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Zorluk: OrtaPerformance and Scalability Optimization

A media streaming service is preparing to broadcast a high-profile live sporting event. The application is deployed behind an Application Load Balancer (ALB) and uses Amazon Aurora MySQL for user profile and authorization metadata. Historical data shows that traffic will spike from 5,0005,000 requests per second to over 250,000250,000 requests per second in the first 55 minutes of the broadcast. The workload is highly read-intensive, with a 95:595:5 read-to-write ratio. Which combination of actions should a solutions architect recommend to ensure the platform handles the peak flash traffic with minimal latency and no dropped connections?

  1. Request AWS Support to pre-warm the ALB to handle the expected load, and deploy Amazon ElastiCache for Redis with replica nodes to cache metadata queries using a cache-aside pattern.Cevap
  2. B
    Rely on the ALB's automatic scaling to dynamically handle the load, and configure Aurora Auto Scaling with Target Tracking policies on CPU utilization to scale reader instances.
  3. C
    Request AWS Support to pre-warm the ALB, and configure an Amazon RDS Multi-AZ deployment with a standby instance to automatically scale and handle the increased read query load.
  4. D
    Request AWS Support to pre-warm the ALB, and deploy an Amazon ElastiCache for Memcached cluster to act as a persistent database cache, using multi-AZ replication to guarantee high availability of the cache data.

Cevap

Request AWS Support to pre-warm the ALB to handle the expected load, and deploy Amazon ElastiCache for Redis with replica nodes to cache metadata queries using a cache-aside pattern.
The correct architecture requires requesting AWS Support to pre-warm the Application Load Balancer to ensure it has enough capacity ready to handle the immediate 250,000250,000 requests per second without dropping packets. Furthermore, implementing Amazon ElastiCache for Redis with replica nodes provides a highly available, sub-millisecond caching layer that handles the 95%95\% read workload, preventing database exhaustion.

Adım Adım Çözüm

1
Analyze the rate of the traffic spike.
The traffic increases 5050-fold (from 5,0005,000 to 250,000250,000 requests per second) in 55 minutes.
This extremely rapid rate of scaling exceeds the capabilities of standard ALB auto-scaling, which requires pre-warming by AWS Support to avoid dropped connections.
2
Determine database scaling requirements.
Identify that the database workload is 95%95\% reads, meaning caching is highly effective.
Offloading reads to a caching tier reduces the load on the Amazon Aurora primary cluster and provides sub-millisecond latencies.
3
Select the appropriate caching technology.
Choose Amazon ElastiCache for Redis over Memcached.
ElastiCache for Redis supports replication, multi-AZ failover, and persistence, ensuring the caching tier remains highly available during the live event.

Anahtar Kavram

Handling rapid flash traffic spikes requires pre-warming load balancers and offloading read traffic using a highly available cache-aside pattern.
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Performance and Scalability Optimization

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