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Project Technical Lead:  

Project Committers detail:

Committer

Committer

Company

 Committer Contact Info

Committer Bio

Committer Picture

Self Nominate for PTL (Y/N)

Vijay Palpalc networksvijay.pal@palcnetworks.com


Vignesh Kesavanpalc networkskvignesh@palcnetworks.com


Vishwas Sharmapalc networksvishwas.sharma@palcnetworks.com


Shivashankar C Rpalc networkscshivash@palcnetworks.com


Subham Ranapalc networksrsubham@palcnetworks.com


Sarthak Sharmapalc networksssarthak@palcnetworks.com


Presentation


The following is base ppt file for above pdf.


Use Case Details

AttributesDescriptionInformational
Type

New Blueprint for Predictive Maintenance  of Hardware at the Edge


Blueprint Family - Proposed Name

AI Edge Blueprint Family


Use Case

Provide Predictive Maintenance  of Hardware ( HDD ,sensors , Optics ,interfaces ,  CPU etc) in advance before system failure


Blueprint proposed Name

Predictive Maintenance


Initial POD Cost (capex)

Leverage Unicycle POD - less than $150k


Scale & Type

Up to 100K devices

  x86/ARM server or deep edge class


Applications

Our AI based Predictive Maintenance solution has application  and usage in every aspect networks / data center’s / compute nodes /autonomous robots and cars.


Power Restrictions

Less than 10Kw


Infrastructure orchestration

Docker 1.13.1 or above and K8s 1.10.2 or above- Container Orchestration

OS - Ubuntu 22.x


SDN

-


Workload Type

Any


Additional Details

Kafka message bus and Webhook/Nginx middleware

Kubeless function management engine over Kubernetes

PMC Client with network connectivity

GUI based installer for Functions




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