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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
Yes
API Access
Has API
No
Integrations
Red Hat OpenShift
Yes
Kubernetes
Yes
Mirantis Kubernetes Engine
No
OpenStack
No
PyTorch
Yes
TensorFlow
Yes
Integrations
Red Hat OpenShift
Yes
Kubernetes
No
Mirantis Kubernetes Engine
Yes
OpenStack
Yes
PyTorch
No
TensorFlow
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
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
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
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
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