Private Cloud HPC Architecture: Components, Installation, and Best Practices

As computational needs grow, organizations face two choices: public cloud services or full control over their own infrastructure. Private Cloud HPC offers a practical middle ground between these extremes: a dedicated computing platform built in the organization’s own data center, serving multiple teams through a virtualization layer, and mimicking the flexibility of public cloud. This guide covers the core components, installation process, common problems, and best practices for Private Cloud HPC.

Core Architecture Components

Private Cloud HPC consists of several integrated layers. Correct selection of each layer directly affects the overall system performance.

Hypervisor and Orchestration Layer

The two most common choices are OpenStack and VMware vSphere. OpenStack provides an open-source ecosystem with Nova (compute), Neutron (network), Cinder (block storage), and Keystone (authentication) components. VMware vSphere is preferred in more conservative environments due to its enterprise support and mature toolset. The choice should be shaped by existing IT expertise, licensing budget, and long-term vendor dependency tolerance.

Network Infrastructure

Network latency in HPC workloads directly impacts computation times. A typical Private Cloud HPC deployment has three separate network planes:

• Management network: Carries IPMI/BMC access, DHCP/PXE boot, and orchestration traffic.
• Compute network (MPI fabric): Carries communication between MPI processes over InfiniBand HDR (200 Gb/s) or RoCEv2. This network must not be shared with Ethernet — this is critical.
• Storage network: Isolates the I/O traffic of parallel filesystems like BeeGFS or Lustre from the compute network.

Storage Layer

For simulation and analysis workloads requiring parallel I/O, Lustre or BeeGFS is preferred. Object storage (Ceph RGW or OpenStack Swift) is suitable for large datasets and archiving. Storage bandwidth is typically the bottleneck — IOPS and sequential read/write speeds should be evaluated before capacity.

Job Scheduler

SLURM has become the de facto standard for open-source HPC clusters. PBS Pro offers an alternative for organizations wanting commercial support. In SLURM with OpenStack integration, note that virtual nodes have different resource profiles than physical nodes, and this difference must be reflected in partition design.

Hybrid Bare-Metal / Virtual Approach

Pure virtualization can cause significant performance loss for GPU workloads due to virtualization overhead. A hybrid approach is recommended instead: GPU nodes are operated as bare-metal while CPU-heavy workloads are directed to the virtual machine pool.

In SLURM configuration, this separation is defined at the partition level. The GPU partition is assigned to bare-metal nodes, and the CPU partition to virtual nodes on OpenStack. This prevents GPU resource degradation from virtualization latency while enabling flexible scaling for CPU workloads.

Multi-Tenant Management and Security

In enterprise environments, multiple departments or projects need to share the same infrastructure. OpenStack Keystone provides network and resource isolation between projects (tenants). Centralizing user authentication via LDAP or Active Directory integration must be configured separately for both SLURM and the OpenStack identity layer.

From a security perspective, a common mistake is allowing tenant networks to overlap with the management network. Ensure with Open vSwitch rules or security groups that tenant traffic can never access the management plane.

Common Problems and Solutions

MPI Performance Lower Than Expected

The cause is usually MPI traffic being routed over Ethernet instead of InfiniBand. Specify --mca btl_openib_allow_ib 1 and the correct interface name at mpirun startup. Also verify that InfiniBand driver versions match across all nodes.

OpenStack Nova - SLURM Resource Mismatch

After a virtual node restarts or migrates, the SLURM node state may remain DOWN. This requires scontrol update nodename=vnodeXX state=resume. For an automated solution, write an automation script that sends notifications from the OpenStack event stream to SLURM.

Storage Bottleneck

During intensive parallel write operations, the BeeGFS metadata server can become a bottleneck. Keeping metadata and data servers on separate disks and allocating sufficient memory to the metadata server reduces this problem.

Installation Process: Four Phases

A successful Private Cloud HPC project progresses through four phases:

Phase 1 — Requirements analysis and architectural design: Workload profile, security requirements, and budget framework are established; technology selections are finalized.

Phase 2 — Hardware procurement and installation: Hardware matching the reference architecture is procured, installed in the data center, and cooling/power coordination is established.

Phase 3 — Software stack installation: OpenStack or VMware, SLURM, parallel filesystem, and LDAP/AD integration are configured together.

Phase 4 — Training and go-live: System administrators and users are trained; the infrastructure goes live. Optionally, remote monitoring and capacity planning are sustained with a managed support service.

Best Practices

• Always separate network planes physically or logically; never allow MPI traffic to use the management network.
• Avoid virtualizing GPU nodes; even GPU passthrough adds measurable latency compared to bare-metal.
• Monitor CPU, memory, network, and storage metrics per node in real time with Prometheus and Grafana; capacity planning is built on this data.
• Enable Fairshare policy in SLURM to ensure fair resource distribution across departments.
• Configure OpenStack security groups with minimum privilege principle and conduct regular audits.

Private Cloud HPC infrastructure, when properly designed, gives your organization both the multi-tenant flexibility of public cloud and the performance of bare-metal HPC. For more information about architectural options, visit our Private Cloud HPC solution page or speak directly with the Mevasis engineering team via our contact form.