Microsoft Azure SQL Edge is a very small footprint and robust IoT database product from Microsoft that runs on Lenovo Edge servers to process the data locally for increased security and reduced latency. The combination of Azure SQL Edge and Lenovo’s innovative ThinkSystem SE350 Edge Server provides the ideal Edge gateway solution for processing data aggregated from scores of IoT devices.
Azure SQL Edge is a fully containerized solution compatible with most docker container engines. It can run on any Intel, AMD, or ARM64 device and includes native support for data streaming (the same engine that powers Azure Stream Analytics). It has many security features like data encryption, classification, and access controls. Azure SQL Edge also has Time Series Processing and ML inferencing capabilities. ML Models can be trained on premises and deployed to the edge where inferencing can be done on data that is being collected.
This paper describes the steps required to set up and run Azure SQL Edge on the SE350. It also provides some performance data with Azure SQL Edge running on the SE350. The intended audience is IT professionals, solution architects, sales engineers, and consultants to assist in planning, designing, and implementing Microsoft SQL Server at the Edge. Some general knowledge about data center and edge scenarios, and about Microsoft SQL Server is expected to get the most benefit out of this paper.
Table of Contents
IOT Edge device setup
Azure SQL Edge - Azure IoT Edge method
Azure SQL Edge - Docker method
Connecting to the SQL Edge container
Add data volumes to SQL Edge container
Appendix: Bill of Materials
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Changes in the December 1, 2021 update:
- Added use case for Azure SQL Edge on ThinkSystem SE350
- Added a section on adding data volumes to SQL Edge containers