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Difficulty: MediumOptimizing Compute and Storage Performance

A financial services company runs a high-volume trading platform on AWS. The application tier runs on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer (ALB). The database tier uses an Amazon Aurora PostgreSQL database cluster with one writer and two readers. Every morning at the market open, the platform experiences an instantaneous, massive spike in traffic. During these events, users experience HTTP 503 Service Unavailable errors and dashboard widgets fail to load or display stale data. Investigation reveals that the ALB drops connections during the initial minute of the spike before scaling, and the database reader instances experience CPU utilization near 100% with elevated replication lag. Which two actions should a Solutions Architect recommend to optimize the performance of the compute and storage layers during these spikes? (Select TWO).

  1. Enable Aurora Auto Scaling for the Aurora Replicas in the database cluster to dynamically scale horizontal read capacity based on average CPU utilization.Answer
  2. Configure an Amazon EC2 Auto Scaling warm pool to keep pre-initialized instances ready, and request AWS Support to pre-warm the Application Load Balancer prior to the scheduled market opening times.Answer
  3. C
    Enable read routing to the RDS Multi-AZ standby database instance to distribute read queries across both the active and standby nodes.
  4. D
    Adjust the Application Load Balancer target tracking scaling policy thresholds to trigger scaling earlier, relying on dynamic scaling to absorb the instantaneous traffic spikes.
  5. E
    Purchase EC2 Instance Savings Plans to cover the compute costs of the EC2 instances, AWS Fargate tasks, and AWS Lambda functions.

Answer

To resolve the performance bottlenecks, the Solutions Architect should enable Aurora Auto Scaling for the database cluster's reader instances to dynamically scale horizontal read capacity based on average CPU utilization, and configure an Amazon EC2 Auto Scaling warm pool to keep pre-initialized instances ready while requesting AWS Support to pre-warm the Application Load Balancer prior to the scheduled market opening times.
The correct recommendations are to configure Aurora Auto Scaling for the reader instances and to use EC2 warm pools combined with pre-warming the Application Load Balancer. Aurora Auto Scaling dynamically adjusts horizontal read capacity to handle high query loads and reduce replication lag. Pre-warming the Application Load Balancer ensures the load balancer has sufficient capacity to handle instantaneous traffic spikes without dropping connections, while EC2 warm pools decrease instance launch times by maintaining pre-initialized instances.

Step-by-Step Solution

1
Analyze the database performance bottleneck under read-heavy traffic.
Identify that reader instances are overloaded with high CPU utilization and replication lag is increasing.
To optimize database read performance, horizontal scaling using Aurora Auto Scaling for the Aurora Replicas is required.
2
Analyze the entry-point bottleneck for sudden, instantaneous traffic spikes.
Identify that the Application Load Balancer is dropping connections because dynamic scaling cannot keep up with flash spikes.
To handle predictable, instant surges, the ALB must be pre-warmed by AWS Support, and EC2 warm pools should be used to minimize the boot time of new application instances.

Key Concept

Scaling compute and storage layers dynamically and proactively to handle instantaneous traffic spikes and database read contention.
Estimated Time:3m 0s
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Topics

Optimizing Compute and Storage Performance