A solutions architect is designing a database tier for a new high-throughput social networking application. The application requires microsecond read latency to serve a small list of popular trending profiles. The write volume is expected to scale up to transactions per second, and the architect must ensure that these write operations are evenly distributed to prevent partition bottlenecks on the underlying Amazon DynamoDB table.
Which TWO options should the solutions architect select to meet these performance requirements?
- Deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache read requests for popular profiles.Cevap
- Choose a high-cardinality attribute, such as a unique UserID, as the partition key.Cevap
- CChoose a monotonically increasing attribute, such as a registration timestamp, as the partition key.
- DConfigure Amazon RDS Read Replicas to act as the primary write target during peak workloads.
Cevap
Deploying an Amazon DynamoDB Accelerator (DAX) cluster to cache read requests for popular profiles, and choosing a high-cardinality attribute, such as a unique UserID, as the partition key.
The correct architecture requires deploying a DynamoDB Accelerator (DAX) cluster to provide in-memory microsecond read responses for the trending profiles. It also requires selecting a high-cardinality partition key, such as UserID, to distribute the write load of transactions per second evenly across partitions and avoid write bottlenecks.
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High-performing DynamoDB architectures rely on in-memory caching (DAX) for sub-millisecond read access and high-cardinality partition keys to distribute read/write throughput uniformly across partitions.
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