Modern Enterprise Infrastructure.
A collection of expert explainers and practical insights
from HPE, exploring the technologies shaping modern IT
infrastructure, from compute and networking to hybrid cloud,
AI-ready platforms and real-world implementation.
Compute
The systems, servers and storage foundations
modern enterprise workloads depend on.
AI-Ready Servers
Why legacy server estates can hold back AI workloads before projects ever reach scale.
- GPU data bottlenecks
- AI-era security requirements
- Operational visibility across the estate
Why Your Legacy Storage Is Choking Your GPU
Why a starved GPU usually isn't a chip problem — it's storage that can't feed data fast enough.
- Storage as an active throughput engine
- Unified access to cut the copy-and-stage tax
- All-NVMe and GPUDirect paths
Virtualization Modernization
Why modernizing virtualization means rethinking how workloads are placed and managed — not simply replacing one hypervisor with another.
- Workload-first infrastructure decisions
- Consistent operations across hybrid environments
- Security, governance, and phased modernization
Hybrid Cloud
The operating models and platforms that help organisations run infrastructure consistently across on-prem, cloud and edge environments.
Why AI Is Breaking Enterprise Virtualization
Why traditional VM stacks and operating models are struggling to support production AI.
- Bare-metal-like performance demands
- Unified control planes and portability
- Policy, automation, and phased migration
Edge AI
Why running inference close to the data changes what the hardware has to survive and secure.
- Lower latency, cost, and compliance at distributed sites
- Hardware-rooted security for an expanded attack surface
- Centralised management of distributed fleets
Why Hybrid Clouds Break
Why disconnected tools and operating models can make hybrid cloud harder to manage — and how a workload-first approach helps.
- Workload placement based on performance, cost, and governance
- Consistent provisioning, security, and observability
- Managing cloud, on-prem, and edge as one operating model
Networking
The connectivity, fabric and automation
layer supporting modern enterprise environments.
Self-Driving Networks
How AI-driven networking promises to detect, decide, and act with far less human intervention.
- Predictive over reactive operations
- Closed-loop automation
- Experience, resilience, and security
How AI Is Changing Datacenter Network Fabrics
Why AI training traffic breaks traditional hierarchical networks and forces a flatter fabric.
- East-west GPU traffic and non-blocking Clos fabrics
- Ethernet scaling to 800G and beyond
- Intent-based automation across the fabric lifecycle
Why Security Belongs in the Network
Why embedding security directly into the network can improve visibility, enforcement, and threat response across the enterprise.
- Integrated networking and security
- Zero trust, segmentation, and consistent policy
- AI-driven visibility and automated threat response
Video Hands-on Labs
Practical video-led examples showing how modern infrastructure
concepts work in real-world implementation scenarios.
A Day in the Life of
a Self-Driving Network
What autonomous networking looks like in practice — from real-time decisions to continuous optimisation.
- How AI-driven networks detect and resolve issues without manual intervention
- The shift from reactive troubleshooting to predictive, closed-loop operations
- Real-world scenarios showing how automation improves performance, resilience, and user experience
Get Agentic AI
into Production
How enterprises can move agentic AI beyond experimentation and into secure, governed, production-ready environments.
- Moving agentic AI from pilot to production
- Security, governance, and operational control
- Scaling AI infrastructure and workloads efficiently