Building Cloud Infrastructure: Design, Control & Scale

Cloud infrastructure is now powering AI, research, and high‑performance computing (HPC) breakthroughs. However, as workloads become more complex, many organizations have realized that traditional cloud environments (while convenient) limit visibility, efficiency, and control. 

By aligning hardware, software, and orchestration around specific performance and budget goals, when building cloud infrastructure, enterprises can design environments that deliver predictable power, airtight security, and scalable growth. Whether deploying a private cloud for research, extending on‑prem HPC clusters, or building hybrid Kubernetes architectures, success starts with total control of cost, design, and security.

How to Build a Cloud Computing Infrastructure

Unlike off-the-shelf cloud offerings, a purpose-built cloud infrastructure gives you direct control.

 

Whether you’re designing a private cloud for in-house research or building a hybrid model to support on-demand expansion, the process starts with a strategic alignment between infrastructure requirements and business objectives.

Requirements for Building a Cloud Infrastructure

To create a robust and scalable cloud foundation, you’ll need to balance hardware selection, software architecture, and performance tuning. Below are the key components and considerations.

Hardware: CPUs, GPUs, Networking, and Storage

At the heart of any high-performance cloud environment is the hardware. PSSC Labs specializes in designing infrastructure optimized for compute-heavy workloads. That includes:

1. CPUs: Multi-core processors with high clock speeds for data processing and orchestration.
2. GPUs: Acceleration for AI training, simulation, and rendering tasks.
3. High-throughput networking: 10GbE, 25GbE, or InfiniBand for fast node-to-node communication.
4. Storage: Scalable SSD or NVMe options with parallel file systems like Lustre for I/O-intensive applications.

With PSSC Labs, you’re not relying on virtualized hardware from hyperscalers. Instead, you’re getting dedicated, non-virtualized resources engineered to match your specific workload.

Software: Virtualization, Kubernetes, and Orchestration Layers

Once the physical environment is in place, software becomes the glue. Core layers include:

• Virtualization (VMware, KVM): For multi-tenant environments or legacy application compatibility.
• Containers and Orchestration (Docker, Kubernetes): For modern, microservice-driven applications.
• Management tools: Solutions like SLURM (for HPC scheduling), Terraform, or Ansible for deployment and configuration automation.

This is where NZO Cloud excels—giving users complete control over their software environment, enabling them to build highly customized and optimized cloud experiences.

Performance Tuning for HPC Workloads

Cloud infrastructure intended for HPC must be tuned for low latency and high throughput. Best practices include:

• NUMA-aware configuration
• GPU passthrough and driver optimization
• MPI (Message Passing Interface) tuning for distributed jobs
• High-speed scratch storage for large simulations

This kind of tuning ensures your HPC clusters operate at peak efficiency, minimizing bottlenecks and maximizing ROI.

Building a Cloud Infrastructure Step by Step

Whether you’re working with internal IT or partnering with a cloud integrator, these are the foundational steps to building your own cloud.

Step 1: Define Performance and Budget Goals

Begin with clear metrics. What throughput or time-to-completion is acceptable for your simulations or workloads? What’s your capex or opex ceiling? NZO Cloud helps teams model predictable performance aligned with fixed subscription pricing, eliminating surprise charges.

Step 2: Select the Right Architecture (Public, Private, Hybrid)

• Private cloud offers the most control and security.
• Public cloud offers flexibility but less visibility into performance and cost.
• Hybrid cloud blends both, often with on-prem infrastructure (via PSSC Labs) connected to scalable cloud platforms (via NZO Cloud).

Step 3: Choose Hardware and Operating System

Select compute, storage, and network components to match workload intensity. Then layer in your preferred OS—typically a Linux distribution like Ubuntu, CentOS, or Rocky Linux for HPC environments.

Step 4: Set Up Virtualization or Container Orchestration

Decide between virtual machines and containerized workloads. Kubernetes is ideal for cloud-native apps, while tools like SLURM handle large-scale batch jobs. NZO Cloud enables you to deploy custom Kubernetes clusters without sacrificing performance or security.

Step 5: Implement Automation and Monitoring Tools

Use infrastructure-as-code to streamline deployments and updates. Layer in monitoring tools (Prometheus, Grafana, Zabbix) for resource visibility, and integrate security tools like audit logging, IAM, and firewall policies.

Building Your Own Cloud Infrastructure: Benefits and Challenges

Building your own cloud infrastructure is a strategic investment. While it demands careful planning and technical expertise, the payoff is substantial, particularly for organizations with performance-intensive workloads, sensitive data, or strict cost controls. Below, we dive deeper into the key benefits and challenges.

Benefits: Greater Control Over Data, Cost, and Scalability

1. Data Sovereignty and Security by Design

When you own the infrastructure, you own the data pathways. Unlike shared public cloud environments, where data can traverse multiple regions or virtualized layers, a private or custom-built infrastructure ensures:

• Full visibility into where your data is stored and processed.
• End-to-end control over encryption standards, access policies, and compliance frameworks (HIPAA, ITAR, GDPR, etc.).
• Reduced risk of lateral movement attacks or cross-tenant vulnerabilities.

PSSC Labs’ dedicated hardware combined with NZO Cloud’s firewall-first architecture provides clarity and auditability that hyperscalers often obscure behind abstraction layers.

2. Predictable, Transparent Costs

Cloud billing nightmares, like unexpected egress fees, license overages, or instance spikes, are top reasons why cloud projects go over budget. With a self-managed infrastructure or NZO Cloud’s fixed subscription model:

• You avoid variable billing models that penalize success or scale.
• Budgeting becomes easier for long-term planning and multi-year projects.
• You can allocate resources without worrying about per-minute or per-byte charges.

For example, a research lab running simulations can run thousands of jobs without financial anxiety. They know their compute, storage, and bandwidth costs up front.

3. Tailored Scalability and Performance Optimization

Prebuilt cloud instances are generalized by design. But HPC, AI/ML, and engineering workloads require fine-tuned environments:

• Need GPU-to-CPU ratios for deep learning? You can design that.
• Need SSD-backed scratch storage optimized for high IOPS? You can build that too.
• Want guaranteed IaaS performance with no noisy neighbors? Dedicated infrastructure solves it.

With this level of design control—enabled by PSSC Labs hardware and NZO Cloud’s software stack—you can match infrastructure precisely to application requirements, boosting efficiency and reducing overhead.

4. Long-Term ROI and Lifecycle Flexibility

While initial setup costs may be higher, long-term ROI is often better than with pay-as-you-go services. Why?

• Infrastructure amortizes over time.
• Performance bottlenecks are reduced, speeding up time-to-value.
• Cloud lock-in risks are minimized, giving you the freedom to evolve your environment as needs change.

Challenges: Complexity, Security Management, and Ongoing Optimization

1. Infrastructure and Operational Complexity

Designing and deploying your own cloud infrastructure isn’t plug-and-play. You need expertise across:

• Architecture design (CPU/GPU sizing, redundancy, networking).
• Hypervisors or orchestration tools (Kubernetes, SLURM, etc.).
• Integration across storage, compute, monitoring, and automation layers.

Smaller IT teams may struggle without external support. PSSC Labs’ turnkey hardware deployments and NZO Cloud’s onboarding engineers help reduce friction in this situation.

2. Security is Your Responsibility

With great control comes greater accountability. Unlike public clouds, where security is shared, in your own cloud:

• You are responsible for patching, IAM, firewall configurations, and data protection.
• Intrusion detection, compliance auditing, and incident response must be built in.
• Misconfigurations (e.g., open ports, unrestricted S3 buckets) can be fatal.

NZO Cloud helps mitigate this with a secure-by-default stance: dedicated firewall setups, static IPs, the option for private internet access, and Bastion hosts—all configured for your organization alone.

3. Requires Continuous Monitoring and Optimization

Cloud is not “set it and forget it.” To maximize ROI and performance:

• Resource usage needs to be continuously monitored.
• Workloads should be profiled and benchmarked regularly.
• Emerging bottlenecks—such as I/O saturation or memory paging—must be resolved quickly.

This continuous tuning is essential for applications like genomics sequencing, real-time CFD simulations, or LLM inference, where even a small latency or throughput loss impacts results or costs.

4. Potential for Skill Gaps and Longer Ramp-Up

Even with well-designed tools and infrastructure, teams may face internal knowledge gaps. Training on Kubernetes, parallel file systems, and orchestration platforms can take weeks (or months).

NZO Cloud addresses this challenge with preconfigured clusters, detailed training guides, and direct support from onboarding engineers—bridging the gap from “deployment” to “productivity.”

Building Private Cloud Infrastructure for Total Control

The foundation of a private cloud is physical ownership or dedicated access to resources, which can be managed on-premises or hosted in a trusted third-party facility. Here’s what that entails:

1. Use Dedicated Resources for Isolation and Predictable Performance

Dedicated computing eliminates the unpredictability of shared cloud environments. With no virtualized neighbors to compete for CPU cycles or bandwidth, performance is consistent—critical for workloads like computational fluid dynamics (CFD), machine learning, or large-scale simulation.

PSSC Labs offers non-virtualized, bare-metal infrastructure that delivers this kind of repeatable, high-performance experience. Systems can be tailored to specific ratios of CPU, GPU, memory, and storage, and optimized with high-speed interconnects like InfiniBand.

2. Integrate with Existing On-Prem HPC Environments

Private cloud infrastructure doesn’t have to start from scratch. In many cases, it extends existing high-performance clusters by introducing cloud-native features:

• Bursting capacity for peak loads via containerized clusters.
• Shared scheduling using SLURM or Kubernetes across hybrid environments.
• Unified storage using Lustre or other parallel file systems.

This approach allows engineering, research, or analytics teams to scale elastically without losing the investments they’ve made in legacy systems.

Security and Compliance in Private Cloud Builds

For industries like government, healthcare, life sciences, and defense, security isn’t optional—it’s foundational. A private cloud offers maximum visibility and enforcement capabilities.

Dedicated Firewalls and Static IPs

Security starts with isolation at the infrastructure level. PSSC Labs Cloud HPC provides:

• Dedicated firewalls configured for each deployment—no multi-tenant risk.
• Static IP addresses for predictable, whitelisted access patterns.
• Optional Bastion Hosts and private internet access for additional hardening.

These features eliminate the guesswork of shared public cloud settings and give your IT and compliance teams full control over traffic paths, audit logs, and access permissions.

Simplified, Transparent Data Access for Regulated Industries

Knowing exactly where your data resides—and who can access it—is critical for meeting frameworks like FedRAMP, HIPAA, and ISO27001. In a private cloud environment:

• Every connection is traceable.
• Every data transfer is under your control.
• Encryption policies are enforced without compromise.

This transparency is especially important for genomics labs, aerospace contractors, and public institutions handling sensitive datasets.

Building a Future-Proof Cloud Infrastructure

Today’s infrastructure must be ready for tomorrow’s workloads. A future-proof design balances current performance needs with the flexibility to adapt as technologies and use cases evolve.

Component	Key Features	Benefits
Scalable Node Designs & Containerization	Modular, scalable compute nodes  Kubernetes-based orchestration Use of container images for deployment Support for workload mobility	Incremental scaling without disruption Fast, reproducible deployments Efficient resource utilization
GPU Optimization & Accelerated Workflows	GPU-optimized infrastructure (AMD Instinct, NVIDIA) Multi-GPU support for parallel processing AI and simulation workload acceleration	Faster model training Accelerated analytics  Support for large-scale HPC workloads
Modular Architectures That Evolve	Disaggregated compute and storage Upgradeable GPU and storage layers Container-native compatibility	Future-proof design Avoids full rearchitecture Long-term ROI and innovation readiness

Building the Infrastructure for Cloud Security

Security should never be an afterthought when building cloud infrastructure, especially when sensitive data, critical IP, or regulated workloads are involved. While public cloud providers rely on shared responsibility and abstracted controls, a purpose-built cloud infrastructure gives you the power to design security into the architecture itself.

Whether you’re deploying in a private cloud, hybrid model, or federated multi-site environment, security infrastructure must align with your organization’s operations, not the other way around.

Cloud Security Simplified

Traditional public cloud security relies heavily on virtual constructs—shared firewalls, IAM templates, and complex policy layers. While scalable, this model introduces ambiguity: Where does your data go? Who else is on the same hardware? Are default configurations exposing your workloads?

Dedicated Access, Private Connections, and Transparent Data Flow

Security starts with eliminating unnecessary exposure. In a PSSC Labs Cloud HPC deployment:

• Only your organization can access computing and storage, and there is no resource sharing.
• Private network connections can be established using static IPs or physically segmented access layers.
• Data flows are fully traceable, with no reliance on opaque internal routing.

This simplifies compliance reporting, shortens incident response times, and ensures that security teams have complete visibility over every system interaction.

Optional Bastion Box Configurations and Federated Control

To further harden cloud deployments, PSSC Labs includes optional Bastion Box setups—secure, access-controlled gateways that regulate traffic between your users and your cloud nodes. This ensures:

• No direct access to cloud infrastructure from the public internet.
• All administrative access is auditable and restricted by role.
• External users or collaborators can be isolated through segmented zones.

Additionally, organizations can implement federated identity and access controls, allowing centralized management of user roles, keys, and secrets across environments. This is particularly beneficial in multi-team, multi-application deployments with varying security clearances.

Hybrid-Cloud Security Strategies

For organizations embracing a hybrid cloud model, security architecture becomes more complex and important. In these environments, workloads may span on-prem infrastructure, private cloud nodes, and even burst into public cloud services.

The key is understanding the security tradeoffs between shared vs. dedicated infrastructure:

Feature	Shared Public Cloud	Dedicated/Private Cloud (e.g. PSSC Labs)
Resource Isolation	Virtualized	Physical & Guaranteed
Traffic Visibility	Limited (abstracted)	Full Transparency
Access Control	IAM + Role-Based Policies	Custom Firewall + Federated IAM
Compliance Readiness	Requires manual configuration	Built into infrastructure by default
Incident Containment	Multi-tenant risk	Single-tenant containment

Hybrid cloud success depends on clearly delineated trust boundaries and the ability to control data flow between cloud environments. Organizations can confidently operate in a hybrid landscape without compromising security posture by building infrastructure on dedicated resources with NZO Cloud’s access orchestration and PSSC Labs’ hardware controls.

Kubernetes Cloud Infrastructure Build

Containerized applications are the backbone of modern software architecture. Kubernetes has emerged as the de facto standard for orchestration, especially in cloud-native, microservices-driven environments. But when paired with HPC, Kubernetes takes on new strategic value: it enables researchers, engineers, and data scientists to deploy and scale compute-intensive workloads with unprecedented agility.

Building a Kubernetes-ready cloud infrastructure requires more than setting up a cluster. It requires tight integration between hardware, networking, storage, and orchestration tools—all aligned for repeatable, secure, and high-throughput execution.

Building a Kubernetes-Ready Cloud Infrastructure

At its core, Kubernetes automates containerized applications’ deployment, scaling, and management. However, HPC workloads introduce complexities beyond the typical web app or CI pipeline.

Container Orchestration Essentials

To build a robust Kubernetes infrastructure, you need:

• Dedicated compute nodes optimized for predictable CPU/GPU scheduling
• Persistent storage with high IOPS (e.g., NVMe + Lustre)
• High-bandwidth networking to support MPI communication and parallel processing
• Cluster provisioning tools like kubeadm, Rancher, or cloud-native services

PSSC Labs enables this orchestration with bare-metal nodes pre-optimized for containerization, eliminating the performance penalties of virtualized cloud instances. Meanwhile, NZO Cloud offers the control plane flexibility and cost predictability needed to scale Kubernetes clusters with confidence.

HPC + Kubernetes Use Cases

While originally designed for stateless microservices, Kubernetes now supports a range of stateful, performance-intensive HPC applications:

• AI/ML training and inference: Deploying TensorFlow or PyTorch pipelines in scalable GPU-enabled pods.
• Computational Fluid Dynamics (CFD): Running OpenFOAM simulations across nodes with Kubernetes scheduling parallel jobs.
• Genomics and Bioinformatics: Orchestrating bioinformatics pipelines (e.g., Nextflow, Snakemake) with data locality awareness and dynamic pod scaling.

These use cases demand high availability and deterministic performance, which are achievable only when orchestration is coupled with HPC-grade infrastructure.

Kubernetes Cloud Infrastructure Build Optimization

Building the cluster is only half the battle—operational excellence comes from tuning it.

Scaling Pods for HPC Workloads

Unlike typical Kubernetes deployments, HPC applications often run across dozens (or hundreds) of tightly coupled pods. Optimization strategies include:

• Custom pod schedulers (e.g., Volcano, Kube-batch) for gang scheduling
• GPU-aware scheduling for ML jobs using NVIDIA’s device plugin
• Resource quotas and limits to prevent starvation and guarantee throughput

These enhancements help ensure that jobs are not only deployed but also executed efficiently at scale.

Monitoring Tools and Automation Frameworks

Operational observability is critical. Recommended integrations include:

• Prometheus + Grafana for cluster metrics
• ELK/EFK stacks for log aggregation
• Kubecost or Goldilocks for cost and resource optimization
• ArgoCD or Flux for GitOps-based CI/CD

NZO Cloud’s managed Kubernetes environments often come pre-integrated with these tools, allowing teams to focus on workflows, not infrastructure setup.

Designing a Cloud Infrastructure That Scales

A successful cloud infrastructure should be engineered for continuous growth. As organizations evolve, so do their compute and storage demands. Whether scaling to support an expanding research team, onboarding new AI workloads, or integrating multi-site HPC projects, the ability to scale efficiently without degrading performance or blowing through budget is critical.

Elasticity in cloud environments makes it easier to architect for consistent performance, resilient operations, and efficient growth across the entire lifecycle of your workloads.

How to Build Cloud Infrastructure for Growth

To ensure your infrastructure can grow with your organization, it must be built with modularity, workload awareness, and orchestration baked in from the start.

Designing for AI, HPC, and Research Scalability

Unlike traditional enterprise applications, AI, HPC, and scientific research workloads have highly variable and intensive compute demands. Designing for scale in these environments requires:

• High-throughput interconnects: InfiniBand or 100GbE+ networking for fast data movement.
• GPU density planning: Supporting horizontal GPU scaling for deep learning training or inference.
• Disaggregated storage architectures: Decoupling compute and storage to allow independent scaling.
• Workload-specific resource pools: Isolating resources by job type (e.g., simulation vs. inference) to optimize scheduling.

PSSC Labs helps teams deploy physical infrastructure that can scale node-by-node without disrupting existing workflows. At the same time, NZO Cloud provides the orchestration layers to scale containers, virtual clusters, and applications based on real-time demand.

Building Resilient Systems with Automation

Scalability and resilience go hand-in-hand. A system that can grow must also be able to recover, reroute, and adapt under pressure. Automation is the glue that enables this agility.

Failover, Redundancy, and Performance Orchestration

A resilient cloud infrastructure includes:

• Redundant power and networking across racks and zones.
• Cluster-aware monitoring that can detect node failure and trigger automated failover.
• Performance orchestration tools (e.g., Slurm for batch jobs, Kubernetes HPA/VPA for container scaling) to adapt to resource contention in real time.

Automation frameworks such as Terraform, Ansible, or Helm charts streamline repeatable deployments, while monitoring stacks (Prometheus, Grafana, Loki) ensure proactive alerting and response.

NZO Cloud’s High-Performance Benchmarks and Turnkey Setup

NZO Cloud infrastructure is built for rapid deployment and repeatable scale. Key features include:

• Fixed subscription pricing that allows teams to grow without financial volatility.
• Flexible onboarding with a dedicated cloud engineer to set up clusters, security, and orchestration.
• Proven HPC performance benchmarks, eliminating the guesswork from workload planning.

By combining automation and performance consistency, NZO Cloud allows research, AI, and engineering teams to scale with confidence—knowing their infrastructure will perform as expected at every stage of growth.

Conclusion

Designing and building a cloud infrastructure isn’t just about assembling hardware and software—it’s about engineering a foundation for continuous innovation. Organizations can scale without compromise with the right balance of dedicated resources, intelligent orchestration, and security built into every layer.

PSSC Labs provides the dedicated hardware and performance architecture, while NZO Cloud delivers the control plane, cost predictability, and orchestration intelligence to make it all work seamlessly. Together, they empower teams in AI, engineering, and research to build clouds that not only meet today’s demands but also anticipate tomorrow’s.

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