Examkin

Question

Difficulty: MediumPerformance and Scalability Optimization

An utility company is designing an emergency alert system. During a regional power outage, the system must immediately ingest status updates from up to 500,000500\text{,000} smart grid sensors within a 30-second30\text{-second} window. The ingestion layer consists of an Application Load Balancer (ALB) routing requests to EC2 instances, which validate the sensor's digital signature against a relational database before writing the status to the database. The database currently runs on a single Amazon RDS for PostgreSQL DB instance. Which architecture optimization strategy will meet these scalability and latency requirements under sudden load?

  1. A
    Rely on the default auto-scaling behavior of the Application Load Balancer, and deploy an Amazon RDS for PostgreSQL Read Replica to distribute the validation read queries.
  2. Pre-warm the Application Load Balancer by contacting AWS Support, migrate the database to Amazon Aurora PostgreSQL, and configure Aurora Auto Scaling for the Aurora Replicas to scale read capacity.Answer
  3. C
    Pre-warm the Application Load Balancer by contacting AWS Support, enable Multi-AZ on the RDS for PostgreSQL instance, and configure the EC2 instances to route validation read queries to the standby replica.
  4. D
    Pre-warm the Application Load Balancer by contacting AWS Support, and deploy an Amazon ElastiCache for Memcached replication group across multiple Availability Zones to cache the validation data.

Answer

Pre-warm the Application Load Balancer by contacting AWS Support, migrate the database to Amazon Aurora PostgreSQL, and configure Aurora Auto Scaling for the Aurora Replicas to scale read capacity.
The correct strategy addresses both scaling constraints. First, pre-warming the ALB ensures that the entry point can immediately handle the massive connections from 500,000 smart grid sensors. Second, migrating to Amazon Aurora PostgreSQL and utilizing Aurora Replicas with Aurora Auto Scaling allows the system to scale reads horizontally and dynamic workloads efficiently, which is optimal for validating the sensors' digital signatures during peak events.

Step-by-Step Solution

1
Address the immediate network traffic spike at the ingestion layer.
Requesting ELB pre-warming from AWS Support configures the ALB with enough capacity to handle the sudden influx of 500,000 sensor connections without triggering throttling or HTTP 503 errors.
Standard ALB auto-scaling is reactive and cannot scale instantly to absorb massive, immediate spikes in traffic.
2
Select a database engine that supports dynamic horizontal read scaling.
Migrating to Amazon Aurora PostgreSQL enables the deployment of up to 15 Aurora Replicas that share the same underlying storage volume.
Aurora PostgreSQL Replicas have minimal replication lag (typically under 100 milliseconds) and share storage, making them highly efficient for heavy read traffic scaling.
3
Configure auto-scaling for the database read tier.
Setting up Aurora Auto Scaling dynamically adds or removes Aurora Replicas based on reader CPU utilization or average connections.
This ensures the read capacity automatically adjusts to handle validation queries during emergency events and scales back down afterward to optimize cost.

Key Concept

Handling flash traffic requires pre-warming the load balancer, while scaling relational database reads horizontally requires using replicas rather than passive standby instances.
Estimated Time:2m 0s
Rate this question

Topics

Performance and Scalability Optimization

More questions from this topic