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Zorluk: OrtaPerformance and Scalability Optimization

A financial technology company is launching a new mobile micro-investing application. During a high-profile marketing event, the application expects an immediate traffic spike from a baseline of 500 requests per second to over 150,000 requests per second within a three-minute window. The architecture utilizes an Application Load Balancer (ALB) that routes traffic to Amazon ECS tasks, and an Amazon Aurora MySQL database cluster. The majority of the surge traffic will consist of read-only queries fetching market tickers and user balance summaries. Which strategy should a solutions architect recommend to optimize the performance and scalability of the application during this launch?

  1. A
    Configure the Application Load Balancer with target tracking scaling policies to handle the traffic spike, scale the Amazon ECS tasks horizontally, and configure the database cluster to scale up vertically.
  2. Submit a request to AWS Support to pre-provision Application Load Balancer capacity, configure Aurora Auto Scaling to dynamically scale reader nodes to handle read queries, and implement Amazon ElastiCache (Redis OSS) to cache market tickers.Cevap
  3. C
    Submit a request to AWS Support to pre-provision Application Load Balancer capacity, route read queries directly to the primary database's Multi-AZ standby instance, and scale the ECS tasks using step scaling.
  4. D
    Submit a request to AWS Support to pre-provision Application Load Balancer capacity, configure Aurora Auto Scaling to scale reader nodes, and deploy Amazon ElastiCache for Memcached to replicate and persist session state across multiple regions.

Cevap

Submit a request to AWS Support to pre-provision Application Load Balancer capacity, configure Aurora Auto Scaling to dynamically scale reader nodes to handle read queries, and implement Amazon ElastiCache (Redis OSS) to cache market tickers.
The correct answer resolves the immediate capacity needs of the load balancer through pre-provisioning, scales database read capabilities with Aurora reader nodes, and uses Redis caching to minimize load on the database layer.

Adım Adım Çözüm

1
Analyze the load profile and timing
An immediate traffic spike from 500 to 150,000 requests per second in 3 minutes cannot be absorbed by the default warm-up rate of an Application Load Balancer.
Identifying this constraint necessitates pre-warming the load balancer via AWS Support.
2
Determine database scaling strategy for read queries
Select Aurora Auto Scaling with reader nodes to scale out read operations.
Since standard standby instances cannot serve read traffic, horizontal scaling must use Aurora Replicas.
3
Implement caching for hot query data
Use Amazon ElastiCache (Redis OSS) to cache the frequently read ticker details.
An in-memory cache offloads read pressure from the database, ensuring low-latency retrieval for repeating queries.

Anahtar Kavram

Handling rapid, large-scale traffic surges through load balancer pre-provisioning, horizontal database read-scaling, and in-memory caching.
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Performance and Scalability Optimization

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