HPE and Microsoft have joined forces to help the channel bridge private and public cloud services for customers.
HPE's Microsoft Azure Stack solution offers greater flexibility and scalability to businesses, delivered as IaaS and PaaS. The solution allows businesses to seamlessly move workloads between on-premise and Azure public cloud services, but it's the way businesses can pay for the service in a flexible way that makes it so attractive for the channel to sell to customers.
Offering a single pay-as-you-go bill for both on-premise HPE private cloud and Microsoft Azure public cloud will help businesses avoid capital-expenditure-based hardware purchases, which can look unsavoury on a company's balance sheet.
“Many enterprises would like to host Azure within their data centers for performance, security or compliance reasons and many service providers would like to offer Azure-compatible services for data sovereignty or other targeted services,” said Paul Miller, vice president of marketing, Converged Data Center Infrastructure, at HPE.
“HPE is teaming with Microsoft to deliver the right mix of on- and off-premises Azure services with built-in security, operations management, pay-as-you-go pricing and the expertise that provides unmatched flexibility and cost savings for enterprise workloads."
HPE's Microsoft Azure Stack is built on the HPE ProLiant DL380 Azure stack, which will be hosted on-premise and is deployed with HPE's SecureData software. This protects the data whether running through public or private clouds such as Azure, AWS, VMware and OpenStack.
“Microsoft and HPE share a view that hybrid cloud capabilities and consistency across public and private cloud environments helps customers accelerate their cloud strategy,” said Mike Schutz, general manager, product marketing, Microsoft.
“The HPE solution for Azure Stack builds off the relationship we announced last year, tightly integrating the hardware, software, support and services to help customers benefit from the pace of cloud innovation while reducing deployment complexity and risk.”
