SAP-C02 Design for New Solutions Practice Question
A financial services company is designing a new system on AWS to process real-time stock trades. The system must handle up to 10,000 trades per second with end-to-end latency under 500 milliseconds. Trades are ingested via REST API, validated, enriched with market data, and stored in a database for regulatory compliance. The architecture must be highly available across three Availability Zones. The company wants to use AWS managed services to minimize operational overhead. Which solution should a Solutions Architect recommend?
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 Amazon API Gateway to ingest trades, send to Amazon Kinesis Data Streams for buffering, use AWS Lambda to process in parallel, and store results in DynamoDB with on-demand capacity.
It uses Amazon API Gateway for ingestion, Kinesis Data Streams for durable buffering and scalability (handles up to 10,000 tps by adding shards), AWS Lambda for stateless validation/enrichment (auto-scales with Kinesis), and DynamoDB with on-demand capacity for low-latency storage (millisecond response). This combination provides high availability across three AZs with minimal operational overhead. Option A is wrong because managing EC2 instances and RDS Multi-AZ adds operational overhead and slower scaling compared to serverless services. Option B is wrong because SNS does not provide a persistent buffer; if the Lambda subscriber is unavailable or throttled, messages can be lost, and ordering is not guaranteed. Option C is wrong because SQS FIFO queues have a maximum throughput of 3,000 tps (with batching) or 300 tps (without), which is insufficient for 10,000 tps. Additionally, Kinesis Data Streams is better suited for real-time streaming at high throughput.
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 Network Load Balancer to distribute trade requests to a fleet of EC2 instances running a custom Java application. The application processes trades and writes to Amazon RDS for MySQL with Multi-AZ.
Why it's wrong here
EC2 instances introduce operational overhead; RDS MySQL may not meet latency requirements.
- ✗
Use Amazon API Gateway to ingest trades, publish to an SNS topic, subscribe an SQS queue and a Lambda function. Lambda validates and enriches, then stores in DynamoDB.
Why it's wrong here
SNS does not provide durable buffering; if Lambda fails, messages may be lost.
- ✗
Use Amazon API Gateway to ingest trades, send to an SQS FIFO queue for ordered processing, trigger an AWS Lambda function for validation and enrichment, and store in DynamoDB.
Why it's wrong here
SQS FIFO queues are limited to 300 transactions per second, insufficient for 10,000 tps.
- ✓
Use Amazon API Gateway to ingest trades, send to Amazon Kinesis Data Streams for buffering, use AWS Lambda to process in parallel, and store results in DynamoDB with on-demand capacity.
Why this is correct
Kinesis can handle high throughput, Lambda scales automatically, DynamoDB provides low-latency storage.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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