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Zorluk: KolayCost-Optimized Database Design and Capacity Planning

A company is migrating a database workload to AWS. The database experiences sudden, unpredictable spikes in traffic that last for only a few minutes, followed by long periods of idle time. The solutions architect needs to select a database capacity strategy that prevents application throttling while minimizing costs for idle resources. Which configuration meets these requirements most cost-effectively?

  1. Amazon DynamoDB configured with On-Demand capacity modeCevap
  2. B
    Amazon DynamoDB configured with Provisioned capacity mode and a high constant throughput limit
  3. C
    Amazon DynamoDB configured with Provisioned capacity mode and Application Auto Scaling
  4. D
    Amazon RDS Multi-AZ deployment utilizing Read Replicas as the primary disaster recovery failover target to handle the write spikes

Cevap

Amazon DynamoDB configured with On-Demand capacity mode
The configuration utilizing Amazon DynamoDB configured with On-Demand capacity mode is correct. On-demand capacity mode is ideal for highly unpredictable or spiky workloads because it instantly accommodates the traffic peaks and charges only for the reads and writes performed, avoiding costs during idle hours.

Adım Adım Çözüm

1
Analyze the workload characteristics
The workload is characterized by sudden, unpredictable traffic spikes lasting a few minutes, followed by long periods of inactivity.
Identifying the traffic pattern determines whether provisioned or on-demand capacity is more cost-effective.
2
Evaluate DynamoDB capacity modes against the workload profile
Provisioned capacity mode with auto scaling is too slow to adapt to instantaneous multi-minute spikes. Constant high provisioning wastes money during idle hours. On-Demand capacity mode scales instantly and bills only for active read/write requests.
Matching the resource scaling characteristics to the speed and frequency of traffic spikes ensures optimal cost and performance.

Anahtar Kavram

Selecting between DynamoDB On-Demand and Provisioned capacity modes based on workload predictability and spikiness to optimize costs.
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Cost-Optimized Database Design and Capacity Planning