What adjustment can be made to resolve a bottleneck in data throughput from a specific data source in Amazon Kinesis?

To effectively resolve a bottleneck in data throughput from a specific data source in Amazon Kinesis, changing the partition key to a more granular value is a valid adjustment that can be made. In Kinesis, data is distributed across shards based on the partition key. When a partition key is too broad or lacks granularity, it can lead to uneven data distribution across the available shards, resulting in some shards being overwhelmed while others remain underutilized.

By using a more granular partition key, you spread the data more evenly across multiple shards. This balanced distribution allows for higher throughput because more shards can handle the incoming data simultaneously. Each shard has a fixed read and write capacity, so increasing the number of partitions through finer-grained keys can alleviate pressure on the shards that are experiencing a bottleneck.

Other options might touch upon different methods for managing data but do not directly address the issue of granularity and distribution that is crucial for optimizing throughput in a streaming architecture like Kinesis.