AWS Certified Data Analytics Specialty 2021 – Hands-On - Kinesis Consumers

The video tutorial covers various methods to consume data from Kinesis Data Streams, including the use of the Kinesis SDK, Kinesis Client Library (KCL), and AWS Lambda. It explains the classic consumer polling mechanism, the constraints on throughput and latency, and how multiple consumers affect performance. The tutorial also discusses the deprecated Kinesis Connector Library and its alternatives, such as Kinesis Firehose and AWS Lambda. Key features of KCL, like checkpointing and shard discovery, are highlighted, along with the importance of DynamoDB provisioning. Finally, the video explores AWS Lambda's capabilities for real-time data processing and notifications.

Which of the following is a classic consumer of Kinesis Data Streams?

• Kinesis SDK

• AWS S3

• AWS Glue

• Amazon RDS

What is the maximum number of GetRecords API calls allowed per shard per second in Kinesis?

• 10

• 15

• 20

• 5

What is the primary role of the Kinesis Client Library (KCL)?

• To provide data analytics

• To manage data consumption from Kinesis Data Streams

• To write data to Amazon S3

• To enhance data security

Which database is used by KCL for coordination and checkpointing?

• DynamoDB

• Amazon RDS

• Amazon Redshift

• Amazon Aurora

What has largely replaced the Kinesis Connector Library?

• AWS Glue

• Kinesis Firehose and AWS Lambda

• Amazon EMR

• AWS Step Functions

What is one of the key uses of AWS Lambda with Kinesis Data Streams?

• To perform lightweight ETL tasks

• To manage user authentication

• To create virtual machines

• To store data in Amazon S3

What is the benefit of using AWS Lambda for processing data from Kinesis?

• It ensures data encryption

• It allows real-time data processing and triggering actions

• It provides high storage capacity

• It offers advanced machine learning capabilities