KindleYou is a location-based social search mobile app that allows users to like or dislike other users, and allows users to chat if both parties liked each other in the app. It has more than 1 billion customers across the world.
They use DynamoDB to support the mobile application and S3 to host the images and other documents shared between users.
DynamoDB has a table with 60 partitions and is being heavily accessed by users. There are lots of hot partitions. To better accommodate uneven access patterns, how will DynamoDB use its capacity to prevent throttling?

Answer options:

A.Using Burst Capacity effectively
B.Using Adaptive Capacity
C.Design Partition Keys to distribute workload evenly
D.Using Write Sharding to Distribute Workloads Evenly

Answer: B
Option A is incorrect. DynamoDB provides some flexibility in your per-partition throughput provisioning by providing burst capacity. DynamoDB reserves a portion of that unused capacity for later bursts of throughput to handle usage spikes.
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-partition-key-design.html#bp-partition-key-partitions-adaptive
Option B is correct. Adaptive Capacity enables your application to continue reading and writing to hot partitions without being throttled, provided that traffic does not exceed your table’s total provisioned capacity or the partition maximum capacity
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-partition-key-design.html#bp-partition-key-partitions-adaptive
Option C is incorrect. The partition key portion of a table`s primary key determines the logical partitions in which a table`s data is stored. Provisioned I/O capacity for the table is divided evenly among these physical partitions. Therefore a partition key design that doesn`t distribute I/O requests evenly can create "hot" partitions that result in throttling and use your provisioned I/O capacity inefficiently. use your provisioned throughput more efficiently as the ratio of partition key values accessed to the total number of partition key values increases. This design is more useful for these specific partition keys like USERID where the application has many users and DEVICE ID where each device accesses data at relatively similar intervals. This involves re-designing or be cautious during design and handle specific workloads.
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-partition-key-uniform-load.html
Option D is incorrect.One way to better distribute writes across a partition key space in DynamoDB is to expand the space which can be done in several different ways.This includes adding a random number to the partition key values to distribute the items among partitions, or use a number that is calculated based on something that you are querying on. This involves re-designing or be cautious during design and handle specific workloads.
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-partition-key-sharding.html