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Colocation
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Colocation

Colocation: a data centre model where the facility owner provides space, power, and cooling to multiple customers who own their own servers.

Last refreshed: 28 June 2026 · Appears in 1 active topic

Key Question

Can colocation providers keep pace with hyperscalers as AI demand strains both grid access and capital?

Timeline for colocation

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Common Questions
What is colocation in data centres?
colocation is a data centre model where an operator leases space, power, and connectivity to multiple customers who install their own servers. It differs from cloud (where compute is virtualised) and from hyperscale (where a single company owns and operates the facility).Source: Lowdown data-centres briefing
How does the AI boom affect colocation providers?
AI training demand has created a new category of colocation tenant: GPU-as-a-service operators who lease racks of GPU servers to AI developers. This has driven record demand for high-density colocation capacity, but grid constraints limit how fast colo providers can build.Source: Lowdown data-centres briefing
What is colocation and how does it differ from cloud computing?
colocation is a facility model where customers own their servers but lease the physical space, power, and connectivity from a third-party data centre operator. Cloud computing, by contrast, means renting compute capacity from a cloud provider that owns all the hardware.

Background

colocation (colo) is the data centre operating model in which a facility owner leases physical space, power, and network connectivity to multiple tenant customers who install their own servers and networking equipment. The largest colocation operators, including Equinix, Digital Realty, and NTT, collectively operate hundreds of facilities globally, providing shared physical infrastructure to thousands of enterprise, cloud, and carrier customers.

colocation sits alongside hyperscale as a distinct segment in the data centre market. While hyperscalers build purpose-built owner-operated campuses, colocation serves smaller enterprises and cloud providers that cannot justify owning a facility. The AI infrastructure boom is reaching colocation through GPU-as-a-service demand: operators including CoreWeave and Lambda Labs lease colocation capacity to run GPU clusters for AI training customers.

Grid-connection constraints affect colocation operators differently from hyperscalers. A colo provider cannot easily shift to behind-the-meter gas generation because it must serve multiple tenants with potentially different power requirements and sustainability commitments. This makes the grid queue problem particularly acute for colocation expansion in constrained markets such as Dublin, London, and Northern Virginia.

More questions
How are colocation data centres being used for AI training?
AI start-ups and GPU-as-a-service operators such as CoreWeave and Lambda Labs lease rack space and power from colocation providers to install dense GPU clusters, avoiding the capital cost of building their own facilities.
Which are the largest colocation data centre operators globally?
The largest colocation operators by number of facilities are Equinix, Digital Realty, and NTT, each running hundreds of sites across multiple continents serving enterprise, cloud, and carrier customers.
Why can colocation providers not simply switch to behind-the-meter power?
Unlike a hyperscaler with a single operator's power budget, a colocation facility serves multiple tenants with different power requirements and sustainability commitments, making it impractical to replace grid supply with onsite gas or renewable generation for the whole building.
Source Material