SAP-C02 Design for New Solutions Practice Question
A company is building a serverless application using AWS Lambda and Amazon DynamoDB. They need to ensure that the application can handle a sudden increase in traffic without losing any data or causing errors. Which THREE strategies should they implement?
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
✓
Use DynamoDB on-demand capacity mode.
To handle sudden traffic spikes without data loss or errors, the company should: Option A (DynamoDB on-demand capacity) automatically scales to handle unpredictable throughput; Option C (DynamoDB auto scaling) adjusts provisioned capacity based on demand; Option E (Lambda reserved concurrency) ensures a baseline of concurrent executions to prevent throttling. Option B (SQS) adds decoupling but is not strictly necessary for this requirement and can introduce latency; Option D (DAX) improves read performance but does not address write scaling or throughput spikes for write-intensive loads.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use DynamoDB on-demand capacity mode.
Why this is correct
On-demand handles unpredictable traffic without capacity planning.
- ✗
Decouple the application with Amazon SQS.
Why it's wrong here
SQS decouples but does not directly handle DynamoDB throttling or Lambda concurrency.
- ✓
Enable DynamoDB auto scaling.
Why this is correct
Auto scaling adjusts throughput based on traffic.
- ✗
Use DynamoDB Accelerator (DAX) for caching.
Why it's wrong here
DAX improves read performance but not write scaling or data loss prevention.
- ✓
Configure Lambda reserved concurrency.
Why this is correct
Reserved concurrency ensures the function has capacity.
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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Same concept, more angles
2 more ways this is tested on SAP-C02
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company is building a serverless application using AWS Lambda, Amazon API Gateway, and Amazon DynamoDB. They need to ensure that the application can handle sudden spikes in traffic without throttling. Which design should they implement?
hard- A.Use Lambda provisioned concurrency and an API Gateway usage plan.
- ✓ B.Enable DynamoDB auto scaling and configure Lambda function reserved concurrency.
- C.Configure Lambda function reserved concurrency and an API Gateway cache.
- D.Use DynamoDB Accelerator (DAX) and Lambda function reserved concurrency.
Why B: Enabling DynamoDB auto scaling automatically adjusts read/write capacity to handle traffic spikes, while configuring Lambda reserved concurrency ensures that the function has a guaranteed pool of concurrency available, preventing throttling from other functions. Option A (Lambda provisioned concurrency) reduces cold starts but does not prevent throttling; API Gateway usage plans control client access rates but do not handle backend spikes. Option C (reserved concurrency) alone prevents other functions from using concurrency but does not address DynamoDB throttling; API Gateway cache reduces read load but not write spikes. Option D (DAX) is a caching layer for DynamoDB reads, not a scaling mechanism for traffic spikes.
Variation 2. A company is designing a new cloud-native application that uses Amazon API Gateway, AWS Lambda, and Amazon DynamoDB. The application handles user authentication using Amazon Cognito User Pools. During a stress test, the team notices that some requests are failing with HTTP 503 (Service Unavailable) errors. The CloudWatch logs show that Lambda functions are being throttled, and the DynamoDB table is experiencing high write throttling. The team needs to resolve these issues while maintaining low latency. Which solution is the MOST effective?
hard- ✓ A.Set Lambda reserved concurrency to a value that covers peak load and enable DynamoDB auto scaling with a target utilization of 70%.
- B.Use Amazon SQS to buffer requests to Lambda and configure a DynamoDB Accelerator (DAX) cluster for caching.
- C.Increase the DynamoDB write capacity units to the maximum expected peak and configure Lambda provisioned concurrency.
- D.Replace AWS Lambda with Amazon ECS on Fargate and use an Application Auto Scaling target tracking policy.
Why A: Setting Lambda reserved concurrency ensures that the function always has capacity available to handle peak load without being throttled by the account-level concurrency limit, while DynamoDB auto scaling with a target utilization of 70% dynamically adjusts write capacity to match traffic patterns, preventing write throttling. This combination directly addresses both throttling issues without introducing additional latency from buffering or caching layers.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This SAP-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 SAP-C02 exam.