Panzura has announced a data management platform infused with artificial intelligence (AI) that makes it simpler to manage data distributed across multiple clouds.
Company CEO Patrick Harr says Vizion.ai makes use of a data engine deployed as a cloud service through which organizations can consolidate all metadata to prove a single index of all the data stored in a multi-cloud environment to make it easily searchable.
In addition, Harr says the Panzura has baked machine learning algorithms and predictive analytics into the service that make it possible for IT organizations to leverage a software-as-a-service (SaaS) application to determine what data should be stored where, based on cost and application performance requirements. That applies to not just analyzing the difference between on-premises and cloud computing environments, but also various tiers of storage now being routinely provided by cloud service providers.
“There can be as many as four different tiers of cloud storage,” says Harr.https://o1.qnsr.com/log/p.gif?;n=203;c=204663295;s=11915;x=7936;f=201904081034270;u=j;z=TIMESTAMP;a=20410779;e=i
Vizion.ai can also be integrated with open source Elasticsearch software in addition to exposing an application programming interface through which third-party applications can access the analytics generated.
Machine learning algorithms will soon automate a wide range of data management functions. Many of the rote tasks that conspire to consume massive amounts of time for storage administrators will become increasingly automated. That doesn’t mean the role of the storage administrator will disappear. AI technologies present an opportunity for storage administrators to up-level their skills in a way that should enable them to focus more on the policies required to optimize data management. Naturally, making that transition requires new tools. But it’s already clear that the days when storage administrators spent hours optimizing I/O performance by manually managing what data sets are physically stored where are coming to an end.