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Reference Architectures

Three VergeOS deployment models -- HCI, HCI + Dedicated Compute, and UCI -- with a decision framework, topology diagrams, and guidance for edge and CSP scenarios.

VergeOS supports three deployment architectures from the same software installation. Choosing the right one depends on node count, growth pattern, and workload specialization requirements. This page walks through each model, provides a decision framework, and covers two common real-world scenarios: edge deployments and cloud service provider (CSP) multi-tenant environments.

Architecture Decision Tree

Use the following framework to guide your recommendation. The node-count bands below are coarse rules-of-thumb: HCI fits smaller deployments (2--12 nodes typically), and UCI applies when compute and storage growth diverge or specialized hardware is needed.

Quick rules of thumb:

  1. Start with HCI unless you have a specific reason not to.

  2. Consider HCI + Compute when compute demand outpaces storage growth (6--10 nodes).

  3. Choose UCI for 10+ node environments, specialized hardware, or maximum performance isolation.

  4. You can evolve from HCI to HCI + Compute to UCI as the environment grows -- the same VergeOS installation supports all three.


Model 1: HCI (Hyperconverged Infrastructure)

Node range: 2--6 nodes | Clusters: 1

In an HCI deployment every node contributes both compute and storage. The two controller nodes carry Tier 0 (vSAN metadata) plus Tier 1 (workload) storage and run VMs. Scale-out nodes add Tier 1 storage and compute capacity to the same cluster.

Advantages

  • Operational simplicity -- single cluster, single hardware spec, unified management.

  • Predictable scaling -- every node adds both storage and compute proportionally.

  • Lowest entry point -- a 2-node cluster is the smallest VergeOS deployment possible.

  • Single hardware specification simplifies procurement and spare-parts inventory.

Limitations

  • Cannot scale compute independently of storage (or vice versa).

  • Limited hardware specialization -- all nodes share the same role.

  • Recommended maximum of approximately 6 nodes before considering a second cluster.

  • Potential resource contention on controller nodes running both metadata operations and VM workloads.

Ideal Use Cases

Scenario
Why HCI Works

Small/medium deployments (2--6 nodes)

Minimal complexity, every node pulls double duty

Balanced workloads

Storage and compute grow at roughly the same rate

Edge / remote sites

2-node clusters with full HA and small footprint

Evaluation and testing

Fastest path to a working VergeOS system


Model 2: HCI + Dedicated Compute (Hybrid 2-Cluster UCI)

Node range: 6--10 nodes | Clusters: 2

This is the hybrid 2-cluster variant of UCI: controller and storage roles stay collapsed on one HCI cluster, while compute is split out into its own cluster. The HCI cluster (Cluster 1) provides all storage via its controller and optional scale-out nodes. The compute cluster (Cluster 2) runs VM workloads without contributing any disks.

Key Design Principles

Cluster 1 -- HCI (Combined)

  • Always includes Nodes 1 & 2 with Tier 0 storage (controllers). - Can include additional HCI scale-out nodes for more storage and compute. - A cluster-level toggle controls whether this cluster also runs VM workloads. - All storage tiers exist in this cluster.

Cluster 2 -- Compute Only

  • Pure compute -- maximum CPU and RAM available for VMs. - Scales independently based on compute demand. - Supports flexible, workload-optimized hardware (GPU nodes, high-memory nodes). - Storage I/O from compute nodes traverses the core fabric to Cluster 1.

Advantages

  • Independent compute scaling without buying unwanted storage.

  • Maintains HCI operational simplicity for the storage layer.

  • Cost-effective -- scale only the resource tier that is growing.

  • Clear growth path to the canonical 3-cluster UCI if needs evolve further.

Limitations

  • Storage I/O from compute nodes crosses the network (adequate core fabric bandwidth is essential).

  • More complex than pure HCI (two clusters to manage instead of one).

  • Requires a decision on whether the HCI cluster should also run workloads.

Ideal Use Cases

Scenario
Why HCI + Compute Works

6--10 node deployments

Sweet spot for the two-cluster model

Compute growth outpacing storage

Add CPU/RAM without expanding disks

GPU or specialized compute

Dedicated compute cluster with passthrough hardware

Cost optimization

Scale only what you need


Model 3: UCI (Ultra Converged Infrastructure) -- Canonical 3-Cluster

Node range: 10+ nodes | Clusters: 3+

The canonical 3-cluster UCI completely separates controllers, storage, and compute into dedicated clusters. Each resource tier is independently scalable and uses hardware optimized for its role. (UCI is an umbrella term for any independent-scaling deployment; Model 2 above is its hybrid 2-cluster variant.)

Cluster Specialization

Cluster
Role
Optimized For

Cluster 1 -- Controllers

Tier 0 metadata, cluster management

High memory (e.g. 768 GB in the Data-Science RA), high-endurance NVMe for Tier 0

Cluster 2 -- Storage

All workload storage (Tier 1+)

Maximum drive density, NVMe or SAS/SATA SSD

Clusters 3+ -- Compute

VM workloads, specialized hardware

Standard, GPU, high-memory, or custom node types

Advantages

  • Maximum performance -- no resource contention between storage and compute.

  • Complete independent scaling -- add storage without compute (or vice versa).

  • Hardware specialization -- right-size hardware per role (NVMe-dense for storage, GPU-equipped for compute).

  • Workload isolation -- different compute clusters for different workload types.

  • Optimal for large-scale and multi-tenant environments.

Limitations

  • Highest operational complexity of all three architectures.

  • Minimum 6 nodes (derived from the 2-node-per-cluster minimum × 3 clusters: 2 controllers + 2 storage + 2 compute).

  • More complex capacity planning across three cluster types.

  • Higher core fabric bandwidth requirements between clusters.

  • Professional services recommended for initial deployment.

Ideal Use Cases

Scenario
Why UCI Works

10+ node enterprise deployments

Independent scaling avoids over-provisioning

AI / HPC / GPU workloads

Dedicated GPU compute clusters, separate from storage

Cloud service providers

Optimize hardware spend per resource tier across tenants

Storage-heavy or compute-heavy growth

Scale only what is growing


Architecture Comparison

Aspect
HCI
HCI + Compute (Hybrid 2-Cluster UCI)
UCI (Canonical 3-Cluster)

Minimum nodes

2

4 (2 HCI + 2 compute)

6 (2+2+2)

Cluster count

1

2

3+

Performance

Good

Better

Optimal

Hardware flexibility

Low

Medium

Maximum

Independent scaling

No

Partial (compute only)

Complete

Specialization

None

Compute only

Full (controller, storage, compute)

Complexity

Low

Medium

High

Resource efficiency

Variable

Good

Maximum

Best fit

Small, balanced

Mid-size, compute-heavy

Large, specialized


Edge Deployment Scenarios

Edge clusters are compact, 2-node VergeOS deployments designed for remote or branch office locations. They use low-power, small form factor hardware and are directly connected (no switches required for the core fabric).

Typical Edge Configuration

  • 2 nodes directly connected via dual NICs (core fabric).

  • Small form factor hardware (Intel NUC, SFF 1L PCs, or similar).

  • 2 TB NVMe for workloads + 4 TB SSD for bulk storage per node.

  • Full HA and redundancy despite the minimal footprint.

Edge Management Models

VergeOS supports three edge management scenarios of increasing sophistication:

  1. Standalone with central management -- 2-node clusters at each site, managed centrally via the Sites dashboard. Catalog Repositories distribute VM recipes from the management cluster to all edge sites.

  2. Centralized backup and DR -- Same as above, plus a central system at the primary data center provides Site Sync replication, ioGuardian repair servers, and centralized snapshot storage for all branch offices.

  3. Multi-tier with archive -- Adds a secondary archive cluster at a DR site for long-term retention using high-capacity HDDs, providing a complete 3-2-1 backup strategy.

When to Recommend Edge

  • Space or power constraints at remote sites.

  • Applications that store data centrally but need local compute.

  • Organizations managing 5--100+ distributed locations.

  • Cost-sensitive branch office deployments.


CSP / Multi-Tenant Scenarios

Cloud Service Providers leverage VergeOS multi-tenancy to deliver IaaS from shared infrastructure. Each tenant operates as an isolated Virtual Data Center (VDC) with its own UI, networks, storage, and access controls.

Typical CSP Configuration

  • 6-node HCI clusters at primary data centers (high-density servers, 768 GB+ RAM per node).

  • Site Sync between data centers for DR.

  • ioGuardian repair servers for automatic block retrieval from remote sites.

  • Global inline deduplication reduces storage consumption across replicated snapshots.

  • Tenant Recipes automate provisioning of complete customer environments (tenant, networks, firewall rules, VMs, storage).

CSP Growth Path

Phase
Deployment
Nodes

Phase 1

2 primary sites with DR via Site Sync

6 per site

Phase 2

Add 2-node edge clusters in new regions

2 per region

Phase 3

Scale out edge sites by adding clusters (illustrative)

varies per site

Phase 4

Add dedicated storage clusters for storage-heavy tenants and archive tiers

2+ storage nodes per site

Key VergeOS Features for CSPs

  • Multi-tenancy with complete isolation between customer environments.

  • Self-service management via web UI and API for tenant administrators.

  • Catalog Repositories for centralized VM recipe management.

  • OpenID Authentication integration with existing identity providers.

  • Tenant Recipes for automated, repeatable customer onboarding.


Network Design Models Overview

The deployment architecture you choose influences your network design. VergeOS supports several network topologies, covered in detail in Module 4: Networking. Here is a brief overview to inform your architecture decision:

Model
NICs per Node
Core Fabric
External Network
Best For

L2 Static + Dedicated Core

4

2 dedicated L2

Bonded L2 (LACP)

Production environments, VMware migrations

L3 Dynamic + Dedicated Core

4

2 dedicated L2

BGP / OSPF / EIGRP advertised

Large-scale, advanced segmentation

L3 Static + Dedicated Core

4

2 dedicated L2

Bonded L3 (static routes)

Large-scale, Layer 3 switching

L2 Static (2 NICs)

2

2 shared (VLAN tagged)

Shared with core (VLAN tagged)

Edge, PoC, small deployments

Key requirements across all models:

  • Core fabric networks must be on dedicated Layer 2 segments (isolated from each other).

  • Jumbo frames (MTU 9216+) on all core fabric switch ports.

  • Zero switch hops between nodes on core fabric -- all nodes must connect to the same switching fabric.

  • STP disabled on core fabric ports.


VMware Bridge

Coming from VMware? VergeOS lets you scale storage and compute independently inside one system — compute-only clusters consume the shared vSAN over the core fabric, with no external SAN/NAS and no separate storage product to license.

Nutanix Bridge

Coming from Nutanix? VergeOS builds pure storage clusters and pure compute clusters in one system — storage runs as an integrated OS service, so there is no CVM consuming RAM/CPU on any node type.

Summary

Concept
Key Takeaway

HCI

Every node does everything. Simple, cost-effective at small scale. Start here.

HCI + Compute

Hybrid 2-cluster UCI: collapsed controller+storage, independent compute scaling.

UCI

Canonical 3-cluster: dedicated controller, storage, and compute. Maximum flexibility.

Edge

2-node direct-connect clusters for remote sites, centrally managed.

CSP

Multi-tenant HCI deployments with Site Sync DR and tenant recipe automation.

Evolution

Same VergeOS installation supports all three models -- grow from HCI to UCI over time.

Next Steps

  • Customer Scoping -- Learn the requirements gathering methodology to translate customer needs into a specific architecture recommendation.

  • Networking -- Deep dive into network design models referenced above.

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