DEA-C01 Question 135
Select 2You are designing a distributed data processing solution on AWS to process vast amounts of data from IoT devices in near real-time. The solution should scale automatically based on the incoming data volume and provide fault tolerance. Which combination of services would best address these requirements?
- A
Amazon Kinesis Data Streams and AWS Lambda
- B
Amazon EMR with Auto Scaling enabled
- C
Amazon RDS with Multi-AZ deployments
- D
Amazon S3 and AWS Glue
- E
Amazon DynamoDB with On-Demand mode
Show answer and explanation
Correct answers: A, B
Explanation
The combination of Amazon Kinesis Data Streams and AWS Lambda is well-suited for real-time distributed data processing, as both services scale automatically and provide fault tolerance. Amazon EMR with Auto Scaling enabled is another great choice for distributed computing, particularly for batch or near real-time processing of large data sets using frameworks like Apache Spark or Hadoop. Together, these solutions address the requirements of scalability, fault tolerance, and distributed computing effectively.
- A. Correct.
Amazon Kinesis Data Streams and AWS Lambda work well for real-time data ingestion and processing in a distributed and scalable manner. Kinesis can handle high throughput, and Lambda scales automatically to process the incoming data.
- B. Correct.
Amazon EMR with Auto Scaling enabled is ideal for distributed data processing at scale. It supports fault-tolerant, distributed frameworks like Apache Spark and Hadoop, and Auto Scaling allows the cluster to adjust resources based on workload demands.
- C. Incorrect.
Amazon RDS with Multi-AZ deployments provides high availability and fault tolerance for relational databases but is not suitable for distributed data processing or real-time data ingestion at scale.
- D. Incorrect.
Amazon S3 and AWS Glue are useful for batch processing and ETL operations but are not designed for real-time distributed data processing or automatic scaling based on workload.
- E. Incorrect.
Amazon DynamoDB with On-Demand mode is a scalable and fault-tolerant database solution but is not designed for distributed computing or real-time data processing.