Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Distributed AI represents a computing approach that eliminates the necessity of transferring large data sets, enabling data analysis directly at its origin. Developed by IBM Research, the Distributed AI APIs consist of a suite of RESTful web services equipped with data and AI algorithms tailored for AI applications in hybrid cloud, edge, and distributed computing scenarios. Each API within the Distributed AI framework tackles the unique challenges associated with deploying AI technologies in such environments. Notably, these APIs do not concentrate on fundamental aspects of establishing and implementing AI workflows, such as model training or serving. Instead, developers can utilize their preferred open-source libraries like TensorFlow or PyTorch for these tasks. Afterward, you can encapsulate your application, which includes the entire AI pipeline, into containers for deployment at various distributed sites. Additionally, leveraging container orchestration tools like Kubernetes or OpenShift can greatly enhance the automation of the deployment process, ensuring efficiency and scalability in managing distributed AI applications. This innovative approach ultimately streamlines the integration of AI into diverse infrastructures, fostering smarter solutions.

Description

Flannel serves as a specialized virtual networking layer tailored for containers. In the context of the OpenShift Container Platform, it can be utilized for container networking as an alternative to the standard software-defined networking (SDN) components. This approach is particularly advantageous when deploying OpenShift within a cloud environment that also employs SDN solutions, like OpenStack, allowing for the avoidance of double packet encapsulation across both systems. Each flanneld agent transmits this information to a centralized etcd store, enabling other agents on different hosts to effectively route packets to various containers within the flannel network. Additionally, the accompanying diagram showcases the architecture and the data flow involved in facilitating communication between containers over a flannel network. This setup enhances overall network efficiency and simplifies container management in complex environments.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Red Hat OpenShift
Kubernetes
Mirantis Kubernetes Engine
OpenStack
PyTorch
TensorFlow

Integrations

Red Hat OpenShift
Kubernetes
Mirantis Kubernetes Engine
OpenStack
PyTorch
TensorFlow

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

IBM

Country

United States

Website

developer.ibm.com/apis/catalog/edgeai--distributed-ai-apis/Introduction/

Vendor Details

Company Name

Red Hat

Founded

1993

Country

United States

Website

docs.openshift.com/container-platform/3.4/architecture/additional_concepts/flannel.html

Product Features

Alternatives

DeepSpeed Reviews

DeepSpeed

Microsoft
Contrail Networking Reviews

Contrail Networking

Juniper Networks
AWS Neuron Reviews

AWS Neuron

Amazon Web Services