How to Write a Test Plan for AI Infrastructure
A practical guide to AI infrastructure testing, covering acceptance criteria, FAT, SAT, UAT, performance validation, and risk management for AI
Infrastructure for Production AI Workloads
AI performance is determined long before the first workload runs. Infrastructure decisions shape everything from model training times and cluster utilisation to scalability, resilience and operational cost.
When platforms are built around generic specifications rather than actual workloads, organisations often face performance bottlenecks, underutilised resources and expensive redesigns.
Specialist Expertise
GPU Infrastructure
Design scalable environments for AI training, inference and accelerated computing workloads.
HPC Cluster Architecture
Build environments that maximise throughput, utilisation and researcher productivity.
Storage & Data Architecture
Design storage tiers that support performance, resilience and efficient data movement.
Including: BeeGFS, Lustre, Storage Scale
High Performance Networking
Enable efficient communication between nodes, GPUs and storage systems.
Including: InfiniBand, RoCE, Omni-Path
What Success Looks Like
- Infrastructure aligned to actual workload requirements.
- Reduced deployment risk and rework.
- Improved platform scalability.
- Faster implementation timelines.
- Better utilisation of compute and storage resources.
With unparalleled experience in deploying major, multi-million-pound systems worldwide, Red Oak Consulting stands as a leader in the field.
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High-Performance Computing projects delivered
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HPC projects delivered on time
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HPC procurements ranging from £100K to £500 million
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Proven track record of customer satisfaction
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HPC in the Cloud projects
Red Oak made the whole project go smoothly and they understood our expectation. The Team was very friendly and approachable and showed a high level of professionalism. The Red Oak Team put a lot of effort in the commissioning and it was hugely appreciated.”
Swansea University,
College of Engineering
The procurement was highly successful. Owen was highly professional and highly knowledgeable. And Mark really saved the day for us. Both Owen and Mark smoothly integrated into the KAUST team but more importantly, believed in our mission to deliver this computer in order to support the global ambitions of KAUST and the kingdom of Saudi Arabia.”
King Abdullah University of Science and Technology
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