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Difficulty: MediumPerformance and Scalability Optimization

A global sports streaming service plans to launch a real-time commentary portal for a major tournament finals. The portal will experience a predictable but sudden increase in read traffic, surging from a baseline of 2,0002,000 requests per minute to over 1,500,0001,500,000 requests per minute in less than ten minutes. The backend application runs on Amazon ECS using AWS Fargate, and reads from an Amazon Aurora PostgreSQL database. High performance, sub-second latency, and zero dropped requests are critical requirements during the tournament. Which architecture design optimization should a solutions architect recommend to ensure the system scales efficiently under this load?

  1. Deploy Amazon ElastiCache for Redis to cache database queries, and contact AWS Support to pre-warm the Application Load Balancer (ALB) before the tournament begins.Answer
  2. B
    Configure Amazon Aurora replicas with Auto Scaling to handle the read queries, and rely on the Application Load Balancer (ALB) default auto-scaling to absorb the rapid traffic surge.
  3. C
    Enable Multi-AZ deployment for the Amazon Aurora database, and direct read traffic to the standby DB instance during peak traffic hours.
  4. D
    Configure an Application Load Balancer (ALB) with an ECS Auto Scaling policy that has a scaling cooldown period of 15 seconds to ensure rapid container deployment.

Answer

Deploy Amazon ElastiCache for Redis to cache database queries, and contact AWS Support to pre-warm the Application Load Balancer (ALB) before the tournament begins.
The correct answer combines caching with database query offloading and load balancer pre-warming. Deploying Amazon ElastiCache for Redis offloads high-volume read traffic from the Aurora database, keeping latency sub-second. Requesting ALB pre-warming from AWS Support prepares the load balancer to handle the sudden burst of 1,500,0001,500,000 requests per minute immediately, ensuring zero dropped requests.

Step-by-Step Solution

1
Analyze the load profile and traffic requirements.
Identify that the system experiences a massive, instantaneous read traffic spike (2,0002,000 to 1,500,0001,500,000 requests per minute).
This establishes that default elastic scaling of the Application Load Balancer is insufficient and database queries must be cached to prevent bottlenecking.
2
Select the appropriate caching strategy for database reads.
Introduce Amazon ElastiCache for Redis to offload the read traffic from Amazon Aurora.
Caching read results at the database tier ensures sub-second latency and keeps database CPU usage within bounds.
3
Address the sudden traffic burst handling at the load balancer tier.
Request ALB pre-warming from AWS Support prior to the event.
ALB pre-warming configures the load balancer to handle the anticipated spike without dropping initial packets while waiting for auto-scaling to trigger.

Key Concept

Handling sudden, massive traffic bursts (flash traffic) requires pre-provisioning or pre-warming load balancers and implementing caching strategies like Amazon ElastiCache to offload reads from database engines.
Estimated Time:2m 0s
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Topics

Performance and Scalability Optimization

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