Introducing Virtual Data Optimizer to Reduce Cloud and On-premise Storage Costs
New to Red Hat Enterprise Linux 7.5, Virtual Data Optimizer (VDO) is a device mapper module which adds data reduction capabilities to the Linux block storage stack. VDO uses inline compression and data deduplication techniques to transparently shrink data as it is being written to storage media.
VDO combines three techniques — zero-block elimination, data deduplication, and data compression — to reduce data footprint. The first of these, zero-block elimination, works by eliminating blocks of data consisting entirely of zeros while the second technique, data deduplication, eliminates identical copies of blocks of data that have already been stored. Finally, data compression is applied, which reduces the size of the unique blocks of data stored. By utilizing these techniques, VDO can dramatically increase the efficiency for both storage and network bandwidth utilization.
VDO can be used to save storage space and reduce costs. Because it’s a feature of Red Hat Enterprise Linux (RHEL), it can be used anywhere RHEL is deployed; similar savings can be seen in both traditional data center and cloud-based deployments.
In the traditional data center, this means you can repurpose storage resources you already have and make more efficient use of future equipment. Enterprise data replication can also benefit from this efficiency since less data on storage means less data to replicate.
In the cloud, VDO allows you to cut storage costs as well. Depending on your deployment needs, this can translate to lower costs per compute instance, lower costs for cloud-based external block storage, and reduced costs for long-term retention of data snapshots. In addition, reduced footprint on premises or in the cloud translates to reduced bandwidth requirements to copy the data to or from the cloud or even between clouds.
The amount of data reduction you will see with VDO will vary depending on the type of data being stored and the workflow that creates and stores the data. Already compressed data types such as video or audio files will not benefit from this technology, but online backups, virtual machine, and container deployments will see substantial benefits. It is not uncommon for users to report 6:1 data reduction rates in mixed container and VM environments using deduplication and compression technologies such as those provided by VDO. Several good candidates for data reduction with VDO are listed below.
Read the entire article here, Introducing Virtual Data Optimizer to Reduce Cloud and On-premise Storage Costs – Red Hat Enterprise Linux Blog
Via the fine folks at Red Hat.