Ensono Recognized with Honorable Mention in Gartner’s May 2020 Magic Quadrant for Public Cloud Infrastructure Professional and Managed Services, Worldwide
Ensono announced today that it has been recognized with Honorable Mention in Gartner’s 2020 Magic Quadrant for Public Cloud Infrastructure Professional and Managed Services, Worldwide.
“As our clients increasingly seek to unlock the value of the cloud, we continue to invest in the skills of our associates, and the creation of services to enable our clients to transform and do great things,” said Sean Roberts, General Manager, Public Cloud, Ensono. “Ensono Cloud Transform Framework is helping clients on their journey to the cloud. The framework offers clients continuous optimization and the support to adopt new technologies to drive their transformation and innovation.”
According to the report, “public cloud infrastructure as a service (IaaS) delivers compute, storage and network resources in a self-service, highly automated fashion. The leading public cloud IaaS providers also offer platform as a service (PaaS) capabilities and other cloud software infrastructure services as part of a cloud infrastructure and platform services (CIPS, previously referred to by Gartner as integrated IaaS+PaaS) offering.” Further, the report estimates that “by 2025, more than 80% of public cloud managed and professional services deals will require both hybrid cloud and multicloud capabilities from the provider, up from less than 50% in 2020.”
Gartner, Inc., “Magic Quadrant for Public Cloud Infrastructure Professional and Managed Services, Worldwide,” Craig Lowery, To Chee Eng, Scot MacLellan, Ross Winser, Brandon Medford, 4 May 2020.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose