Conceptualizing the Processing Model for the AWS Kinesis Data Analytics Service

Real-time Data Processing with AWS Kinesis Data Analytics

Unlock the power of real-time data analysis with AWS Kinesis Data Analytics. This service enables you to transform and analyze streaming data as it arrives, leveraging serverless technologies and powerful frameworks like Apache Flink and SQL.

Understanding the Kinesis Streaming Platform

Kinesis Data Analytics is an integral part of the broader Kinesis streaming platform, which includes:

• Kinesis Data Streams: For ingesting and storing streaming data.
• Kinesis Data Firehose: For reliably delivering streaming data to destinations like data lakes and data warehouses.
• Kinesis Video Streams: For capturing, storing, and analyzing video streams.

Key Concepts & Runtimes

This course dives into the core of Kinesis Data Analytics, covering:

• Introduction to Kinesis Data Analytics: Learn how to process and analyze data streams effectively.
• Processing Runtimes: Explore the available runtimes for processing your data:
  • Apache Flink Runtime: A powerful distributed stream processing engine.
  • SQL Runtime: Utilize standard SQL queries for real-time data analysis.
  • Apache Beam Runtime: A unified programming model for batch and stream data processing.

Deployment & Configuration

Master the deployment process using both:

• AWS Command Line Interface (CLI): Automate application deployment with proper role and policy configuration for resource access.
• AWS Web Console: A visual interface for configuring your Kinesis Analytics application, including setting up enhanced fan-out consumers and configuring output to Kinesis Firehose delivery streams.

Advanced Techniques

Expand your skills with:

• Apache Flink Table API: Process streaming data using the Table API for efficient data manipulation.
• SQL Runtime Deep Dive: Learn to create and utilize in-application streams, and understand the role of the stream pump in data flow.

Skills & Outcomes

Upon completion, you will be able to:

• Create and deploy streaming applications on Kinesis Data Analytics.
• Connect Kinesis Data Analytics to other AWS services as both data sources and data sinks.
• Effectively process and analyze real-time data streams using Apache Flink and SQL.