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.

What are the primary methods to consume data from Kinesis Data Streams?

Explain the difference between Kinesis Client Library (KCL) and Kinesis Connector Library (KCL).

How does the polling mechanism work in Kinesis Data Streams?

What are the limitations on the number of GET records API calls per shard per second?

Describe how multiple consumers affect throughput in Kinesis Data Streams.

What role does DynamoDB play in the Kinesis Client Library?

How can AWS Lambda be utilized with Kinesis Data Streams?