MLA-C01 Question 6
Select 3You are building a machine learning pipeline to analyze real-time user activity data from a mobile application. The application generates high-velocity JSON logs, which need to be ingested, transformed, and stored in a cost-efficient manner for both batch and real-time analytics. Which combination of services should you use to meet the requirements?
- A
Amazon Kinesis Data Streams for ingesting the real-time JSON logs
- B
Amazon S3 for storing the transformed logs in a cost-efficient manner
- C
Amazon Redshift for processing and storing the raw JSON logs
- D
AWS Glue for transforming the JSON logs before storing them
- E
Amazon RDS for storing the high-velocity logs in real time
Show answer and explanation
Correct answers: A, B, D
Explanation
To meet the requirements of ingesting, transforming, and storing high-velocity real-time JSON logs, a combination of Amazon Kinesis Data Streams, AWS Glue, and Amazon S3 is ideal. Kinesis handles real-time ingestion, Glue performs transformations, and S3 provides cost-effective and durable storage. Redshift and RDS are not suitable for this use case due to their limitations with high-velocity data ingestion and transformation in real time.
- A. Correct.
Correct: Amazon Kinesis Data Streams is designed for ingesting real-time, high-velocity data streams like JSON logs. It provides a scalable solution to process streaming data.
- B. Correct.
Correct: Amazon S3 is a cost-efficient and durable storage solution. It is ideal for storing transformed data for batch analytics or archival purposes.
- C. Incorrect.
Incorrect: Amazon Redshift is a data warehouse optimized for complex queries and analytics, but it is not suited for processing and directly storing high-velocity raw JSON logs.
- D. Correct.
Correct: AWS Glue provides ETL capabilities, making it a good choice for transforming the JSON logs before storing them in the desired format.
- E. Incorrect.
Incorrect: Amazon RDS is a relational database service and is not optimized for handling high-velocity real-time data ingestion like JSON logs from a mobile application.