Technology Spreading Resources Thin? Converge IT.
Bring together disparate infrastructure elements & optimize your IT.
Make the most of your infrastructure
Genisys Group engineers use hyper-converged technology to give IT teams back time by removing complicated and inefficient tools and tasks. Capacity allocation, backups and high-availability are included and automated rather than being additional and time consuming.
Scalability and performance
Genisys Group Hyper-Converged solutions bring web scale architectures to our customers’ environments. This means that numerous resource intensive workloads can be managed and grown easily without the need for individual datacenter components to be planned, procured and implemented.
Private cloud and hybrid cloud
Hyper-Converged solutions provided by Genisys Group are integral to creating private cloud environments as customers pool resources and provide internal reporting enabling insight into individual line of business utilization and charge back potential. The nature of these solutions also provides compatibility with public cloud adoption and paves the way for Hybrid Cloud environments. This is all architected and implemented by GGI engineers and specialists.
There are many reasons to adopt hyperconvergence. One is that it is an economical and efficient way to move workloads to a software defined data center. Software defined datacenters abstract the layers of an environment like compute, network, storage and hypervisors. The elimination of the reliance on hypervisors and hardware gives our customers funds back from their budgets that were going to maintenance and renewal costs of legacy architectures.
Hyper-Converged allows organizations to architect their datacenters in a way that allows for resources to be shared and managed in a more efficient, reliable and simpler manner than previously available for x86 workloads. Since hyperconvergence pools resources and automates tasks, companies.
Genisys Group evaluates customers’ existing environments and architects HC solutions which can handle current workload needs while being easily scalable as requirements.