Operations | Monitoring | ITSM | DevOps | Cloud

Pain Killer, Not a Vitamin: What Actually Triggers a DCIM Vendor Switch

Organizations replace their DCIM vendor when an unresolved pain point becomes urgent enough to act on — not because a competing platform has a longer feature list. Understanding what those pain points actually are, for each type of stakeholder in the data center ecosystem, is the clearest way to predict where DCIM displacement is happening now and where vendor stickiness will hold.

How Will PUE Caps In Singapore Change The Way Data Centers Are Managed?

Power Usage Effectiveness has long been used as a metric to calculate data center efficiency. For roughly the last two decades, this popular metric has been used to manage data centers throughout the world. In Singapore, arguably one of the leading data center hubs in Southeast Asia with 1.4 gigawatts capacity, future PUE limits are likely to force operators of both new and existing data centers to modify their facilities and how they are managed.

The Waiting Game for Data Centre Capacity (And How UK Businesses Can Beat It)

UK data centre occupancy hit 91% in 2024, according to Arizton market data, and new capacity is not arriving fast enough to close the gap. Grid connection wait times for new projects now run between five and 15 years, reports Data Center Dynamics, and Savills has attributed the 11% year-on-year drop in new capacity delivery to power constraints rather than a lack of demand or investment. Rising wholesale energy costs are addingpressure to an already tight market.

Cloud cost management: how repatriation improves control for UK enterprises

Hyperscale providers are nothing if not consistent in their temptation of enterprise IT buyers. They bombard leaders with a simple message: migrate to the public cloud, shut down data centres, and enjoy both financial savings and operational agility. However, as UK enterprises have scaled their digital footprints, a more nuanced reality has bitten. Public cloud costs have swollen.

Peak Cloud: Decentralising for resilience

For more than a decade, the prevailing wisdom in enterprise IT was simple: move everything to the public cloud. Hyperscale platforms promised unlimited scalability, lower costs, agility and freedom from the burdens of managing infrastructure. Cloud-first has been rapidly gaining momentum as the de facto path to a modern digital footprint. Until now.

How to Manage AI Infrastructure in Your Traditional Enterprise Data Center

Managing AI infrastructure in a traditional enterprise data center comes down to validating that sufficient capacity exists before hardware arrives, then maintaining accurate infrastructure data to support planning, deployment, troubleshooting, and ongoing operations. This is because AI has changed what enterprise data centers were built to handle.

Toil Reduction Outside the Data Center: Lessons From the Clinical Front Office

Ask an operations team where the week went, and you'll usually get a list of things that shouldn't have needed a person. Access requests provisioned by hand. A disk cleared for the ninth time this quarter. Certificates rotated one at a time because the renewal script was scoped, estimated, and never finished. None of it is difficult, and all of it is necessary. And at the end of the quarter there's nothing to point at, because the work left no trace beyond the absence of an outage.

DCIM in the AI Era: The Now, the New, and the Next of Data Center Infrastructure Management

Data Center Infrastructure Management (DCIM) software is evolving in three overlapping stages: Now (a unified ingestion and observation layer across power, cooling, and IT systems), New (expanded control functions, including bandwidth management), and Next (generative and agentic AI built on top of that monitoring foundation). Understanding which stage a platform actually operates in is the single most useful filter for evaluating DCIM vendors in 2026 and beyond.

Why More UK Firms are Turning to Colocation for their AI Workloads

The last few years have seen AI conversations dominated by the need for investment in hyperscale infrastructure as firms race to build ever larger training models. But as those conversations evolve, the emphasis is shifting to the next phase of AI adoption, focusing on the scaling of use cases and real-world value.

Agentless Auto-Discovery Keeps Asset Records Current Across IT, OT, and Virtual-No Manual Entry Required

Manual asset entry is the hidden drain on your data center’s productivity. That one missed update causes hours of chasing spreadsheets, hunting down equipment details, and doubting if your inventory matches reality. Hyperview’s agentless asset auto-discovery flips the script, delivering real-time asset data across IT, OT, and virtual environments without the manual hassle. Keep your records current effortlessly and focus on running your data center with confidence.