The largest FUSE platform — dual x86 compute nodes and up to 1.344PB of storage in a single 5U chassis, built for larger data centre deployments that need compute and capacity together.
The Exos AP5U84 is the flagship of the FUSE family — the same 84-bay, 5U chassis behind our EX5U84 SCALE enclosure, but with dual x86 compute nodes built in rather than relying entirely on an external host server. It brings the density of SCALE's largest JBOD together with genuine server-grade processing, aimed at larger data centre deployments where both capacity and integrated compute matter.
A distinctive feature of this platform: with dual controllers installed, the chassis can be split into two independent compute nodes, effectively giving you two separate storage servers sharing one physical enclosure — useful for multi-node architectures or workload isolation without doubling your rack footprint.
The AP5U84 exists for deployments where you need both serious compute and serious capacity in one physical footprint. At up to 1.344PB in a single 5U chassis with integrated AMD EPYC processing, it removes the need for a separate compute tier talking to storage over the network — useful anywhere latency between compute and data matters, or where rack space for two separate systems simply isn't available.
The same drawer-style chassis design and hot-swappable components as the EX5U84 SCALE enclosure carry over here, along with the same practical configuration rules: drive quantities in multiples of 14, and a maximum of two different drive sizes per system. If you outgrow the 84 internal bays, the platform expands using further Exos enclosures rather than requiring a full replacement.
The ability to split dual controllers into two independent nodes is a genuinely distinctive option among the FUSE range — worth considering if you have two workloads that benefit from isolation but don't each need a dedicated chassis.
Need help specifying the right FUSE configuration — or working out whether SCALE, FUSE or PROTECT is the right family for your workload?
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