
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
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Defining the right approach upfront reduces risk, avoids unnecessary complexity and creates a clear path from experimentation to production. Assess current AI, data and HPC capabilities across people, processes and technology.
Assess organisational readiness, identify high-value use cases and establish a practical roadmap for AI adoption.
Define the infrastructure, operating model and governance required to support demanding compute workloads.
Including: Slurm, K8s, MAAS, BCM
Evaluate deployment models and operating costs across cloud, on-premises and hybrid environments.
Including: AWS, Azure, Neoclouds
Navigate a rapidly evolving ecosystem with independent recommendations based on workload requirements rather than vendor preference.
Including: NVIDIA, AMD, Intel
High-Performance Computing projects delivered
HPC projects delivered on time
HPC procurements ranging from £100K to £500 million
Proven track record of customer satisfaction
HPC in the Cloud projects
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.”
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A practical guide to AI infrastructure testing, covering acceptance criteria, FAT, SAT, UAT, performance validation, and risk management for AI


A lot of HPC and AI outages don’t happen solely because of hardware failures. They happen because one person or
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