Azure Stack Edge
An Azure managed device that brings the compute, storage and intelligence of Azure to the edge
Purpose-built hardware-as-a-service with Azure Stack Edge
Run your workloads and get quick actionable insights right at the edge where data is created using purpose-built hardware-as-a-service with Azure Stack Edge.
With easy ordering and fulfilment, you can manage your device from the cloud with standard Azure management tools
With Azure loT Edge, you can deploy and manage containers from loT Hub and integrate with Azure loT solutions at the edge with rugged options using Kubernetes with multi-node and virtual machine support
Bring hardware acceleration to a diverse set of Machine Learning workloads with NVIDIA T4 Tensor Core GPU and Intel VPU
Keep a local cache of your Azure Storage account, utilising the storage gateway to automatically upload
Get started easily with hardware-as-a-service and a seamless cloud-to-edge experience
Simply order your appliance from the Azure portal in a hardware-as-a-service model, paid monthly via your Azure subscription.
Get a seamless cloud-to-edge experience where you configure, monitor and update your Azure Stack Edge with the same management portal and development tools that you have come to expect from Azure.
Run your applications at the edge close to the data
Run your containerised applications and VMs right at the edge where data is created and collected. Analyze, transform and filter data at the edge, sending only the data you need to the cloud for further processing or storage.
Analyze your data for quick actionable insights with hardware accelerated AI/ML
Build and train Machine Learning models in Azure or use Azure Cognitive service and then utilise the built-in NVIDIA T4 GPU or Intel VPU in the Mini R to accelerate the results locally. Upload the full dataset or a subset to the cloud to retrain your models and make your edge devices even smarter.
Transfer data efficiently and easily between the cloud and edge
Azure Stack Edge acts as a cloud storage gateway and enables eyes-off data transfers to Azure, while retaining local access to files. With its local cache capability and bandwidth throttling, to limit usage during peak business hours, Azure Stack Edge can be used to optimise your data transfers to Azure and back.
Choose the device best suited for the job
Azure Stack Edge Pro Series
Enterprise scale and performance for your edge workloads
Compact form factor optimised for edge and branch locations. Flexible mounting options.
- 32 vCPUs, 51 GB RAM, 720 GB
- 32 vCPUs, 102 GB RAM, 1.6 TB, 1 NVIDIA A2 GPU
- 32 vCPUs, 204 GB RAM, 2.5 TB, 2 NVIDIA A2 GPUs
All figures are customer usable capacity.
1U rack-mountable appliance, optimised for conditions inside a datacenter or branch location.
- 40 vCPUs, 102 GB RAM, 4.2 TB, 1 NVIDIA T4 GPU
- 40 vCPUs, 102 GB RAM, 4.2 TB, 2 NVIDIA T4 GPUs
All figures are customer usable capacity.
Ruggedised datacenter-grade power with a built-in NVIDIA T4 GPU, in a transportable case for remote locations.
Available options: With or without Uninterruptable Power Supply (UPS)
Azure Stack Edge Mini SeriesDesigned for edge processing on the go
Ruggedized, battery-operated device-small enough to fit into a backpack-designed for harsh environments and disconnected scenarios. Includes a built-in Intel VPU for edge processing.
Machine Learning at the edge
Azure Stack Edge helps you address latency or connectivity issues by processing data close to the source. Run Machine Learning models right at the edge locations. Transfer the data set you need, either the full data set or a subset, to Azure to retrain and continue to improve your model.
Internet of Things
Process, sort, analyse your IoT or datacenter data to determine what you can act on right away, what you need to keep and store in cloud and what you do not.
Network data transfer from the edge to the cloud
Easily and quickly transfer data to Azure for further compute or archival purposes or to expedite your cloud migration. Return the appliance to Microsoft when you are done.
Edge and remote site compute
Run applications at remote locations to speed transactions and address bandwidth constraints. Local applications can still work when your connectivity to cloud is limited.
Make sure the data you are sending back to the cloud does not violate any compliance regulations by using ML models to help alert you to potentially sensitive data and take action locally.
Azure Stack Edge and Azure AI Helping Stop Animal Trafficking
See how customers are using Azure Stack Edge
T. Michael Thornton, Vice President R&D, Customer Solutions Business, Olympus
"The on-premises nature of Azure Stack Edge and the Intel-based field-programmable gate arrays (FPGAs) make it really seamless for us to be able to integrate that device into part of our natural application."
Cengiz Balkas, SVP and General Manager, Wolfspeed
"I think an improvement of this magnitude comes roughly every 20, 30 years."
AI in edge appliances promotes Autonomous Vessel in the maritime industry
Azure Stack Edge pricing
- No upfront cost
- No termination fees
- Pay only for what you use
Connect with our technology partners
Transform your business quickly using AI/ML partner solutions which can run on Azure Stack Edge.