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 job alerts

Getting insights using job metrics and diagnostics logs is crucial for job monitoring and troubleshooting issues. However, it would take an enormous amount of human effort to keep a watch on various metrics 24/7 and raise an alarm or take immediate action in case of any issues. Hence, another important aspect of job monitoring is letting the platform do the hard work of monitoring, notifying a human, or performing a custom action when a metric reaches a critical threshold. The Azure alert experience fills this gap and provides a highly intuitive experience for setting up job alerts to take an action when a job metric reaches a predefined threshold.

Let's understand the features offered with an example. To ensure that your Stream Analytics job processes incoming events with low latency, you may want to keep an eye on the job's resource consumption. One way to accomplish this is by setting an alert on the SU% utilization metric. Apart from sending an email notification...