Server Nodes Installed in Private Cloud Appliance

At the heart of a Private Cloud Appliance installation are three management nodes configured in a fully active cluster for maximum performance and availability. Each node is capable of running the same controller software and system-level services, and has equal access to the system configuration, so the appliance remains operational in case of individual node failures.

The management nodes, running the controller software, provide a foundation for the collection of services responsible for operating and administering Private Cloud Appliance. Responsibilities of the management cluster include monitoring and maintaining the system hardware, ensuring system availability, upgrading software and firmware, backing up and restoring the appliance, and managing disaster recovery.

The part of the system where the appliance infrastructure is controlled is called the Service Enclave, which runs on the management node cluster and can be accessed through the Service CLI or the Service Web UI. Access is closely monitored and restricted to privileged administrators. For more information, see Private Cloud Appliance Infrastructure Administration. For hardware configuration details of the management nodes, see Main Server Components by Model.

The compute nodes in Private Cloud Appliance are part of the hardware layer and provide the processing power and memory capacity to host compute instances.

When a system is initialized, compute nodes are automatically discovered by the admin service and put in the Ready-to-Provision state. Administrators can then provision the compute nodes through the Service Enclave, after which they are ready for use. When additional compute nodes are installed at a later stage, the new nodes are discovered, powered on, and discovered automatically by the same mechanism. Provisioning, monitoring, and other administrative operations are performed from the Service Web UI or Service CLI.

The minimum configuration of the base rack contains three compute nodes, but it can be expanded by three nodes at a time up to 18 compute nodes, if you choose to use all of your flex bay space for compute nodes. The system can support up to 20 compute nodes in total, with two slots reserved for spares that you can request through an exception process. Contact your Oracle representative about expanding the compute capacity in your system.

For hardware configuration details of the compute nodes, see Main Server Components by Model. For more information about managing compute resources, see Compute Instances.

GPU capacity is added to Private Cloud Appliance by incorporating server nodes containing GPU hardware. GPU nodes are always installed in an expansion rack connected to the appliance base rack.

An X10-2c GPU expansion rack adds 1 to 6 GPU nodes to the Private Cloud Appliance installation. Two expansion racks can be connected to the base rack, for a maximum of 12 GPU nodes.

The X10-2c GPU L40S Compute Server is a 3 RU server with Intel Xeon Platinum 8480+ architecture, high-speed Ethernet connectivity, and four NVIDIA L40S GPUs with 48GB GDDR6 memory and 1466 peak FP8 TFLOPS.

For detailed component specifications, see the manufacturer website.

• Intel Xeon Platinum 8480+ Processor specifications

• NVIDIA L40S GPU data sheet

Unlike standard compute nodes, the GPU nodes are not automatically discovered. After physical installation, and assuming an active high-performance storage pool is present in the appliance configuration, the GPU expansion rack is activated by running a script from one of the management nodes. The script tasks are followed by the node installation process, which prepares the nodes for provisioning.

The new nodes are provisioned from the Service Enclave, using the UI or CLI. When the GPU nodes are up and running, appliance administrators can manage and monitor these in the same way as standard compute nodes. Users must deploy compute instances with a dedicated shape to take advantage of the GPUs. For more information, see Integrating GPU Expansion Nodes. For hardware configuration details of the GPU nodes, see Main Server Components by Model.