Understanding your VMware estate's complexity, before you decide.

Faced with Broadcom's licensing changes, many organizations have to decide: stay on VMware and optimize, migrate to another platform, or modernize part of the environment. Many are still stuck at the gate: 42% of IT leaders are still working out how to proceed, and preparation, which includes auditing the existing estate, is often the longest phase (Enix). Before choosing any direction, one technical question comes first, the same in every case: what is the real complexity of this environment, with the dependencies and legacy that have built up in it over time? Searches for “vmware exit,” “vmware migration,” and “vmware alternatives” have surged, yet the hard part isn't picking a target, it's honestly knowing your starting point.

A VM inventory gives you a count, not a risk assessment. The real complexity of a migration or a modernization effort comes from elsewhere: accumulated configuration exceptions, undocumented application dependencies, forgotten snapshot or clone chains, orphaned VMs and inherited Shadow IT, manual workarounds turned permanent, leftover physical-to-virtual (P2V) conversion residue and machines “modernized” on the surface but still legacy underneath, platform-specific features (Fault Tolerance, RDM, resource pools), end-of-life operating systems, and downtime tolerance that varies by application tier. These complexity factors, not the VM count, determine whether a project takes three weeks or eight months.

Building that picture today is slow, thankless work. Inventories get assembled by hand, multiple sources get correlated (vCenter, spreadsheets, homegrown scripts, tribal knowledge), already-stretched teams get pinged again. It takes weeks, sometimes months, while the environment keeps moving: the data ages before it is even analyzed. And many are missing that starting point: only 36% have complete visibility of their IT estate, a share that keeps declining year over year (Flexera). Whether done in-house or by a partner, the collection stays manual and one-shot: a single snapshot, already going stale by the time you receive it. And as threats multiply on every side, it is prudent to limit by design how widely sensitive infrastructure data is shared, even with a trusted provider. The result: structural decisions made on a partial, stale, or approximate picture.

Without that picture up front, complexity surfaces mid-execution, one application at a time: a forgotten dependency, an unanticipated platform constraint, and a first application doesn't cut over as planned; then a second. That's often how a project ends up on hold, while everyone catches up on what could have been seen before starting. And the cost lands on both sides: whether you leave or stay, the constraints you never spotted force the plan to change. Per CloudBolt, 63% have changed their VMware strategy at least twice, only 4% have completed a full migration away from VMware, and 41% stay and optimize their estate: trajectories that keep shifting, shaped by technical complexity, cost, and organizational constraints alike. Committing before measuring what actually needs to move risks assessing, or even moving, a large share of an estate that could have stayed put. And once a migration is actually underway, the lost time costs twice over: the old and new environments run in parallel until it's done. On top of that comes compliance pressure: since the VMware licensing clampdown, compliance campaigns and vendor audits have intensified (Network World), making a dated, defensible picture of your actual usage all the more useful. You don't cut that risk by hoping; you cut it by seeing the complexity before you commit.

Whatever the direction, the first step is the same: measure what exists, without being pushed toward any option. VIA is a self-hosted VMware infrastructure analyzer. It connects read-only to vCenter and, if you enable it, reads inside guest VMs (L2/L3) with credentials you provide, then calculates a per-VM complexity score from observable factors (dependencies, configuration, platform constraints), and produces a ready-to-share report. The analysis runs entirely inside your network: no data from your environment is sent automatically, and only what you choose to share (support package, contribution) reaches us. The report presents complexity factors neutrally and traceably, without recommending a destination platform. What used to take months of collection and correlation then happens in a few hours. And because the analysis is deterministic and automated, you can re-run it as often as you want to track how things evolve, whereas a manual assessment remains a single snapshot.