Meeting GDPR Requirements for AI Workloads
Does your AI workload data really stay in the EU? With EU AI compliance getting stricter, see where hyperscaler data flows create risk and how to keep AI compute inside your jurisdiction.
See how one company slashed processing times and cut costs by optimizing their big data infrastructure.
There isn't much of a debate when it comes to whether or not the system chosen to process big data can have a huge impact on timeliness, resources and expenses. However, it can be difficult to grasp just how much of a speed-up is possible between the alternatives and with so many options available, selecting the right solution can become daunting.
To illustrate, this case study will delve into one company's struggle with lengthy processing times and their costly expenses as they searched for a better, more effective way of managing their business needs.
Perspectives, mises à jour et histoires de notre équipe
Does your AI workload data really stay in the EU? With EU AI compliance getting stricter, see where hyperscaler data flows create risk and how to keep AI compute inside your jurisdiction.
Kubernetes can introduce hidden lock-in. Explore how upstream OpenStack and Kubernetes preserve portability, control, and sovereignty.
Learn how to run AI workloads on Kubernetes and OpenStack in 2026 with best practices for GPUs, storage, security, and hybrid cloud.