Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 88 discussion

The best solution to resolve the issue of uneven shard usage and WriteThroughputExceeded exceptions is to balance the load more evenly across the shards. This can be effectively achieved by changing the partition key to something that ensures a more uniform distribution of data across the shards.

https://aws.amazon.com/blogs/big-data/under-the-hood-scaling-your-kinesis-data-streams/

The correct answer is **A. Change the partition key from facility ID to a randomly generated key.** Amazon Kinesis Data Streams uses the partition key that you specify to segregate the data records in the stream into shards. If the company uses the facility ID as the partition key, and if some facilities produce more data than others, then the data will be unevenly distributed across the shards. This can lead to some shards being heavily used while others are idle, and can cause `WriteThroughputExceeded` exceptions. By changing the partition key to a randomly generated key, the data records are more likely to be evenly distributed across all the shards, which can help to avoid the issue of some shards being heavily used and others being idle. This solution requires the least operational overhead and does not involve increasing costs (as in option B), archiving data (which might not be desirable or feasible, as in option C), or changing to a partition key that might also lead to uneven distribution (as in option D).

D is not good, because you're effectively making things worse by partitioning by date. My answer is A