CASE STUDIES

Sovereign infrastructure, in practice.

How data centers, service providers, and enterprises run production workloads on the Awanio platform — from VMware exits to branded public clouds.

The scenarios below are representative of typical Awanio deployments. Customer names are withheld.

sync_alt VMWARE EXIT

Regional Hosting Provider

Leaving vSphere without leaving familiar workflows behind

Challenge

A hosting provider running hundreds of VMs across multiple ESXi clusters faced steep per-core renewal costs after the VMware licensing changes. Their operations team had a decade of vCenter muscle memory and no appetite for a disruptive re-platforming project.

Solution

The provider deployed Vapor as the hypervisor layer and Cockpit for centralized management, then used Condensa with Changed Block Tracking to move workloads incrementally — replicating VMs in the background and cutting over per tenant during scheduled windows.

Vapor Cockpit Condensa

OUTCOMES

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Majority

of licensing spend eliminated after renewal exit

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Per-tenant

cutover windows instead of one big-bang migration

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Near-zero

retraining required for the ops team

dns WHITE-LABEL CLOUD

Telecom Operator

Launching a branded public cloud on sovereign infrastructure

Challenge

A telecom operator wanted to sell IaaS to enterprise customers under its own brand, with data guaranteed to stay in-country. Building a self-service portal, billing, and tenant isolation from scratch was quoted in years, not months.

Solution

Using the Cloud Enabler Platform (CEP), the operator launched a white-label cloud console on top of its own data centers — self-service VM provisioning, project-level tenant isolation, and automated billing, all running on Kubernetes with KubeVirt.

Cloud Enabler Platform

OUTCOMES

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Months

from kickoff to a sellable branded cloud

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In-country

data residency for every tenant workload

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Self-service

provisioning without ops tickets

smart_toy AI-ASSISTED OPERATIONS

Financial Services

Operating multi-cluster Kubernetes with a lean platform team

Challenge

A financial services firm ran workloads across several Kubernetes clusters with a small platform team. Routine diagnostics and capacity questions consumed engineering time, and compliance rules prevented sending cluster data to external AI services.

Solution

KudashAI gave the team a single console across all clusters with Plan-Execute-Verify AI assistance. Local LLM support kept every prompt and cluster detail inside their own network, satisfying the compliance requirement.

KudashAI

OUTCOMES

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One console

for every cluster instead of context switching

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On-premise

AI assistance with no data leaving the network

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Faster

incident diagnosis for routine cluster issues

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