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Reference architecture: Real-time event processing with Microsoft Azure Stream Analytics

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The reference architecture for real-time event processing with Azure Stream Analytics provides a generic blueprint for deploying a real-time platform as a service (PaaS) stream-processing solution by using Microsoft Azure.

Summary

Traditionally, analytics solutions are based on capabilities such as ETL (extract, transform, load) and data warehousing, where data is stored before analysis. Changing requirements, including more rapidly arriving data, are pushing this existing model to the limit.

The ability to analyze data within moving streams before storage is one solution. Although this approach isn't new, it hasn't been widely adopted across industry verticals.

Microsoft Azure provides an extensive catalog of analytics technologies that can support an array of solution scenarios and requirements. Selecting which Azure services to deploy for an end-to-end solution can be a challenge, considering the breadth of offerings.

This reference describes the capabilities and interoperation of the Azure services that support an event-streaming solution. It also explains some of the scenarios in which customers can benefit from this type of approach.

Contents

  • Executive summary
  • Introduction to real-time analytics
  • Value proposition of real-time data in Azure
  • Common scenarios for real-time analytics
  • Architecture and components
    • Data sources
    • Data integration layer
    • Real-time analytics layer
    • Data storage layer
    • Presentation/consumption layer
  • Conclusion

Author: Charles Feddersen, Solution Architect, Data Insights Center of Excellence, Microsoft Corporation

Published: January 2015

Revision: 1.0

Download: Real-Time Event Processing with Microsoft Azure Stream Analytics

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