amazon Kinesis Data Streams as the streaming service.

The company uses the Kinesis SDK to write data to Kinesis Data Streams. A few months after launch, a data analyst found that write performance is significantly reduced. The data analyst investigated the metrics and determined that Kinesis is throttling the write requests. The data analyst wants to address this issue without significant changes to the architecture. Which actions should the data analyst take to resolve this issue? (Choose two.)

Lonely Sayi · Accepted Answer

Increase the Kinesis Data Streams retention period to reduce throttling.

Lonely Sayi · Accepted Answer

Increase the number of shards in the stream using the UpdateShardCount API.

Lonely Sayi · Answer

Replace the Kinesis API-based data ingestion mechanism with Kinesis Agent.

Lonely Sayi · Answer

Choose partition keys in a way that results in a uniform record distribution across shards.

Lonely Sayi · Answer

Customize the application code to include retry logic to improve performance.

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