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Average Ratings 0 Ratings
Description
Develop a hybrid storage solution that seamlessly integrates with your current network-attached storage (NAS) and Azure Blob Storage. This on-premises caching appliance enhances data accessibility whether it resides in your datacenter, within Azure, or traversing a wide-area network (WAN). Comprising both software and hardware, the Microsoft Azure FXT Edge Filer offers exceptional throughput and minimal latency, designed specifically for hybrid storage environments that cater to high-performance computing (HPC) applications. Utilizing a scale-out clustering approach, it enables non-disruptive performance scaling of NAS capabilities. You can connect up to 24 FXT nodes in each cluster, allowing for an impressive expansion to millions of IOPS and several hundred GB/s speeds. When performance and scalability are critical for file-based tasks, Azure FXT Edge Filer ensures that your data remains on the quickest route to processing units. Additionally, managing your data storage becomes straightforward with Azure FXT Edge Filer, enabling you to transfer legacy data to Azure Blob Storage for easy access with minimal latency. This solution allows for a balanced approach between on-premises and cloud storage, ensuring optimal efficiency in data management while adapting to evolving business needs. Furthermore, this hybrid model supports organizations in maximizing their existing infrastructure investments while leveraging the benefits of cloud technology.
Description
Execute your workloads and gain immediate actionable insights at the source of data generation with Azure Stack Edge, which offers specialized hardware-as-a-service. You can effortlessly procure your appliance through the Azure portal, adopting a hardware-as-a-service approach that is billed monthly through your Azure subscription. Experience a fluid cloud-to-edge integration as you set up, oversee, and upgrade your Azure Stack Edge using the same management interface and development tools familiar from Azure. Deploy your containerized applications and virtual machines directly at the data creation point for optimal efficiency. Process, transform, and filter your data on the edge, transmitting only the essential information to the cloud for additional processing or storage requirements. Additionally, you can design and train machine learning models in Azure or leverage Azure Cognitive Services, utilizing the integrated NVIDIA T4 GPU or Intel VPU in the Mini R to enhance local processing speeds. This enables businesses to make data-driven decisions faster than ever, significantly improving operational effectiveness.
API Access
Has API
No
API Access
Has API
No
Integrations
Azure Marketplace
No
Azure Network Function Manager
No
Microsoft Azure
No
Integrations
Azure Marketplace
Yes
Azure Network Function Manager
Yes
Microsoft Azure
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$399 per month
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/services/fxt-edge-filer/
Vendor Details
Company Name
Microsoft
Founded
1974
Country
United States
Website
azure.microsoft.com/en-us/products/azure-stack/edge
Product Features
Product Features
Cloud Management
Access Control
No
Billing & Provisioning
No
Capacity Analytics
No
Cost Management
No
Demand Monitoring
No
Multi-Cloud Management
No
Performance Analytics
No
SLA Management
No
Supply Monitoring
No
Workflow Approval
No