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Home/Platform/GPU MicroCloud
Platform

GPU MicroCloud

We stand up a full private cloud on your floor: racks of edge GPUs and servers, software-defined storage, a 10G fabric and a Kubernetes control plane — all on-prem. Workloads are scheduled and bin-packed across the pool, MIG carves each GPU into isolated slices, zero-trust policy gates every call, and every minute is metered for chargeback. Datacenter discipline, where your data lives.

Kubernetes
cloud-native, on-prem
MIG
hard isolation
metered
per-tenant chargeback
01 — What it does

Your GPUs, run like cloud

/schedule

Fair-share scheduling

A priority-and-quota scheduler places jobs across the pool, preempts politely, and keeps expensive silicon busy.

queuequotapreempt
/isolate

Hard multi-tenant isolation

MIG partitioning carves each GPU into isolated slices, so tenants share hardware without sharing blast radius.

MIGcgroupssecure
/meter

Metering & chargeback

Per-tenant, per-job accounting turns shared capacity into auditable cost and showback reports.

meteringshowbackreports
02 — How it works

Pool to bill

01

Pool

Aggregate edge GPUs.

02

Schedule

Place workloads.

03

Isolate

Partition tenants.

04

Meter

Account & bill.

Distributed by design

Many nodes, one intelligence.

GPU nodes pool as one mesh — scheduled, partitioned and sharing state through a control plane. Workloads land anywhere; the cloud behaves as one.

ControlGPU node
03 — Architecture

Inside the micro-cloud

/compute

Heterogeneous compute pool

Edge GPUs, CPU servers and training boxes are pooled as one schedulable fabric — production racks plus a dedicated test / stage rack.

edge GPUserversDGX
/orchestrate

Kubernetes control plane

A cloud-native control plane handles dynamic model deployment, job scheduling, capacity allocation and execution failover across namespaced dev / test / prod.

KubernetesHelmfailover
/storage

Software-defined storage

CEPH block / file / object, an S3-compatible object store and NFS / iSCSI SAN give every workload durable, shared state — no external cloud.

CEPHS3NFS/iSCSI
/partition

MIG slice fabric

Each GPU is partitioned into right-sized MIG instances and bin-packed by memory and NVLink topology — tenants share silicon, never blast radius.

MIGNVLinkbin-pack
04 — Governance

Governed like a cloud region

/zerotrust

Zero-trust by default

Policy-as-code and OAuth2 / OpenID gate every call; per-tenant namespaces and RBAC separate workloads and data end to end.

OPAOAuth2/OIDCRBAC
/observe

Deep observability

OpenTelemetry and eBPF trace every workload; metrics, logs and dashboards make utilization and cost visible in real time.

OpenTelemetryeBPFGrafana
/data

Stateful data services

Cache, queue and database services run inside the cloud beside the compute, with columnar analytics for usage and reporting.

RedisPostgreSQLClickHouse
/meter

Metering & chargeback

Per-tenant, per-job accounting turns shared capacity into auditable showback — quotas, reports and capacity planning.

meteringquotasshowback
05 — By the numbers

The fabric underneath

10G
overlay SAN + LAN
7×
MIG slices / GPU
3
namespaces · dev/test/prod
Let's build

Datacenter discipline, on-prem.

Turnkey Edge-AI — fixed time, fixed cost, full responsibility.