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Zorluk: OrtaHigh-Performing Database Solutions

A solutions architect is designing a database architecture for a high-frequency financial trading application. The application requires a relational database to store transactional trade execution history, demanding high availability and the ability to scale read operations dynamically from 5,0005,000 to 50,00050,000 queries per second during market opening spikes. In addition, the application must display a real-time leaderboard showing top trading accounts with microsecond read latency. Which combination of database services and configurations should the solutions architect choose to meet these requirements? (Select two.)

  1. Amazon Aurora PostgreSQL with Aurora Replicas and Auto Scaling to scale read operations dynamically during market spikes.Cevap
  2. Amazon ElastiCache for Redis to store and serve the real-time leaderboard data with microsecond read latency.Cevap
  3. C
    Amazon RDS for PostgreSQL with a cross-Region read replica configured as the primary automatic failover target for high availability.
  4. D
    Amazon DynamoDB to store the trade execution logs, utilizing a partition key based on a monotonically increasing timestamp to guarantee high write throughput.
  5. E
    Amazon DynamoDB configured with Provisioned Capacity mode to host the real-time leaderboard, managing highly unpredictable, spiky traffic without Auto Scaling.

Cevap

The correct architecture combines Amazon Aurora PostgreSQL utilizing Aurora Replicas with Auto Scaling for relational, read-scalable transaction logging, along with Amazon ElastiCache for Redis to provide microsecond read latency for the real-time leaderboard.
The correct options are the choices recommending Amazon Aurora PostgreSQL with Aurora Replicas and Auto Scaling, and Amazon ElastiCache for Redis. Amazon Aurora PostgreSQL natively supports high availability and handles read surges by dynamically adding Aurora Replicas via Auto Scaling. Amazon ElastiCache for Redis is an in-memory caching database optimized for microsecond-latency operations, which directly satisfies the leaderboard requirement.

Adım Adım Çözüm

1
Evaluate the relational database requirement for trade execution history.
Amazon Aurora PostgreSQL provides MySQL and PostgreSQL compatibility with auto-scaling Aurora Replicas, allowing read capacity to scale dynamically to meet spikes from 5,0005,000 to 50,00050,000 queries per second.
Relational constraints require a SQL-compatible engine, while high availability and spiky traffic require dynamic read replicas and automatic failover.
2
Evaluate the caching layer requirement for the real-time leaderboard.
Amazon ElastiCache for Redis supports in-memory data structures, enabling microsecond latency retrievals.
Microsecond read latency cannot be consistently achieved by standard relational databases under heavy load and requires an in-memory caching mechanism.
3
Filter out configurations that violate best practices, failover mechanics, or partitioning rules.
Eliminated options using RDS replicas for failover, monotonically increasing partition keys in DynamoDB, and provisioned capacity without auto scaling.
These options introduce performance bottlenecks, lack automatic failover mechanisms, or result in scaling failures under spiky workloads.

Anahtar Kavram

Combining Amazon Aurora Auto Scaling Replicas for scalable relational reads and Amazon ElastiCache for microsecond caching performance.
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