Book Image

Stream Analytics with Microsoft Azure

By : Ryan Murphy, Manpreet Singh
Book Image

Stream Analytics with Microsoft Azure

By: Ryan Murphy, Manpreet Singh

Overview of this book

Microsoft Azure is a very popular cloud computing service used by many organizations around the world. Its latest analytics offering, Stream Analytics, allows you to process and get actionable insights from different kinds of data in real-time. This book is your guide to understanding the basics of how Azure Stream Analytics works, and building your own analytics solution using its capabilities. You will start with understanding what Stream Analytics is, and why it is a popular choice for getting real-time insights from data. Then, you will be introduced to Azure Stream Analytics, and see how you can use the tools and functions in Azure to develop your own Streaming Analytics. Over the course of the book, you will be given comparative analytic guidance on using Azure Streaming with other Microsoft Data Platform resources such as Big Data Lambda Architecture integration for real time data analysis and differences of scenarios for architecture designing with Azure HDInsight Hadoop clusters with Storm or Stream Analytics. The book also shows you how you can manage, monitor, and scale your solution for optimal performance. By the end of this book, you will be well-versed in using Azure Stream Analytics to develop an efficient analytics solution that can work with any type of data.
Table of Contents (18 chapters)
Title Page
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Chapter 6. How to achieve Seamless Scalability with Automation

In the previous chapters, we looked into designing and developing on Azure Stream Analytics, constructing and querying real-time events from Azure Stream Analytics. This chapter we will take a detailed review of how to build, configure and deployment scalable streaming solution, improve query performance and a brief look at the deployment of Azure Stream Analytics.

Following is the list topics covered in this session:

  • Understanding parts of Stream Analytics job definitions 
  • Deployment of Azure Stream Analytics using Azure Resource Manager (ARM)
  • Vertical partitioning and horizontal partitioning to increase query performance
  • Processing Out of order and late-arriving events