SAP-C02 Question 147
Select 3A company is designing a new data processing solution on AWS to handle large volumes of real-time streaming data from IoT devices. The solution must ensure low-latency ingestion, support complex stream processing logic, and scale automatically based on changes in data volume. Additionally, the company requires a durable storage solution to archive the processed data for long-term analytics. Which combination of AWS services should the company use to meet these requirements?
- A
Amazon Kinesis Data Streams for data ingestion and processing
- B
AWS Lambda for real-time stream processing
- C
Amazon DynamoDB for storing the processed data
- D
Amazon S3 for archived storage of processed data
- E
Amazon SQS for buffering real-time streaming data
Show answer and explanation
Correct answers: A, B, D
Explanation
The combination of Amazon Kinesis Data Streams, AWS Lambda, and Amazon S3 provides a scalable and low-latency solution for ingesting and processing real-time streaming data. Kinesis Data Streams ensures efficient ingestion, AWS Lambda enables complex stream processing, and Amazon S3 offers durable and cost-effective long-term storage for processed data. This architecture meets the requirements for low-latency ingestion, automatic scaling, and durable storage for analytics.
- A. Correct.
Amazon Kinesis Data Streams is designed for real-time data ingestion and supports high throughput and low latency, making it ideal for ingesting data from IoT devices.
- B. Correct.
AWS Lambda is a serverless compute service that integrates well with Kinesis Data Streams to perform real-time data processing with custom logic.
- C. Incorrect.
Amazon DynamoDB is a NoSQL database that provides low-latency data access but is not the best fit for long-term archival storage or large-scale analytics.
- D. Correct.
Amazon S3 is a highly durable and cost-effective storage solution, suitable for archiving processed data for long-term analytics.
- E. Incorrect.
Amazon SQS is a message queuing service that is better suited for decoupling applications rather than handling continuous real-time streaming data ingestion.