Tag: HAQM Kinesis Analytics

Nowadays, it’s common for a web server to be fronted by a global content delivery service, like HAQM CloudFront. This type of front end accelerates delivery of websites, APIs, media content, and other web assets to provide a better experience to users across the globe. The insights gained by analysis of HAQM CloudFront access logs […]

April 2024: The solution presented in this post is deprecated. Customers across the world are increasingly building innovative Internet of Things (IoT) workloads on AWS. With AWS, they can handle the constant stream of data coming from millions of new, internet-connected devices. This data can be a valuable source of information if it can be […]

Applications log a large amount of data that—when analyzed in real time—provides significant insight into your applications. Real-time log analysis can be used to ensure security compliance, troubleshoot operation events, identify application usage patterns, and much more. Ingesting and analyzing this data in real time can be accomplished by using a variety of open source […]

In this post, I show an analytics pipeline which detects anomalies in real time for a web traffic stream, using the RANDOM_CUT_FOREST function available in HAQM Kinesis Analytics.

This post introduces you to the different types of windows supported by HAQM Kinesis Analytics, the importance of time as it relates to stream data processing, and best practices for sending your SQL results to a configured destination.

This post introduces you to HAQM Kinesis Analytics, the fundamentals of writing ANSI-Standard SQL over streaming data, and works through a simple example application that continuously generates metrics over time windows.