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Thin disks grow as data is written; traditional thick disks reserve their configured capacity up front. That difference explains why a datastore can appear to lose far more space when a VM is created with thick disks, even if the guest operating system has barely used them. To find what is actually consuming storage, distinguish provisioned capacity from datastore consumption, then account for snapshots, other VM files, storage policies, and any thin provisioning in the storage array.

What “eating the datastore” can mean

Capacity reports can describe different layers, and their numbers are not interchangeable:

  • Configured or provisioned capacity: the maximum virtual-disk size assigned to a VM. A thin disk can have a large configured size while occupying less physical space.
  • Datastore consumption: space currently attributed to files on the datastore. On traditional VMFS, a thick disk can consume its full configured capacity from creation, while a thin disk grows as blocks are written.
  • Storage-array consumption: the physical capacity used by the array’s pool. If both the hypervisor and array provision thinly, the array’s usage may differ from what vSphere reports.
  • Policy-reserved capacity: on vSAN, storage policy reservations and consumption affect reported capacity; they should not be read as though they were traditional VMFS thick allocation.

For a VMFS/VMDK overview, Broadcom explains the provisioning and zeroing behavior in its virtual-disk provisioning documentation. vSAN capacity and policy behavior is discussed separately in VMware’s vSAN space-efficiency overview and vSAN thin-provisioning article.

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How thin and thick virtual disks allocate space

In Broadcom’s vSphere/VMFS terminology, there are three common VMDK types. “Thick” is not a single behavior: lazy-zeroed and eager-zeroed thick disks differ in when blocks are zeroed.

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These descriptions apply to the VMFS/VMDK behavior documented by Broadcom. Check the exact vSphere release, datastore type, storage policy, and array configuration before interpreting a particular capacity figure.

Why thin provisioning can run out of space

Thin provisioning makes it possible for the total configured capacity of virtual disks to exceed the datastore’s physical capacity. That is useful when disks are configured larger than the data guests currently store, but it shifts responsibility to capacity monitoring: if the disks grow faster than available backing space, the datastore can fill.

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Look at both the virtualization layer and the underlying storage pool, especially when the array also provisions thinly. Track available capacity and growth over time, and include snapshots and other VM files in the accounting. Microsoft’s documentation describes thin-provisioning capacity monitoring and allocation-status mechanisms in its thin provisioning overview. VMware’s performance material also cautions that thin-on-thin configurations need careful management: vSphere virtual-machine performance white paper.

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There is no single free-space alarm percentage that fits every deployment. Set alerts with the datastore’s growth rate, the array’s behavior, and the consequences of running out of capacity in mind; use the applicable platform and storage-vendor guidance.

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Does one disk type perform better?

There is no universal performance winner. The key difference is preparation of newly consumed blocks: thin disks allocate and zero blocks as needed; lazy-zeroed thick disks allocate at creation but defer zeroing until first use; eager-zeroed thick disks do both at creation.

That work may affect writes when a workload consumes many new blocks, particularly large sequential writes. Broadcom says ordinary production performance is similar across provisioning types, while large-scale sequential writes can reveal differences. The impact depends on workload, overall system load, the storage array, and how the array handles zero data. Its explanation is in Understanding large-scale sequential write performance in VMDKs residing on VMFS datastores.

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So eager-zeroed thick may avoid first-use preparation during those writes, but converting every disk to that type is not a general application-performance fix. Evaluate the workload and array rather than assuming the provisioning label alone predicts performance.

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How to find what is consuming space

  1. Compare configured capacity with datastore-used capacity. Review each virtual disk’s provisioned size and actual datastore consumption as separate values; a thin disk’s configured maximum is not its current physical use.
  2. Identify the disk type and storage context. Determine whether each VMDK is thin, thick lazy-zeroed, or eager-zeroed thick. Check whether a vSAN policy reservation or array-side thin provisioning changes what the reported figures mean.
  3. Account for files beyond the virtual disks. Check snapshots, swap, and other VM files; disk allocation alone may not explain all datastore usage.
  4. Check capacity at both storage layers. Review datastore free space and growth as well as the underlying array pool, with particular care for thin-on-thin configurations.
  5. Plan conversions before changing a disk. Broadcom advises confirming a valid backup and sufficient target capacity before conversion. Its virtual-disk conversion guidance notes that conversion time depends on array performance.
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Which type should you choose?

  • Choose thin when conserving initial datastore capacity matters and you can monitor growth reliably across the hypervisor and storage array.
  • Choose thick lazy-zeroed when you want disk capacity allocated up front but do not need zeroing completed at creation.
  • Choose eager-zeroed thick when the workload or platform requirement justifies completing allocation and zeroing in advance, and the up-front capacity and creation work are acceptable.

For any of these choices, use the storage platform’s current guidance and the behavior of the specific datastore and array—not the disk label alone—to interpret reservation, consumption, and performance.

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