An IoT fleet management company is deploying a new tracking solution where thousands of vehicles send location telemetry data every second. The database must ingest this write-heavy workload with low latency. Which two strategies should a solutions architect recommend to optimize write performance and prevent database throttling? (Select TWO.)
- Use the vehicle ID as the partition key and the timestamp as the sort key for the Amazon DynamoDB table.Cevap
- Configure Amazon DynamoDB on-demand capacity mode or enable auto-scaling for provisioned write capacity.Cevap
- CUse the current date as the partition key and the vehicle ID as the sort key to ensure daily records are grouped together.
- DMigrate the database to Amazon RDS for PostgreSQL and add multiple Read Replicas to offload write operations.
- EConfigure the DynamoDB table with fixed provisioned capacity and disable auto-scaling to prevent latency fluctuations.
Cevap
The solutions architect should use the vehicle ID as the partition key and the timestamp as the sort key to distribute partition traffic, and configure on-demand capacity or auto-scaling to dynamically scale write capacity.
Using the vehicle ID as the partition key distributes write operations evenly across multiple partitions. Combined with on-demand capacity or auto-scaling, the database adapts to traffic changes dynamically, maintaining high performance under heavy load.
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Anahtar Kavram
High-performing write workloads in DynamoDB require high-cardinality partition keys and elastic scaling modes (auto-scaling or on-demand) to avoid partition-level bottlenecks and capacity-based throttling.