Azure Stack Edge
An Azure managed appliance that brings the compute, storage, and intelligence of Azure to the edge
An edge-computing appliance managed by Azure
Azure Stack Edge, previously Azure Data Box Edge, brings the compute power, storage, and intelligence of Azure right to where you need it—whether that’s your corporate data center, your branch office, or your remote field asset.
Hardware-accelerated machine learning using FPGA or GPU*
Edge compute using containers or VMs,* all managed from the cloud and on a single appliance or across a Kubernetes cluster of appliances*
An Azure-managed appliance from order to operations, just like any other Azure service
Cloud-storage gateway for transferring data to Azure over the network while retaining local access to blobs and files
Run machine learning models close to the data source
Get rapid insights from your local data with an edge-computing appliance that offers hardware-accelerated machine learning (ML) capabilities via FPGA or GPU.* Analyze video feeds, sensor data from machinery, and more. Use the best of the cloud and the edge together. Build and train ML models in Azure, run them on the edge, and then upload data to the cloud to retrain and improve your models.
Use edge computing to address your workload needs
Speed up time to results by processing data close to its source without adding latency from a round-trip to the cloud. Run containers to analyze, transform, and filter data at edge locations or in datacenters. Use the Azure IoT Edge platform to provision and manage containers. Azure Stack Edge will also support virtual machines (VMs)* and Kubernetes clusters* so that you have a single platform to run most of your edge-compute workloads.
Manage your edge appliance in the Azure portal
Order your appliance from the Azure portal and pay as you go, just like any other Azure service. Use the same Azure portal, access credentials, and development tools across your cloud and edge environments. Configure, monitor, patch, and update the appliance from the Azure portal.
Transfer data to Azure over the network
Perform high-speed, secure transfers to and from Azure while retaining local access to files using Azure Stack Edge as your cloud storage gateway. Use its local cache capability and bandwidth throttling to limit usage during peak business hours, and optimize your transfers to Azure when bandwidth is limited.
Choose the appliance best suited for the job
Tailored for most commercial scenarios, such as retail stores and datacenters.
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, analyze 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 don’t.
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’re 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’re sending back to the cloud doesn’t violate any compliance regulations by using ML models to help alert you to potentially sensitive data and take action locally.
Azure Stack Edge pricing
- No upfront cost
- No termination fees
- Pay only for what you use
Get started with Azure Stack Edge
What our customers are saying
Olympus, a leader in medical technology solutions, uses Azure Stack Edge to pre-scan medical operating rooms in hospitals and clinics for proper equipment, inventory, and personnel.
Cree, an innovator in power and radio frequency semiconductors, uses Azure Stack Edge to meet the storage needs of its rapidly expanding manufacturing processes.