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Difficulty: MediumPerformance and Scalability Optimization

A financial news and analysis company hosts a portal that publishes quarterly corporate earnings reports. The application is deployed across multiple Availability Zones using an Application Load Balancer (ALB), an Auto Scaling group of Amazon EC2 instances, and an Amazon Aurora PostgreSQL database. At the exact second an earnings report is published, traffic instantly spikes from a baseline of 2,0002,000 requests per second to over 200,000200,000 requests per second. During the first 1010 minutes of these events, users experience HTTP 503503 Service Unavailable errors and significant delays in database query responses.

Which two actions should the Solutions Architect recommend to optimize the performance and scalability of the platform under these conditions?

  1. Submit a support case to AWS Support to pre-warm the Application Load Balancer (ALB) based on the anticipated traffic volume and rate of increase.Answer
  2. Configure Aurora Auto Scaling to dynamically add Aurora Replicas to the DB cluster, and update the application to route read-only queries to the cluster reader endpoint.Answer
  3. C
    Create a target tracking scaling policy for the Application Load Balancer using the ALB ActiveConnectionCount metric to scale out the load balancer instances dynamically before the surge.
  4. D
    Configure the Aurora DB cluster to run in a Multi-AZ configuration, and modify the application to distribute the reporting read queries equally between the primary writer and the Multi-AZ standby instance.
  5. E
    Deploy an Amazon ElastiCache for Memcached cluster to cache database query results, and configure multi-AZ replication to ensure cache availability during AZ failures.

Answer

Submit a support case to AWS Support to pre-warm the Application Load Balancer (ALB) based on the anticipated traffic volume, and configure Aurora Auto Scaling to dynamically add Aurora Replicas while directing read queries to the cluster reader endpoint.
The correct options target the two primary layers under pressure during the flash traffic event: the entry point (ALB) and the database. Pre-warming the ALB ensures that the load balancer can ingest the instant surge of 200,000200,000 requests per second without dropping connections. Using Aurora Auto Scaling alongside the cluster reader endpoint allows the database layer to automatically spin up additional read replicas to handle the query workload without overloading the primary writer.

Step-by-Step Solution

1
Submit a support case to AWS Support to pre-warm the ALB.
The ALB is provisioned with sufficient capacity to support the peak request rate of 200,000200,000 requests per second from the start of the event.
This prevents HTTP 503 Service Unavailable errors caused by the ALB failing to scale out rapidly enough to handle the sudden, massive surge in connections.
2
Configure Aurora Auto Scaling for the database cluster and point read-heavy queries to the reader endpoint.
The application routes read traffic to the reader endpoint, which distributes queries across dynamically scaled Aurora Replicas.
This offloads read operations from the primary writer instance, maintaining low latency for queries during peak reporting periods.

Key Concept

Handling sudden, extreme scale spikes requires pre-allocating load balancing capacity (pre-warming) and utilizing horizontal read-scaling (Aurora Replicas with Auto Scaling) rather than relying on reactive instance-level scaling.
Estimated Time:2m 0s
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Topics

Performance and Scalability Optimization

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