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Zorluk: OrtaPerformance and Scalability Optimization

A logistics company is launching a real-time parcel routing and verification system. The system must process coordinates and tracking updates from delivery agents. The system expects a baseline load of 2,0002,000 requests per second, which instantly surges to 45,00045,000 requests per second during shift-change windows at 08:00 and 17:00 daily. The application runs on Amazon ECS Fargate behind an Application Load Balancer. The system requires a low-latency, replication-enabled cache to store persistent session states, and writes are recorded to an Amazon Aurora PostgreSQL database. Which combination of architectural decisions will optimize the system's performance and scalability for these spikes? (Select TWO.)

  1. Request AWS Support to pre-warm the Application Load Balancer to the expected peak of 45,00045,000 requests per second before the scheduled shift-change windows.Cevap
  2. Use Amazon ElastiCache for Redis with Multi-AZ enabled to store the persistent session states.Cevap
  3. C
    Deploy Amazon ElastiCache for Memcached with multi-AZ replication enabled to store the persistent session states.
  4. D
    Rely on the Application Load Balancer's default dynamic scaling to handle the instant spike from 2,0002,000 to 45,00045,000 requests per second.
  5. E
    Configure Aurora Auto Scaling to dynamically provision additional Multi-AZ standby database instances to distribute the read query load.

Cevap

The solutions architect should request AWS Support to pre-warm the Application Load Balancer before the shift-change windows and deploy Amazon ElastiCache for Redis with Multi-AZ enabled to store the persistent session states.
To handle instantaneous spikes from 2,0002,000 to 45,00045,000 requests per second, the Application Load Balancer must be pre-warmed by AWS Support, as normal auto-scaling is too slow. Additionally, Amazon ElastiCache for Redis is the correct caching technology to store persistent session states because it supports both data persistence and Multi-AZ replication.

Adım Adım Çözüm

1
Analyze the load profile and caching requirements.
The traffic spikes instantly from 2,0002,000 to 45,00045,000 requests per second. The session store requires persistence, low-latency, and multi-AZ replication.
This establishes the constraints for load balancing scaling speed and the cache engine choice.
2
Select the appropriate caching technology.
Amazon ElastiCache for Redis is selected because Memcached does not support persistence or replication.
Ensures the cache can persist data and remain highly available across multiple Availability Zones.
3
Address the sudden traffic spike at the load balancer layer.
Requesting ELB pre-warming is selected over relying on dynamic scaling.
Standard ELB auto-scaling is too slow to handle massive, instantaneous spikes, which leads to dropped connections during the scaling delay.

Anahtar Kavram

Handling massive, instantaneous traffic spikes with ELB pre-warming and choosing the correct replication-capable caching layer.
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Performance and Scalability Optimization

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