Infrastructure as a Service (IaaS) & GPU Infrastructure

Compute Capacity Built Around Your Workload

Access compute and GPU-enabled infrastructure around the processing, capacity and deployment requirements of your applications without needing to build and own the complete underlying environment.

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Turn Infrastructure Utilisation Into Better Cost Control

Some applications and compute-intensive workloads need infrastructure capacity that an organisation may not want to purchase, deploy and maintain entirely in-house.

Infrastructure as a Service provides another option.

We begin with the workload, its processing requirements and the environment it needs to operate within. From there, the required compute, GPU, storage, network and access considerations can shape the infrastructure capacity provided.

For AI and other compute-intensive workloads, GPU Infrastructure can provide access to accelerated compute where the requirement genuinely calls for it.

The objective is not simply access to more hardware. It is access to infrastructure capacity appropriate for what the technology actually needs to run.

Pay for the Capacity Your Workloads Actually Need

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Infrastructure ownership can make sense where requirements are stable, predictable and better served through long-term internal capacity.

It is not the only model.

Where workloads require additional, changing or specialized compute capacity, a service-based infrastructure model can provide access to the required environment without making the organization responsible for building every part of the underlying infrastructure itself.

The right model depends on the workload, expected utilization, operating requirements and level of infrastructure control required.

How IaaS & GPU Infrastructure Delivers Real Value

Access Compute Without Building It All In-House

Use infrastructure capacity for defined workloads without requiring complete ownership and deployment of the underlying environment.

Match Capacity to the Workload

Determine compute requirements from what the application needs to process rather than beginning with a predefined infrastructure configuration.

Support Compute-Intensive Workloads

Use GPU-enabled infrastructure where AI, ML or other processing requirements genuinely require accelerated compute.

Reduce Unnecessary Infrastructure Ownership

Consider service-based capacity where purchasing permanent infrastructure would create more ownership than the workload currently requires.

Bring More Than Compute Into the Decision

Account for storage, network, access, deployment and operating requirements alongside processing capacity.

Adjust Infrastructure With the Requirement

Review capacity as workload requirements change rather than committing to infrastructure purely around assumptions about future demand.

Supporting Intensive Workloads Without Excess Infrastructure

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Infrastructure capacity should follow what the application or workload actually needs to run.

We begin by understanding the workload, expected processing requirements, application architecture and relevant deployment considerations.

That creates the basis for determining whether service-based infrastructure is appropriate and what compute environment the workload requires.

Clarify the application, AI workload or other processing requirement together with how the infrastructure will be used.

Determine the relevant processing, memory, storage, network and capacity considerations based on the workload rather than a predefined configuration.

Assess whether the workload genuinely benefits from GPU-enabled compute and what role accelerated processing needs to play within the environment.

Consider whether ownership, dedicated infrastructure or Infrastructure as a Service provides the more appropriate model for the expected workload and operating requirement.

Establish infrastructure capacity according to the agreed workload and deployment requirements using only verified available configurations.

Assess how utilisation and workload requirements evolve and determine whether the infrastructure capacity should remain, change or expand accordingly.

Supporting Intensive Workloads Without Excess Infrastructure

Infrastructure as a Service (IaaS) & GPU Infrastructure Connects to the Wider Transformation Ecosystem

Cloud Migration & Implementation
Managed Cloud Solutions
Infrastructure Consulting & Setup

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Cloud Migration & Implementation

A Structured Transition Into Cloud

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Managed Cloud Solutions

Cloud Environments Managed Around Your Operations

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Infrastructure Consulting & Setup

Design Infrastructure Around What Your Systems Need

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Cloud Migration & Implementation

A Structured Transition Into Cloud

Learn More

Managed Cloud Solutions

Cloud Environments Managed Around Your Operations

Learn More

Infrastructure Consulting & Setup

Design Infrastructure Around What Your Systems Need

Learn More
Explore Our Services

What Better-Aligned Compute Capacity Can Enable

  • Access to compute capacity aligned more closely with actual workload requirements
  • A clearer basis for deciding between infrastructure ownership and service-based consumption
  • GPU-enabled infrastructure considered specifically where accelerated compute is required
  • Infrastructure capacity planned around application and processing requirements
  • Reduced need to build and own every layer of infrastructure internally where that is not necessary
  • Compute, storage, network and deployment requirements considered as connected parts of the environment
  • Infrastructure choices aligned more closely with expected utilisation
  • A clearer relationship between AI workloads and the compute environment supporting them
  • Capacity decisions that can be revisited as application and workload requirements evolve

Infrastructure as a Service (IaaS) & GPU Infrastructure FAQs

Infrastructure as a Service provides access to infrastructure capacity for applications and workloads without requiring the organisation to build and own the complete underlying environment itself. The appropriate capacity and infrastructure model should follow the workload and its operating requirements.

Depending on the verified requirement and available infrastructure, the service can involve compute infrastructure, GPU infrastructure, supporting storage, infrastructure provisioning and capacity required for suitable application or AI workloads. Specific configurations should be confirmed against currently available SumCircle infrastructure.

Infrastructure ownership may make sense for long-term, predictable requirements where the organisation wants direct ownership of the environment. IaaS may be more appropriate where capacity requirements are changing, the organisation does not want to own the complete infrastructure or a service-based consumption model better fits the workload. The decision should be made around the requirement rather than assuming one model is always better.

GPU Infrastructure provides accelerated compute capacity for workloads that genuinely require it. This can include appropriate AI, machine learning and other compute-intensive applications. The workload should be assessed before determining whether GPU infrastructure is required.

GPU-enabled infrastructure can support appropriate AI and machine learning workloads where their processing requirements justify accelerated compute. The AI solution itself remains part of our AI & Data capability. This service focuses on the infrastructure capacity required to run suitable workloads.

We begin with the workload and consider its processing requirements, expected utilisation, application architecture, deployment needs and supporting infrastructure requirements. Specific CPU, GPU, memory, storage or network configurations should only be recommended after those requirements and available infrastructure have been confirmed.

No. Cloud Infrastructure Services focuses on engineering, migrating, deploying and evolving workloads within cloud infrastructure. Infrastructure as a Service & GPU Infrastructure focuses on providing access to compute capacity through a service-based infrastructure model.

No. Private Infrastructure Solutions focuses on designing and implementing dedicated or controlled infrastructure environments where workload, governance or operational requirements justify them. IaaS & GPU Infrastructure focuses on consuming infrastructure capacity without necessarily owning the complete underlying environment.

Infrastructure Consulting & Setup helps determine what infrastructure architecture and capacity a workload requires. Where that assessment determines that service-based compute or GPU capacity is appropriate, IaaS & GPU Infrastructure can provide the relevant infrastructure direction subject to verified availability.

Available GPU models, compute specifications, configurations, capacity, deployment arrangements, pricing and commercial terms should be confirmed directly against current SumCircle infrastructure availability. We do not publish or promise specifications that have not been verified for the requirement.

Scale the Workload, Not the Unnecessary Cost.

Bring us the application, AI workload or compute requirement you need to support. We will help establish what infrastructure capacity the workload requires and whether a service-based compute environment is the appropriate way to provide it.

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