A successful colocation migration looks deceptively simple on the day of the move. Servers come out of one rack, go into a truck, get racked at the new site, power on, and pass traffic. The reality is that the outcome is determined months earlier, in the assessment phase most internal teams underweight.

The colocation market continues to absorb workloads at a healthy clip. Market Growth Reports puts the global colocation market at roughly $76.8 billion in 2025, projected to reach $85.6 billion in 2026 and grow at a compound annual rate of 11.5% through 2035. The drivers are familiar: enterprises winding down aging on-premise rooms, AI buildouts that exceed what a corporate facility can support, and a steady trickle of cloud repatriation. IDC reported earlier this year that 25% of organizations have moved at least one workload off public cloud and back to on-premise or colocation, with cost (54%) and performance (31%) topping the list of reasons.

For operators planning their first physical migration off-premise, or their first in a decade, the lessons from those who have done it cluster around a handful of decisions.

Start with discovery, not procurement

The most common cause of a migration that misses its window is an incomplete picture of what is actually being moved. Migration documentation from phoenixNAP and Flexential both flag the same failure mode: undocumented dependencies. Applications with hard-coded IP addresses, undocumented cross-system calls, a license server nobody remembers configuring, a backup process that only runs because a workstation under someone’s desk wakes up at 2 a.m.

Discovery means an actual inventory: every server, every appliance, every piece of cabling that matters, with model numbers, firmware versions, warranty status, and power draw. It also means tracing application dependencies through network flow data rather than tribal memory. According to IDC, organizations that run formal readiness assessments before migration achieve roughly 2.4 times higher success rates. That figure looks suspiciously round, but the underlying point holds: the work done before talking to a provider determines how useful that conversation is.

This is also the moment to ask which equipment should be retired rather than transported. Servers nearing end-of-warranty, network gear running unsupported firmware, anything overprovisioned for its actual workload: a migration is the cheapest opportunity to rationalize them.

Choose a provider for what you will need in three years

Provider selection tends to over-weight current power and space requirements and under-weight what comes next. The relevant questions extend well beyond the SLA. Power density ceilings matter more than overall facility capacity. Most enterprise stacks still run comfortably in the 5kW to 10kW per rack range, but anything touching AI inference or high-performance computing (HPC) pushes into territory where air cooling stops being adequate.

Rack densities have moved quickly. Industry surveys put average rack density around 12kW per rack in 2024. New AI-optimized facilities are being designed for 50kW to 150kW per rack, with some hyperscale buildouts engineered for racks exceeding 200kW. NVIDIA’s current generation of GPU servers requires roughly 132kW per rack, according to a Schneider Electric analysis cited by CoreSite. If there is any chance an organization will deploy GPU infrastructure during the term of a colocation contract, the facility needs to support direct-to-chip liquid cooling, rear-door heat exchangers, or a clear retrofit path to both. The Liquid Cooling for AI Act of 2025 (H.R. 5332), introduced in Congress last September, is one signal of how seriously regulators are now treating cooling capacity as critical infrastructure.

Beyond cooling, the questions that matter: carrier diversity at the meet-me room, available cross-connects to the major hyperscalers (most enterprises run hybrid architectures and want direct connectivity), redundancy of power feeds, on-site smart hands capabilities, compliance certifications relevant to the workload, and the provider’s track record on actual delivered uptime rather than the SLA number.

Plan the physical move like a logistics operation, because it is

The actual hardware relocation is the most visible part of the migration and, paradoxically, the one most likely to go well. The mechanics are well understood: detailed rack diagrams, labeled cabling, photographs of every connection before disconnection, validated backups, a documented startup sequence, a rollback plan everyone has read.

Three things separate smooth moves from rough ones. First, label discipline. Cables and devices need durable, descriptive labels that identify both endpoints, not adhesive tags that come off in the truck. Second, the cooldown and power-on sequence. Servers do not appreciate sudden temperature swings or out-of-order boot sequences for clustered systems. Third, photographic documentation: when something is missing or miswired at the destination, photos from the source rack save hours of guesswork.

For fragile or high-value equipment, specialist movers are worth the line item. Servers are sensitive to electrostatic discharge, mechanical shock, magnetic fields, and temperature variation. A general freight company is not the right vendor.

Cutover is a network problem more than a hardware problem

Most migrations are framed as a hardware move. The harder part is usually the network: how traffic transitions from the old environment to the new without dropping customer sessions, breaking VPNs, or stranding users on the wrong side of the move.

The standard approaches are well-rehearsed. A staged migration with a temporary high-bandwidth link between sites lets workloads be tested at the destination before final cutover. Plan for at least three times normal production bandwidth during replication windows, a rule of thumb endorsed by most migration playbooks. DNS strategies, BGP failover, load balancer reconfiguration, and certificate updates all need to be sequenced and tested. Cutover windows should be sized for the worst plausible case, not the expected one.

For workloads with hard uptime requirements, parallel running for a defined period (where the workload operates at both sites simultaneously) is more expensive than a hard cutover but considerably less risky.

Validate before declaring victory

Post-migration testing is the step most often compressed when a project runs late. It is also the step that determines whether problems show up the following Tuesday or six months later, when an obscure batch job finally fails.

The validation list should at minimum include: every application’s functional tests, end-to-end transaction tests across system boundaries, backup and restore verification, monitoring and alerting verification, security control validation, and a deliberate failure test on at least one redundant component. The colocation provider’s delivered power, cooling, and connectivity should be measured against contract terms, not assumed.

What to watch

Over the next 18 months, the variable most likely to bend migration plans is AI infrastructure. Even organizations not currently running GPU workloads are being asked to leave room for them. Providers are racing to retrofit liquid-cooling capacity into existing facilities, and lease terms are reflecting it. Future Market Insights estimates colocation now represents 27% of AI-ready data center deployments, a share that has climbed sharply over the past year.

The migration itself is a project. The architecture decisions made during it are a multi-year commitment. Teams that treat them that way generally come out the other side with infrastructure that does not need to be migrated again.