Thin Provisioning Using Virtualization

Thin provisioning (TP) is a method of optimizing the efficiency with which the available space is utilized in storage area networks (SAN). TP operates by allocating disk storage space in a flexible manner among multiple users, based on the minimum space required by each user at any given time.

In computing, thin provisioning involves using virtualization technology to give the appearance of having more physical resources than are actually available. If a system always has enough resource to simultaneously support all of the virtualized resources, then it is not thin provisioned. The term thin provisioning is applied to disk layer in this article, but could refer to an allocation scheme for any resource. For example, real memory in a computer is typically thin-provisioned to running tasks with some form of address translation technology doing the virtualization. Each task acts as if it has real memory allocated. The sum of the allocated virtual memory assigned to tasks typically exceeds the total of real memory.

Thin Provisioning is a storage area network (SAN) management process where the storage capacity for a device is reserved and allocated on demand through a shared storage pool.

Thin provisioning is also known as virtual provisioning. However, thin provisioning relates to physical computing environments.

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The efficiency of thin or thick/fat provisioning is a function of the use case, not of the technology. Thick provisioning is typically more efficient when the amount of resource used very closely approximates to the amount of resource allocated. Thin provisioning offers more efficiency where the amount of resource used is much smaller than allocated, so that the benefit of providing only the resource needed exceeds the cost of the virtualization technology used.

Just-in-time allocation differs from thin provisioning. Most file systems back files just-in-time but are not thin provisioned. Overallocation also differs from thin provisioning; resources can be over-allocated / oversubscribed without using virtualization technology, for example overselling seats on a flight without allocating actual seats at time of sale, avoiding having each consumer having a claim on a specific seat number.

Thin provisioning is a mechanism that applies to large-scale centralized computer disk-storage systems, SANs, and storage virtualization systems. Thin provisioning allows space to be easily allocated to servers, on a just-enough and just-in-time basis. Thin provisioning is called “sparse volumes” in some contexts.

Thin Provisioning vs Thick Provisioning

In virtual storage, thick provisioning is a type of storage allocation in which the amount of storage capacity on a disk is pre-allocated on physical storage at the time the disk is created.

This means that creating a 100GB virtual disk actually consumes 100GB of physical disk space, which also means that the physical storage is unavailable for anything else, even if no data has been written to the disk.

Thick provisioning contrasts with thin provisioning, which provisions storage on an as-needed basis. Thin provisioning helps to avoid wasted physical capacity and can save businesses on up-front storage costs. However, thick provisioning has the benefit of less latency because all storage is allocated at once when virtual machines are created.

Arxys | Sentio key data storage features and benefits

Data Acceleration

Acceleration of random writes with Write Log (ZIL)
Hybrid Read Cache with first level in RAM (ARC -Adaptive Replacement Cache) and second Read Cache level on an SSD or NVMe (L2ARC)
High cache hit rate by using ARC’s most recently used (MRU) and most frequently used (MFU) Read Cache algorithms
Data resilvering (rebuilding of used space)
Compression and Deduplication for improved performance

Data Accessibility

iSCSI,Fibre Channel (FC), NFS, SMB (CIFS)
Use of Virtual IPs

Data Availability

High-Availability Dual-Controller Clustering
Active-Active and Active-Passive HA Cluster
Dual Storage (Stretched) Metro HA Cluster and Common Storage Cluster architectures

Data Integrity and Protection

Data and metadata check-summing
Self-healing to detect and correct silent data errors with Scrub utility
Atomic Transaction Writes to keep data consistent
Transactional copy-on-write I/O operations eliminate silent data corruption and data fragmentation
Storing multiple copies of user data