DEA-C01 Question 93
Select 2You are a Data Engineer tasked with designing an event-driven architecture for a real-time log analytics platform. The platform ingests logs from multiple sources, processes them in real-time, and stores the results in Amazon S3 for further analysis. Which combination of AWS services should you use to implement this architecture?
- A
Amazon Kinesis Data Streams for log ingestion, AWS Lambda for processing, Amazon S3 for storage
- B
Amazon SQS for log ingestion, Amazon EMR for processing, Amazon DynamoDB for storage
- C
Amazon EventBridge for log ingestion, AWS Lambda for processing, Amazon RDS for storage
- D
Amazon Kinesis Data Firehose for log ingestion, AWS Lambda for processing, Amazon S3 for storage
- E
Amazon SNS for log ingestion, AWS Glue for processing, Amazon RDS for storage
Show answer and explanation
Correct answers: A, D
Explanation
In an event-driven architecture for real-time log analytics, Amazon Kinesis (Data Streams or Data Firehose) is well-suited for ingesting logs in real-time. AWS Lambda provides serverless real-time processing capabilities. Finally, Amazon S3 is a cost-effective and scalable storage solution for storing processed log analytics data. Options 1 and 4 correctly align with these requirements.
- A. Correct.
This is a valid combination. Amazon Kinesis Data Streams is designed for real-time data ingestion, AWS Lambda can process the logs in real-time, and Amazon S3 is a cost-effective storage solution for analytics.
- B. Incorrect.
This is not an optimal choice. While Amazon SQS can be used for message queuing, it is not ideal for real-time, high-throughput log ingestion. Additionally, Amazon DynamoDB is not suitable for storing large volumes of log data for analytics.
- C. Incorrect.
This is not an ideal choice. Although Amazon EventBridge can be used for event routing, it is not optimized for high-throughput log ingestion. Additionally, Amazon RDS is not cost-effective for storing large amounts of log data.
- D. Correct.
This is another valid combination. Amazon Kinesis Data Firehose can handle log ingestion and delivery to S3, AWS Lambda can process logs in real-time, and Amazon S3 serves as a scalable storage solution.
- E. Incorrect.
This is not a suitable combination. Amazon SNS is not designed for high-throughput log ingestion, AWS Glue is more suited for ETL workflows rather than real-time data processing, and Amazon RDS is not ideal for storing large-scale log data.