Question

Difficulty: EasyCost-Optimized Database Design and Capacity Planning

An application experiences sudden, highly unpredictable spikes in database write traffic during marketing events, followed by long periods of complete inactivity. Which Amazon DynamoDB capacity configuration is the most cost-effective for this workload?

  1. DynamoDB in On-Demand capacity modeAnswer
  2. B
    DynamoDB in Provisioned capacity mode with Auto Scaling
  3. C
    DynamoDB in Provisioned capacity mode with fixed capacity scaled for peak demand
  4. D
    DynamoDB in Provisioned capacity mode utilizing Multi-AZ replica instances for write scaling

Answer

DynamoDB in On-Demand capacity mode is the most cost-effective option for unpredictable, spiky workloads with idle periods because it scales instantly and charges only for actual read and write requests.
DynamoDB in On-Demand capacity mode is designed for workloads with highly unpredictable traffic patterns and periods of inactivity. It automatically manages capacity and instantly scales to meet demand without requiring manual configuration or auto-scaling policies. Because it charges only for the read and write request units actually consumed, it eliminates costs during idle periods, making it the most cost-effective choice.

Step-by-Step Solution

1
Analyze the workload characteristics
The workload has sudden, highly unpredictable write spikes and long periods of complete inactivity.
Understanding the traffic pattern helps select the right capacity planning strategy.
2
Compare DynamoDB capacity modes for cost and responsiveness
On-Demand mode scales instantly to handle spikes and charges 00 when idle. Provisioned capacity requires setting minimum throughput, which incurs continuous costs even when idle, and standard auto-scaling takes time to scale up, causing potential throttling during sudden spikes.
Comparing how each capacity mode handles unpredictable spikes and idle times reveals the most cost-effective choice.

Key Concept

Choosing between Provisioned and On-Demand capacity modes in DynamoDB to optimize costs based on workload predictability.
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