DVA-C02 Development with AWS Services Practice Question
A developer is designing a serverless application that uses Amazon API Gateway and AWS Lambda. The application needs to handle a sudden spike in traffic. The Lambda function performs CPU-intensive operations. What should the developer do to ensure the application scales without errors?
⚠ Common exam trap
Many candidates confuse API Gateway throttling (which controls request rate at the API level) with Lambda concurrency management, leading them to pick Option A, when the real bottleneck is Lambda's concurrency limits and cold starts for CPU-intensive functions.
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 the Lambda function with reserved concurrency and provisioned concurrency.
Reserved concurrency guarantees that the Lambda function has a dedicated pool of concurrency available to handle traffic spikes without being throttled by other functions in the account, while provisioned concurrency pre-warms execution environments to eliminate cold starts for CPU-intensive operations. This combination ensures that the application scales smoothly under sudden load without encountering Lambda throttling errors (HTTP 429) or latency spikes from cold starts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set the API Gateway throttling limits to a high value.
Why it's wrong here
Setting API Gateway throttling limits to a high value only controls the maximum number of requests allowed to pass through to the backend Lambda function per second. While it prevents API Gateway from rejecting requests, it does not address the underlying Lambda function's ability to scale quickly or mitigate cold starts. If the Lambda cannot handle the increased throughput, requests will still fail due to Lambda errors or timeouts, not because of API Gateway throttling.
- ✗
Use an Amazon SQS queue to buffer requests before processing.
Why it's wrong here
Using an Amazon SQS queue to buffer requests before processing is an excellent strategy for decoupling components and handling asynchronous workloads, improving system resilience against traffic spikes. However, SQS only queues requests; it does not pre-warm Lambda execution environments or accelerate their startup time. Each message consumed from the queue will still trigger a Lambda invocation, which will incur a cold start if a pre-initialized environment is not available.
- ✓
Configure the Lambda function with reserved concurrency and provisioned concurrency.
Why this is correct
Configuring a Lambda function with reserved concurrency guarantees a specific number of concurrent executions are always available for that function, preventing other functions from consuming its capacity and ensuring it can scale. Provisioned concurrency goes further by pre-initializing a specified number of execution environments, ensuring that invocations within this limit experience significantly reduced latency by eliminating cold starts. Together, these settings provide dedicated capacity and optimize startup performance.
- ✗
Increase the Lambda function timeout to the maximum value.
Why it's wrong here
Increasing the Lambda function timeout to its maximum value only dictates the longest duration a single invocation is allowed to run before AWS Lambda terminates it. This setting does not influence how quickly new Lambda execution environments are provisioned or whether existing environments are pre-warmed. A longer timeout might prevent premature termination of long-running tasks but offers no benefit for improving the function's scaling speed or mitigating cold start latency for new requests.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DVA-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DVA-C02 exam.