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Difficulty: HardPerformance and Scalability Optimization

A company is designing a high-performance web application to support a highly anticipated, time-sensitive product release. The release event will start precisely at 15:00 UTC and is expected to attract an immediate wave of over 300,000300,000 concurrent users submitting search queries and orders. The proposed architecture consists of a stateless web tier running on Amazon EC2 instances behind an Application Load Balancer (ALB), and a database tier utilizing an Amazon Aurora MySQL database cluster. Which TWO actions should the solutions architect implement to ensure the application scales effectively and maintains sub-second latencies during the start of the event? (Select TWO.)

  1. Submit a support case to AWS to pre-warm the Application Load Balancer (ALB) with the expected traffic profile prior to the event.Answer
  2. Configure an Auto Scaling group scheduled scaling policy to pre-provision the required number of EC2 instances for the web tier before 15:00 UTC.Answer
  3. C
    Rely on the Application Load Balancer (ALB) default auto-scaling behavior to dynamically scale out the load balancer capacity as traffic spikes at 15:00 UTC.
  4. D
    Deploy a Multi-AZ DB instance deployment for the database tier and configure the web application to route read queries to the standby replica during peak traffic.
  5. E
    Deploy an Amazon ElastiCache for Memcached cluster to cache session data across multiple Availability Zones, configuring multi-AZ replication to ensure session state persistence if a cache node fails.

Answer

Submit a support case to AWS to pre-warm the Application Load Balancer (ALB) prior to the event, and configure a scheduled scaling policy on the EC2 Auto Scaling group to pre-provision compute instances before 15:00 UTC.
The correct options recommend submitting an ALB pre-warming support ticket to ensure the load balancer is sized for the immediate burst, and using scheduled scaling for the EC2 Auto Scaling group to pre-provision instances before the spike occurs. This proactive strategy ensures both the entry point and the compute layer are ready to accept the sudden volume of traffic.

Step-by-Step Solution

1
Analyze the load characteristics of the event
Determine that the traffic spike is instantaneous (starting precisely at 15:00 UTC) and massive (300,000300,000 concurrent users).
Understanding the instantaneous nature of the load indicates that dynamic scaling policies (which respond reactively) will be too slow.
2
Address load balancer scalability constraints
Formulate a request for ALB pre-warming from AWS Support to handle the immediate burst in request rates.
This prevents the ALB from dropping connection requests during the initial minutes of the event while trying to scale out reactively.
3
Address compute tier scalability constraints
Create scheduled scaling actions to spin up the required web tier instances prior to the event's start time.
Pre-provisioning instances avoids latency spikes caused by instance startup and bootstrapping time.

Key Concept

Optimizing architectures for predictable flash events requires proactive resource provisioning (scheduled scaling) and pre-warming of infrastructure layers (such as load balancers) rather than relying solely on reactive scaling mechanisms.
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Topics

Performance and Scalability Optimization

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