After careful consideration, we have decided to discontinue Amazon Kinesis Data Analytics for SQL applications:

1. From **September 1, 2025**, we won't provide any bug fixes for Amazon Kinesis Data Analytics for SQL applications because we will have limited support for it, given the upcoming discontinuation.

2. From **October 15, 2025**, you will not be able to create new Kinesis Data Analytics for SQL applications.

3. We will delete your applications starting **January 27, 2026**. You will not be able to start or operate your Amazon Kinesis Data Analytics for SQL applications. Support will no longer be available for Amazon Kinesis Data Analytics for SQL from that time. For more information, see [Amazon Kinesis Data Analytics for SQL Applications discontinuation](discontinuation.md).

# Examples: Machine Learning
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This section provides examples of Amazon Kinesis Data Analytics applications that use machine learning queries. Machine learning queries perform complex analysis on data, relying on the history of the data in the stream to find unusual patterns. The examples provide step-by-step instructions to set up and test your Kinesis Data Analytics application. 

**Topics**
+ [Example: Detecting Data Anomalies on a Stream (RANDOM\$1CUT\$1FOREST Function)](app-anomaly-detection.md)
+ [Example: Detecting Data Anomalies and Getting an Explanation (RANDOM\$1CUT\$1FOREST\$1WITH\$1EXPLANATION Function)](app-anomaly-detection-with-explanation.md)
+ [Example: Detecting Hotspots on a Stream (HOTSPOTS Function)](app-hotspots-detection.md)