
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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Design scalable operating models that support AI delivery from development through production.
Including: Kubeflow, MLflow
Build secure, resilient platforms for model training, deployment and management.
Including: Kubernetes, OpenShift
Establish processes for monitoring, governance and continuous improvement.
Including: MLflow, Weights & Biases
Support development teams working with leading machine learning frameworks.
Including: PyTorch, TensorFlow, JAX
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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