Project Committers detail:
Initial Committers for a project will be specified at project creation. Committers have the right to commit code to the source code management system for that project.
A Contributor may be promoted to a Committer by the project’s Committers after demonstrating a history of contributions to that project.
Candidates for the project’s Project Technical Leader will be derived from the Committers of the Project. Candidates must self nominate by marking "Y" in the Self Nominate column below by Jan. 16th. Voting will take place January 17th.
Only Committers for a project are eligible to vote for a project’s Project Technical Lead.
Please see Akraino Technical Community Document section 3.1.3 for more detailed information.
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Company
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Committer
Contact Info
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Overview
As member of Akraino's Kubernetes-Native Infrastructure family of blueprints, the Industrial Edge (IE) blueprint leverages the best-practices and tools from the Kubernetes community to declaratively manage edge computing stacks (i.e. all infrastructure, clusters, and services) at scale and with a consistent, uniform user experience.
The Industrial Edge blueprint addresses a common use case in manufacturing which is "predictive maintenance", the detection of anomalies in sensor data coming from production line servers to be able to schedule maintenance and avoid costly downtimes. Anomaly detection is based on machine learning inference on streaming sensor data.
The 3-node, highly-available factory edge clusters produced by this blueprint are manageble via a central management hub running Open Cluster Management. The management hub cluster also hosts OpenDataHub, which allows streaming data mirrored from factory edge clusters to be stored in a data lake for re-training of machine learning models and deploying updated models back to the factory sites. OpenDataHub includes Jupyter Notebooks for data scientists to analyse data and work on models.
Documentation
User Documentation for KNI Blueprints
Project Team
Member | Company | Contact | Role | Photo & Bio | |||
Frank Zdarsky | Red Hat | Committer | Edge Computing Team Lead, Emerging Technologies, Office of the CTO | ||||
| Andrew Bays | Red Hat | Committer | |||||
| Yolanda Robla | Red Hat | Yolanda Robla Mota | Committer | Red Hat NFVPE - Edge, baremetal provisioning | |||
| Ricardo Noriega | Red Hat | Ricardo Noriega De Soto | Red Hat NFVPE - CTO office Networking | Y | PTL | Principal Software Engineer, Emerging Technologies, Office of the CTO | |
| Abhinivesh Jain | Wipro | Abhinivesh Jain | Committer | Distinguished Member of Technical Staff, CTO office |
Overview
Project contributors:
Red Hat (contact: Frank Zdarsky)
Project committers:
to be identified once the proposal is accepted
Project plan:
to be developed once the proposal is accepted
Resourcing:
- will be established once the proposal is accepted
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Project Templates
Use Case Template
Attributes | Description | Informational |
|---|---|---|
Type | New | |
Industry Sector | Manufacturing, Energy | |
Business Driver | ||
Business Use Cases | ||
Business Cost - Initial Build Cost Target Objective | ||
Business Cost – Target Operational Objective | ||
Security Need | ||
Regulations | ||
Other Restrictions | ||
Additional Details |
Blueprint Template
Attributes | Description | Informational |
|---|---|---|
Type | New | |
Blueprint Family - Proposed Name | Kubernetes-Native Infrastructure for Edge (KNI-Edge) | |
Use Case | Industrial Edge (IE) | |
Blueprint - Proposed Name | Industrial Edge (IE) | |
Initial POD Cost (CAPEX) | (TBC) | |
Scale & Type | 3 servers to 1 rack; x86 servers (Xeon class) | |
Applications | IoT Cloud Platform, Analytics/AI/ML, AR/VR, ultra-low latency control | |
Power Restrictions | (TBC) | |
Infrastructure orchestration | End-to-end Service Orchestration: n/a | |
SDN | OVN | |
| SDS | Ceph | |
Workload Type | containers, VMs | |
Additional Details |
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