The Ultimate Guide to AI Infrastructure
A curated Irish edition of TechDay news, analysis, interviews, reviews, job moves, and related resources for AI Infrastructure.
What to know about AI Infrastructure
AI Infrastructure explores the hardware, software, and systems that make modern artificial intelligence possible. This tag covers everything from compute and storage architectures to networking, data pipelines, and observability stacks that keep AI workloads reliable and efficient.
Stories here dig into practical questions: how to design scalable training and inference clusters, choose between GPUs and emerging accelerators, manage feature stores, and orchestrate distributed workloads. You’ll find discussions of MLOps practices, cost optimization, performance tuning, and the trade-offs behind different infrastructure patterns.
Whether you’re building a new AI platform or evolving an existing stack, this tag helps you understand the components, constraints, and design decisions that sit underneath AI products. Reading these pieces will give you concrete examples, architectural patterns, and lessons learned that you can apply to your own systems.
Analyst Insights
Research and market analysis connected to AI Infrastructure
Google tops Gartner's AI infrastructure magic quadrant
Couchbase launches AI Data Plane for enterprise agents
Quali expands Torque for enterprise AI infrastructure
Neocloud providers set to grab AI cloud market share
Linux Foundation sets 2026 confidential computing summit
Featured News
John Margerison on the new class of employee: AI managers
Businesses should treat AI like a new hire, as weak oversight could expose sensitive data and leave staff needing fresh skills to stay relevant.
Exclusive: Virtuozzo sees GPU clouds reshape AI infrastructure
AI demand is pushing cloud providers towards GPU-as-a-service models, with efficiency and utilisation emerging as key differentiators.
Marvell targets AI connectivity bottleneck with NVIDIA boost
AI data centres are hitting copper limits, pushing Marvell and Nvidia towards optics as clusters grow larger and more distributed.
Expert Columns
Interviews
Interviews and video coverage from the networkRecent AI Infrastructure News
Google adds GPU & TPU support to GKE Autopilot
Developers can now run accelerator-heavy AI workloads on managed GKE Autopilot without handling node setup or low-level network allocation.
NVIDIA & LangChain launch open stack for AI agents
Businesses can now build AI agents more cheaply, as the open stack matches top closed models on one benchmark while cutting run costs sharply.
Taara & GSMA launch calculator for middle-mile costs
Operators can now compare middle-mile build costs across fibre, microwave and optical wireless as data demand and AI workloads reshape networks.
Businesses shift from AI pilots to trust & results
Businesses are now weighing whether AI can cut workloads and risks in core operations, rather than just speed up pilots and paperwork.
Fastly joins DIMPACT coalition to track digital emissions
The move could improve carbon accounting for streaming and publishing firms as emissions from content delivery become harder to ignore.
SUSE, NVIDIA & Vultr launch AI Factory for production
Enterprises can now run governed AI workloads faster, as the validated stack aims to cut integration delays and simplify deployment across environments.
Scality & WEKA expand France AI support partnership
French organisations deploying AI workloads will now get local sales and French-language support as Scality takes the front line for WEKA's joint stack.
Google Cloud says firms need AI infrastructure upgrades
Most organisations must upgrade their systems to run agentic AI in production, as cloud costs, governance and energy use climb.
Nvidia pitches national AI factories for governments
Countries risk losing control over data and AI policy unless they build local computing capacity and home-grown models, Nvidia says.
Molted touts operating layer for AI agents in production
As fleets of autonomous agents move into daily use, teams are wrestling with crashes, credentials and recovery that model demos never cover.
AI data centre demand to exceed supply by 500% by 2030
The shortfall is set to intensify competition for power, land and grid connections as AI workloads push global data centre demand far ahead of supply.
Ecolab completes USD $4.75 billion CoolIT takeover
The purchase bolsters Ecolab's push into AI data centres as demand for liquid cooling surges, with CoolIT sales more than doubling this year.
Nvidia launches revenue-sharing AI cloud financing
The new model could ease access to scarce AI computing for startups and cloud providers, while giving Nvidia a recurring revenue stream.
AI boom to leave data centre demand far above supply
AI-driven demand could overwhelm available capacity by 2030, with spending on servers and GPUs pushing supply short of need across key markets.
European data centres back climate-neutral grid plan
Rising AI and cloud demand could strain Europe's power networks unless grids are expanded and low-carbon electricity access improves, the group warned.
NVIDIA backs Verkada as AI security tie-up expands
The investment could speed up AI search and incident review for schools, factories and retailers using Verkada's cloud security platform.
Eleveight AI expands Armenia factory after rapid sell-out
Demand for sovereign AI compute has forced the Gagarin site to expand within weeks, with capacity set to rise to 5MW by year-end.
3Point launches 3AIgent to speed enterprise AI use
Businesses struggling to move AI pilots into daily use may find 3AIgent useful, as it links trusted data, governance and operational control.
Google Cloud touts Lustre cache offload for AI inference
Benchmark tests show Managed Lustre can cut AI inference costs by more than half, easing GPU demand for long-context model serving.
Sijbrandij launches data centre power coalition for AI
AI data centre developers may gain faster power access as a new coalition seeks to ease grid delays and speed site planning.