DVA-C02 Development with AWS Services Practice Question
A company is running a web application on EC2 instances behind an Application Load Balancer. The application experiences high latency during peak hours. A developer needs to improve performance. Which TWO actions should the developer take? (Choose TWO.)
⚠ Common exam trap
Many candidates confuse vertical scaling (larger instances) with horizontal scaling (Auto Scaling), or think that increasing timeouts or enabling EBS optimization will fix application-level latency issues.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Configure Auto Scaling to add more instances during peak hours.
Option A is correct because configuring Auto Scaling to add more instances during peak hours horizontally scales the compute capacity behind the Application Load Balancer, distributing the increased request load across more targets and directly reducing the per-instance latency caused by peak traffic. Option C is correct because implementing Amazon ElastiCache (Redis or Memcached) offloads repeated reads of frequently accessed data from the backend instances and any database, cutting response times and reducing the load that contributes to high latency during peaks. Option B is not appropriate because increasing the ALB idle timeout only affects how long idle connections are kept open and does not improve application response latency. Option D is not the best fit because vertically scaling with larger instance types is a single-instance change that does not address load distribution and is less elastic than Auto Scaling. Option E is incorrect because EBS optimization improves storage throughput/IOPS consistency for EBS-backed volumes, not the application's peak-hour latency driven by request load.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure Auto Scaling to add more instances during peak hours.
Why this is correct
Configuring Auto Scaling allows the web application to dynamically adjust its capacity by launching additional EC2 instances when demand increases, such as during peak hours. This horizontal scaling approach ensures that the application maintains responsiveness and high availability by distributing the load across more resources, effectively preventing performance degradation and latency spikes. It automatically scales out to meet demand and scales in to optimize costs.
- ✗
Increase the ALB idle timeout.
Why it's wrong here
Increasing the Application Load Balancer (ALB) idle timeout primarily extends the duration an inactive connection is kept open between the client and the load balancer, or between the load balancer and the target instance. While this can prevent premature connection closures for long-running but infrequent requests, it does not address underlying application latency issues caused by insufficient processing capacity or slow database queries during peak load. It's a connection management setting, not a performance scaling mechanism.
- ✓
Implement Amazon ElastiCache to cache frequently accessed data.
Why this is correct
Implementing Amazon ElastiCache, using engines like Redis or Memcached, significantly improves web application performance by storing frequently accessed data in a high-speed, in-memory cache. This reduces the need for repeated, slower queries to the backend database, thereby decreasing database load and dramatically lowering the latency for common data retrieval operations. Caching offloads the database, allowing it to handle more complex or less frequent requests efficiently.
- ✗
Use larger EC2 instance types.
Why it's wrong here
While using larger EC2 instance types (vertical scaling) provides more CPU, memory, and network resources to individual instances, it is generally less cost-effective and less resilient for handling fluctuating web application loads compared to horizontal scaling. A single larger instance still represents a single point of failure, and scaling up often hits diminishing returns. Auto Scaling with smaller instances offers better fault tolerance and more granular cost optimization for variable demand.
- ✗
Enable EBS optimization on the instances.
Why it's wrong here
Enabling EBS optimization provides dedicated network bandwidth between an EC2 instance and its attached Amazon EBS volumes, which is crucial for applications with high I/O requirements. However, for a typical web application experiencing general latency during peak hours, the bottleneck is more often CPU, memory, network throughput to clients, or database query performance, rather than the I/O operations to local EBS volumes. EBS optimization would not directly address these common web application performance issues.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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