Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Google Cloud Platform Reviews & Ratings
    57,138 Ratings
    Company Website
  • Files.com Reviews & Ratings
    285 Ratings
    Company Website
  • Ant Media Server Reviews & Ratings
    207 Ratings
    Company Website
  • Dragonfly Reviews & Ratings
    16 Ratings
    Company Website
  • PeerGFS Reviews & Ratings
    22 Ratings
    Company Website
  • QuantaStor Reviews & Ratings
    6 Ratings
    Company Website
  • SureSync Reviews & Ratings
    13 Ratings
    Company Website
  • Kasm Workspaces Reviews & Ratings
    125 Ratings
    Company Website
  • MongoDB Atlas Reviews & Ratings
    1,635 Ratings
    Company Website
  • Site24x7 Reviews & Ratings
    815 Ratings
    Company Website

What is Azure FXT Edge Filer?

Create a hybrid storage solution that flawlessly merges with your existing network-attached storage (NAS) and Azure Blob Storage. This local caching appliance boosts data accessibility within your data center, in Azure, or across a wide-area network (WAN). Featuring both software and hardware, the Microsoft Azure FXT Edge Filer provides outstanding throughput and low latency, making it perfect for hybrid storage systems designed to meet high-performance computing (HPC) requirements. Its scale-out clustering capability ensures continuous enhancements to NAS performance. You can connect as many as 24 FXT nodes within a single cluster, allowing for the achievement of millions of IOPS along with hundreds of GB/s of performance. When high performance and scalability are essential for file-based workloads, Azure FXT Edge Filer guarantees that your data stays on the fastest path to processing resources. Managing your storage infrastructure is simplified with Azure FXT Edge Filer, which facilitates the migration of older data to Azure Blob Storage while ensuring easy access with minimal latency. This approach promotes a balanced relationship between on-premises and cloud storage solutions. The hybrid architecture not only optimizes data management but also significantly improves operational efficiency, resulting in a more streamlined storage ecosystem that can adapt to evolving business needs. Moreover, this solution ensures that your organization can respond quickly to data demands while keeping costs in check.

What is Amazon EC2 P4 Instances?

Amazon's EC2 P4d instances are designed to deliver outstanding performance for machine learning training and high-performance computing applications within the cloud. Featuring NVIDIA A100 Tensor Core GPUs, these instances are capable of achieving impressive throughput while offering low-latency networking that supports a remarkable 400 Gbps instance networking speed. P4d instances serve as a budget-friendly option, allowing businesses to realize savings of up to 60% during the training of machine learning models and providing an average performance boost of 2.5 times for deep learning tasks when compared to previous P3 and P3dn versions. They are often utilized in large configurations known as Amazon EC2 UltraClusters, which effectively combine high-performance computing, networking, and storage capabilities. This architecture enables users to scale their operations from just a few to thousands of NVIDIA A100 GPUs, tailored to their particular project needs. A diverse group of users, such as researchers, data scientists, and software developers, can take advantage of P4d instances for a variety of machine learning tasks including natural language processing, object detection and classification, as well as recommendation systems. Additionally, these instances are well-suited for high-performance computing endeavors like drug discovery and intricate data analyses. The blend of remarkable performance and the ability to scale effectively makes P4d instances an exceptional option for addressing a wide range of computational challenges, ensuring that users can meet their evolving needs efficiently.

Media

Media

Integrations Supported

AWS Batch
AWS Deep Learning AMIs
AWS Deep Learning Containers
AWS Neuron
AWS Nitro System
AWS Trainium
Amazon EC2
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Amazon Web Services (AWS)
MXNet
PyTorch
TensorFlow

Integrations Supported

AWS Batch
AWS Deep Learning AMIs
AWS Deep Learning Containers
AWS Neuron
AWS Nitro System
AWS Trainium
Amazon EC2
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Amazon Web Services (AWS)
MXNet
PyTorch
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$11.57 per hour
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/fxt-edge-filer/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/ec2/instance-types/p4/

Categories and Features

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

HPC

Popular Alternatives

Popular Alternatives

InfiniBox Reviews & Ratings

InfiniBox

Infinidat