Data integration is complex and helps organizations combine data and business processes in hybrid data environments. The increase in volume, variety, and velocity of data has led to delays in monitoring and reacting to issues. Organizations want to reduce the risk of data integration activity failures and the impact it cause to other downstream processes. Manual approaches to monitoring data integration projects are inefficient and time consuming. As a result, organizations want to have automated processes to monitor and manage data integration projects to remove inefficiencies and catch issues before they affect the entire system. Organizations can now improve operational productivity by creating alerts on data integration events (success/failure) and proactively monitor with Azure Data Factory.
To get started, simply navigate to the Monitor tab in your data factory, select Alerts & Metrics, and then select New Alert Rule.
Select the target data factory metric for which you want to be alerted.
Then, configure the alert logic. You can specify various filters such as activity name, pipeline name, activity type, and failure type for the raised alerts. You can also specify the alert logic conditions and the evaluation criteria.
Finally, configure how you want to be alerted. Different mechanisms such email, SMS, voice, and push notifications are supported.
Creating alerts will ensure 24/7 monitoring of your data integration projects and make sure that you are notified of issues before they potentially corrupt your data or affect downstream processes. This helps your organizations to be more agile and increase confidence in your overall data integration processes. This ultimately results in increasing overall productivity in your organizations, and guarantee that you deliver on your SLAs. Learn more about creating alerts in Azure Data Factory.
Our goal is to continue adding features to improve the usability of Data Factory tools. Get started building pipelines easily and quickly using Azure Data Factory. If you have any feature requests or want to provide feedback, please visit the Azure Data Factory forum.
