September 10th, 2019 by Adam Armstrong
Spectra Logic StorCycle Unveiled
Today Spectra Logic introduced its new storage management software solution designed for data-driven organizations that need a modern storage lifecycle management workflow, StorCycle. The company makes the claim that its new software solution can reduce the overall costs of data storage by up to 70% through the creation of a Perpetual Tier of storage. Users will still have full access to their data and can combine StorCycle with existing NAS devices, or Spectra hardware or use as standalone software in a public cloud.
Data is growing and becoming more valuable. Companies like Spectra Logic have been refining the ability to store massive amounts of data, however, most data stored is cool or inactive. Up to 80% of data that is gathered my not be of immediate use but is still valuable. Storing this cool data on primary storage is expensive and not very useful in the long run. Spectra StorCycle software automatically tiers the inactive data to a more cost-effective storage medium.
StorCycle works by scanning primary storage data. Once it finds inactive or cool files it automatically migrates them to what is known as a secure Perpetual Tier. The Perpetual Tier is any combination of cloud storage, object storage disk, network-attached storage (NAS) and tape. On this tier, data is protected while still being available for end users if need be. With inactive data moved to the Perpetual Tier, the primary storage tier holds the most critical data and is now small enough to have faster backup and recovery windows giving users a cost and performance benefit.
StorCycle also has a Project Archive feature. This feature allows user to tag and move entire project data sets to a Perpetual Storage Tier. If there is a project that need further analysis, categorization, and comparison it can be moved off of primary storage and securely preserved during these processes. This would be ideal for projects in computational and seismic research, oil and gas studies, semiconductor designs, genomics, media and entertainment, weather forecasting, autonomous vehicle research, and other fields where large amounts of machine-generated data are created.