Final answer:
To improve the performance of Amazon Kinesis Data Streams, it is recommended to increase the number of shards, implement efficient data batching, optimize data consumers, and potentially use the enhanced fan-out feature for dedicated throughput per consumer.
Step-by-step explanation:
Improving Performance in Amazon Kinesis Data Streams If a Solutions Architect notices that a system based on Amazon Kinesis Data Streams is performing slowly, there are several recommendations that can be made to improve performance. Assuming the system has a total throughput of 10 Mb/s and it is identified as a bottleneck, here are some potential solutions:Increase the number of shards in the Kinesis stream, as each shard provides a dedicated throughput of 1MB/s for writes and 2MB/s for reads.Implement or improve data batching to more efficiently utilize each shard's capacity.Optimize the data consumers (i.e., the processing application) to ensure they can keep up with the shard's read rates.Use enhanced fan-out feature for consumers, which provides a dedicated throughput per consumer rather than sharing it across all consumers.By addressing these areas, the Solutions Architect can enhance the throughput and efficiency of the system, leading to better performance.
To improve the performance of the Amazon Kinesis Data Streams system, the Solutions Architect can make several recommendations:Increase the number of shards in the stream: Each shard can provide a maximum input rate of 1 MB/s and 1000 writes per second (WPS). By increasing the number of shards, the total throughput of the stream can be increased.Revisit the data size: If the average data size being ingested is less than the shard capacity, it is possible to increase the number of writes per second by sending smaller chunks of data more frequently.Simplify the data processing logic: Complex data processing operations can have an impact on the system's performance. The Solutions Architect should review the data processing operations and optimize them to minimize latency and increase throughput.