Machine Learning
Leverage public clouds to train models, whereas use private cloud for data processing.
Machine learning projects usually involve massive amounts of data used for research and production. With EdgeRay HC, data can be developed on local servers, trained in public clouds to leverage the cloud’s computational power, and then deployed to a private cloud environment for data processing.
Data Security
Deploy their core services on private cloud platforms and front-end services on public cloud platforms.
As enterprises rely more and more on cloud services, data privacy in the cloud is imperative. To comply with industry calls for greater security, enterprises can deploy their core services on private cloud platforms and front-end services on public cloud platforms to protect sensitive data, even while in use and to extend cloud computing benefits to sensitive workloads.
Remote Disaster Recovery
data can be encrypted and backed up to the public cloud to achieve remote disaster recovery without additional IT investment.
The traditional disaster recovery cycle is long and costly. Enterprise services can be simultaneously deployed in private and public clouds to ensure high availability. With EdgeRay HC, data can be encrypted and backed up to the public cloud to achieve a 3-2-1 backup strategy where at least three copies of your data are backed up: one copy to three data centers located in two different locations to achieve remote disaster recovery through redundancy and geographic distance.
Flexibility in Business
Provide smooth expansions for business peaks to reduce maintenance and manpower investment.
Some applications face short-term business expansion needs. Self-built data centers and private clouds often have limited resources that are simply unable to accommodate such changes. With EdgeRay HC’s hybrid cloud expansion capabilities, you can rest easy knowing that flexible coverage is available to support your enterprise.
Machine Learning
Leverage public clouds to train models, whereas use private cloud for data processing.
Machine learning projects usually involve massive amounts of data used for research and production. With EdgeRay HC, data can be developed on local servers, trained in public clouds to leverage the cloud’s computational power, and then deployed to a private cloud environment for data processing.
Data Security
Deploy their core services on private cloud platforms and front-end services on public cloud platforms.
As enterprises rely more and more on cloud services, data privacy in the cloud is imperative. To comply with industry calls for greater security, enterprises can deploy their core services on private cloud platforms and front-end services on public cloud platforms to protect sensitive data, even while in use and to extend cloud computing benefits to sensitive workloads.
Remote Disaster Recovery
data can be encrypted and backed up to the public cloud to achieve remote disaster recovery without additional IT investment.
The traditional disaster recovery cycle is long and costly. Enterprise services can be simultaneously deployed in private and public clouds to ensure high availability. With EdgeRay HC, data can be encrypted and backed up to the public cloud to achieve a 3-2-1 backup strategy where at least three copies of your data are backed up: one copy to three data centers located in two different locations to achieve remote disaster recovery through redundancy and geographic distance.
Flexibility in Business
Provide smooth expansions for business peaks to reduce maintenance and manpower investment.
Some applications face short-term business expansion needs. Self-built data centers and private clouds often have limited resources that are simply unable to accommodate such changes. With EdgeRay HC’s hybrid cloud expansion capabilities, you can rest easy knowing that flexible coverage is available to support your enterprise.