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Zorluk: OrtaPerformance and Scalability Optimization

A financial services company runs a reporting application on AWS. The application uses an Amazon Aurora MySQL database cluster with one primary writer instance. The application workload is highly read-intensive, with a predictable 10×10\times increase in read queries during the final three days of each month. The write query volume remains low and constant. The solution must dynamically scale the read capacity to maintain query latencies under 100 ms100\text{ ms} while minimizing costs during periods of low activity.

Which database scaling strategy should a solutions architect recommend?

  1. Configure Amazon Aurora Auto Scaling to dynamically scale Aurora Replicas based on CPU utilization, and direct the application's read traffic to the Aurora reader endpoint.Cevap
  2. B
    Enable Amazon RDS Multi-AZ deployment, and configure the reporting application's queries to read directly from the standby database instance during peak periods.
  3. C
    Deploy an Application Load Balancer in front of the database cluster to distribute read queries, and request load balancer pre-warming from AWS Support three days prior to the peak.
  4. D
    Deploy an Amazon ElastiCache for Memcached cluster to cache reporting query results, and configure Multi-AZ replication to ensure persistence during failovers.

Cevap

Configure Amazon Aurora Auto Scaling to dynamically scale Aurora Replicas based on CPU utilization, and direct the application's read traffic to the Aurora reader endpoint.
The correct strategy leverages Amazon Aurora Auto Scaling to dynamically provision Aurora Replicas as read load increases. Aurora Replicas share the same storage volume as the primary instance, meaning scaling operations are fast and do not duplicate storage. Directing read traffic to the reader endpoint automatically load balances queries across all active replica instances.

Adım Adım Çözüm

1
Analyze the scaling demands of the reporting application database tier.
Identified a recurring, predictable 10×10\times increase in read queries at the end of the month, with low and constant write traffic.
This establishes that only the read tier needs dynamic horizontal scaling, while the write tier remains stable.
2
Select the appropriate scaling mechanism for read capacity in Amazon Aurora.
Aurora Replicas are chosen because they share the underlying cluster volume, have minimal replication lag, and can be scaled horizontally up to 1515 replicas using Aurora Auto Scaling.
Aurora Auto Scaling dynamically adjusts the replica count based on CPU utilization or connection count metrics, maintaining performance during spikes and lowering costs when idle.
3
Determine the routing mechanism for database read queries.
The application's read queries are directed to the Aurora reader endpoint.
The reader endpoint automatically load balances connections across all active Aurora Replicas in the cluster.

Anahtar Kavram

Horizontal Read Scaling with Amazon Aurora Replicas and Auto Scaling
Tahmini Süre:2m 0s
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Performance and Scalability Optimization

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