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Stream Analytics with Microsoft Azure

You're reading from   Stream Analytics with Microsoft Azure Real-time data processing for quick insights using Azure Stream Analytics

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781788395908
Length 322 pages
Edition 1st Edition
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Authors (4):
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Krishnaswamy Venkataraman Krishnaswamy Venkataraman
Author Profile Icon Krishnaswamy Venkataraman
Krishnaswamy Venkataraman
Ryan Murphy Ryan Murphy
Author Profile Icon Ryan Murphy
Ryan Murphy
Manpreet Singh Manpreet Singh
Author Profile Icon Manpreet Singh
Manpreet Singh
Anindita Basak Anindita Basak
Author Profile Icon Anindita Basak
Anindita Basak
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Toc

Table of Contents (12) Chapters Close

Preface 1. Introducing Stream Processing and Real-Time Insights FREE CHAPTER 2. Introducing Azure Stream Analytics and Key Advantages 3. Designing Real-Time Streaming Pipelines 4. Developing Real-Time Event Processing with Azure Streaming 5. Building Using Stream Analytics Query Language 6. How to achieve Seamless Scalability with Automation 7. Integration of Microsoft Business Intelligence and Big Data 8. Designing and Managing Stream Analytics Jobs 9. Optimizing Intelligence in Azure Streaming 10. Understanding Stream Analytics Job Monitoring 11. Use Cases for Real-World Data Streaming Architectures

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...

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