Nutanix certified hardware platforms are designed for use in all hyperconverged infrastructure, hybrid and private cloud solutions.
Workload affinity and close hardware/software integration
Application breadth demands a broad range of vendors, models and configurations
Established customer support model for both Nutanix NX and OEMs
Nutanix Cloud Platform runs on a range of industry standard server models designed to address different workload requirements. Nutanix NX platforms are designed for use in all hyperconverged infrastructure, hybrid and private cloud solutions.
Node models and configurations with different storage types can be mixed in a cluster, enabling organizations to reduce infrastructure silos.
NX platforms include 1-node and multi-node systems for entry-level deployments, balanced compute and storage use cases and .performance-oriented, high-density 1-node platforms.
1. Configured-to-order NX nodes based on workload requirements
2. Rack and cable infrastructure nodes
3. Deploy Nutanix AOS software and choice of hypervisor (dependent on customer choice and geographical location)
4. Finalize software configuration in Prism
5. Deploy workloads
Nutanix 1000 series platforms are designed to span most entry-level deployments and include platforms such as the single socket NX-1120S and the NX-1175S designs, to the multi-node NX-1065.
Nutanix 3000 series platforms are designed to provide a balance between compute and storage capabilities. These platforms are designed for flexible configurations for a range of workloads, including standard server virtualization, private cloud deployments, VDI, and workloads that require GPUs.
At the very top of the NX platform offerings are the 8000 series units. These 1-node platforms offer a variety of high-density compute and storage configurations optimized for applications which require the highest levels of performance.
These systems excel at large scale datacenter solutions and workloads. These workloads can include business-critical applications, databases, big data and analytics and AI/ML workloads.
Prism screenshot of a high performance cluster.
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