Book Image

Stream Analytics with Microsoft Azure

By : Krishnaswamy Venkataraman, Anindita Basak, Ryan Murphy, Manpreet Singh
Book Image

Stream Analytics with Microsoft Azure

By: Krishnaswamy Venkataraman, Anindita Basak, 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
About the Authors
About the Reviewers
Customer Feedback

Configuring SU using Azure portal

We will now look into how to scale the SUs for a Stream Analytics job using the Azure portal step by step:

  1. Open the job that was previously created in the Azure portal. In the job blade, click the Scale option in the CONFIGURE section:
  1. Drag the SUs slide to the desired number of units, then click the Save button.
  2. To monitor how many SUs a job is using, open the job in the Azure portal.
  3. In the job blade, click the Metrics option in the Monitoring section.
  4. Under Available metrics, select SU % Utilization. You can provide a title and subtitle for the metrics chart, change the Chart type and Time range, and pin the chart to your dashboard. You can also add an alert on the metric as well, so you can receive a notification if the metric exceeds a particular threshold, as follows:

Generally, the SU % Utilization number should be at 80% or lower so that there is enough capacity to handle spikes.

  1. You can also look at the number of Input Events and Output Events to measure...