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Zorluk: OrtaPerformance and Scalability Optimization

An advertising technology company is deploying a real-time bidding analytics platform. The platform must process device telemetry and bid requests. The system handles a baseline load of 5,0005,000 requests per second, but during live sporting events, traffic instantly spikes to 150,000150,000 requests per second. The application is hosted on Amazon EC2 instances behind an Application Load Balancer (ALB). The backend is an Amazon RDS PostgreSQL database. During recent spikes, the platform experienced dropped requests at the load balancer level, and read query latency on the database spiked, causing performance degradation.

Which of the following combinations of actions should a Solutions Architect recommend to optimize the performance and scalability of the platform? (Select TWO.)

  1. Deploy a Network Load Balancer (NLB) in front of the EC2 instances to handle the sudden, massive spikes in traffic without the need for load balancer pre-warming.Cevap
  2. Migrate the database to Amazon Aurora PostgreSQL, and configure Aurora Auto Scaling to dynamically scale Aurora Replicas based on reader CPU utilization.Cevap
  3. C
    Configure the existing RDS PostgreSQL Multi-AZ standby instance to serve read queries during peak traffic hours to reduce the load on the primary DB instance.
  4. D
    Rely on the Application Load Balancer's default auto-scaling capabilities to automatically scale out to handle the instant 3030-fold traffic spike.
  5. E
    Deploy an Amazon ElastiCache for Memcached cluster to cache common read queries, and configure multi-region replication to scale caching layer throughput.

Cevap

The correct actions are deploying a Network Load Balancer (NLB) to handle the instant, massive traffic spikes without requiring pre-warming, and migrating the database to Amazon Aurora PostgreSQL to utilize Aurora Auto Scaling for reader replicas.
To handle sudden, massive spikes in traffic that scale instantly, a Network Load Balancer (NLB) is highly suitable as it can handle millions of requests per second without requiring pre-warming. Additionally, migrating the backend database to Amazon Aurora PostgreSQL allows the use of Aurora Replicas and Aurora Auto Scaling, which can dynamically scale reader nodes to handle read query spikes, offloading traffic from the primary writer node.

Adım Adım Çözüm

1
Analyze the load balancer scaling characteristics.
Determine that the Application Load Balancer cannot scale fast enough to absorb the instant 3030-fold increase from 5,0005,000 to 150,000150,000 requests per second, requiring a Network Load Balancer to handle the spike without pre-warming.
To prevent request drops during sudden spikes, the load balancing tier must be capable of handling rapid throughput changes instantly.
2
Evaluate database scaling patterns.
Identify that the primary PostgreSQL instance is saturated by read query spikes, and that standard RDS Multi-AZ standbys cannot serve read traffic.
To scale read operations, the architecture must implement a technology that supports dynamic horizontal scaling of read endpoints.
3
Select the optimal database and caching architecture.
Choose to migrate to Amazon Aurora PostgreSQL and configure Aurora Auto Scaling for reader replicas.
Aurora Auto Scaling dynamically adjusts reader replicas based on CPU demand, resolving the database read query latency issue.

Anahtar Kavram

Handling sudden, extreme traffic spikes at the load balancer and database layers using Network Load Balancers and Aurora Auto Scaling.
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Konular

Performance and Scalability Optimization

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