How to Easily Integrate Your Enterprise with the Cloud
Posted in tech
When we talk to customers about how DataSphere can move data across different types of storage, the conversation quickly turns to whether or not that includes the cloud. The short answer is, yes, absolutely.
Many enterprises are evaluating the cloud because it offers many benefits, including facilitating collaborative work, increasing flexibility and agility with elastic performance and capacity, and providing a cost-effective data archive. And there are also the savings. Sid Nag, of Gartner reports that, "Growth of public cloud is supported by the fact that organizations are saving 14 percent of their budgets as an outcome of public cloud adoption."
Yet, adoption is slow, as Nag noted, “…the aspiration for using cloud services outpaces actual adoption. There's no question there is great appetite within organizations to use cloud services, but there are still challenges for organizations as they make the move to the cloud.”
Let’s take a look at how DataSphere resolves many of these challenges to make it easy for enterprises to accelerate their cloud adoption schedule.
Automating Cloud Archival for Retired Apps and Cold Data
The simplest use case for public cloud storage is as an archive for old data, but even this use case ends up being no small task for enterprise IT. To begin, IT must first identify what data can be safely moved, which requires extensive research into which applications are retired and where their data is located. Then IT must plan migrations around active application use. If data resides on a storage device that is being used by a business-critical application, IT must schedule and perform migration to the cloud during off-hours to protect business continuity. Since data is migrated over the slow connection of the internet, this migration can be a significant project. In fact, enterprises are sometimes even forced to run sneakernets to ensure data is moved quickly and securely.
With DataSphere, enterprises can add cloud storage as another tier in their global namespace. Once the cloud storage is added, DataSphere can automatically load balance cold data to the new cloud resource, according to objectives set by admins. For example, DataSphere can automatically identify data activity and archive any data that has not been active within a time window that IT defines, such as 30 days, six months, or three years. Data can move between on premises storage and one or multiple clouds without disrupting an application's access, even while the data is in-flight.
Importantly, data archival with DataSphere is more
intelligent than typical archival solutions. First, rather than base movement
decisions on simple file creation dates, as is common with popular archival
tools, DataSphere can see whether data is being accessed at all and keep it
on-premises if it has. Second, data is migrated to the cloud only when movement won’t impact other running applications. This protects business continuity, while allowing archive migration to occur around the clock, without IT intervention. WAN optimization ensures transfer times are efficient, as all data that is sent to the Cloud is automatically de-duplicated and compressed. During transfer, a secure link is used to ensure that data remains safe.
Optimized Active Archive Delivers Cloud Cost Savings for Active Applications
Enterprises can achieve significant cost savings by archiving cold data for active applications, as well, but this effort presents three challenges to overcome. First of all, if applications need the data again, IT must scramble to restore it to on-premises storage. Secondly, as public cloud providers typically charge for bandwidth to retrieve stored data, enterprises must consider when the cost to restore data outweighs cost savings. Finally, cloud archive data is typically stored as an object, which means that applications must be modified to use object data.
DataSphere resolves all of these challenges. It ensures data remains accessible and can automatically retrieve it should applications need it again. It also can retrieve single files to minimize bandwidth charges. Conventionally, if a company needed to restore a single file from a backup, they would still need to pay the bandwidth charge to move the entire backup bundle on premises and then rehydrate the bundle to restore the file. If the bundle contained video and audio files, these bandwidth charges could be significant. DataSphere can restore just the file that is needed. The ability to keep data accessible as files also means that enterprises don’t have to modify applications to use object data.
DataSphere gives petabyte-scale enterprises the ability to automate the movement of data from creation to archival, including the integration of public clouds as an active archive. DataSphere also automates many core management tasks, making it easy for companies to maximize storage efficiency and cost savings, while ensuring the performance and protection required to meet service levels.