AWS Certified Solutions Architect - Associate
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A company needs to configure a real-time data ingestion architecture for its application. The company needs an API, a process that transforms data as the data is streamed, and a storage solution for the data.
Which solution will meet these requirements with the LEAST operational overhead?
Other
Community
UAnonymous
A
Deploy an Amazon EC2 instance to host an API that sends data to an Amazon Kinesis data stream. Create an Amazon Kinesis Data Firehose delivery stream that uses the Kinesis data stream as a data source. Use AWS Lambda functions to transform the data. Use the Kinesis Data Firehose delivery stream to send the data to Amazon S3.
B
Deploy an Amazon EC2 instance to host an API that sends data to AWS Glue. Stop source/destination checking on the EC2 instance. Use AWS Glue to transform the data and to send the data to Amazon S3.
C
Configure an Amazon API Gateway API to send data to an Amazon Kinesis data stream. Create an Amazon Kinesis Data Firehose delivery stream that uses the Kinesis data stream as a data source. Use AWS Lambda functions to transform the data. Use the Kinesis Data Firehose delivery stream to send the data to Amazon S3.
D
Configure an Amazon API Gateway API to send data to AWS Glue. Use AWS Lambda functions to transform the data. Use AWS Glue to send the data to Amazon S3.
Explanation:
Explanation
Correct Answer: C
This solution provides the least operational overhead because:
- Amazon API Gateway is a fully managed service that eliminates the need to provision, scale, or maintain EC2 instances for hosting APIs.
- Amazon Kinesis Data Streams and Kinesis Data Firehose are fully managed services for real-time data streaming and delivery.
- AWS Lambda provides serverless compute for data transformation without managing servers.
- Amazon S3 is a fully managed object storage service.
Why other options are not optimal:
- Option A: Uses EC2 instances for hosting the API, which requires operational overhead for provisioning, patching, scaling, and maintenance.
- Option B: Uses EC2 instances and AWS Glue (which is primarily a batch ETL service, not ideal for real-time streaming). Stopping source/destination checking on EC2 is a network configuration that adds complexity.
- Option D: Uses AWS Glue for real-time data ingestion, which is not its primary use case. AWS Glue is better suited for batch ETL jobs rather than real-time streaming.
Key AWS Services for Real-time Data Ingestion:
- API Gateway: Managed API service
- Kinesis Data Streams: Real-time data streaming
- Kinesis Data Firehose: Automatically loads streaming data into destinations
- Lambda: Serverless compute for transformations
- S3: Data storage
This architecture is fully serverless and managed, minimizing operational overhead while meeting all requirements for real-time data ingestion, transformation, and storage.
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