Hewlett Packard Enterprise Development LP

Peter Erik Mellquist

Bret Alan McKee

Frederick Miles Roeling

Bryan E Stiekes

Blaine R Southam

Joao Claudio Ambrosi

Fredrick M Roeling

Raul Ney Da Silva Lima

Victor Hugo Rebelo Rodrigues

Alex Ferreira Ramires Trajano

Raul Lima

Brian Stiekes

Victor Hugo Rodrigues

Alex Ferreira Trajano

Embodiments described herein are generally directed to a controller of a managed container service that facilitates selection among bare metal machines available within a private cloud. According to an example, a request is received by a Container-as-a-Service controller from a CaaS portal to create a cluster based at least in part on resources of a private cloud of a customer of a managed container service. An inventory of bare-metal machines available within the private cloud is received from a Bare-Metal-as-a-Service (BMaaS) provider associated with the private cloud. A particular bare metal machine is identified for the cluster by selecting among the available bare-metal machines based on cluster information associated with the request, the inventory, and a best fit algorithm configured in accordance with a policy established by the customer.

Container-as-a-service (CAAS) controller for private cloud container cluster management

Embodiments described herein are generally directed to a controller of a managed container service that facilitates autoscaling based on bare metal machines available within a private cloud. According to an example, a CaaS controller of a managed container service monitors a metric of a cluster deployed on behalf of a customer within a container orchestration system. Responsive to a scaling event being identified for the cluster based on the monitoring and an autoscaling policy associated with the cluster, a BMaaS provider associated with the private cloud may be caused to create an inventory of bare-metal machines available within the private cloud. Finally, a bare metal machine is identified to be added to the cluster by selecting among the bare-metal machines based on the autoscaling policy, the inventory and a best fit algorithm configured in accordance with a policy established by or on behalf of the customer.

Container-as-a-service (CaaS) controller for monitoring clusters and implementing autoscaling policies

Container-as-a-service (CAAS) controller for selecting a bare-metal machine of a private cloud for a cluster of a managed container service

Example implementations relate to a logical rack controller. In an example, a logical rack controller receives an inventory of a plurality of physical computing racks. The logical rack controller receives a logical rack definition that indicates selected physical infrastructure from among the inventory to form a logical rack. The logical rack controller validates the logical rack definition by verifying network connectivity of the selected physical infrastructure. After validation of the logical rack definition, the logical rack controller provides, to a provisioning controller, an interface to the logical rack. The provisioning controller can utilize the interface to access the logical rack.

Logical rack controller

Container-as-a-service (CaaS) controller for monitoring clusters and implemeting autoscaling policies

Examples include fabric management devices. Some examples include a fabric management device to manage a network fabric. The fabric management device comprises a serial interface to connect to a network device of the network fabric that provides power and data to the fabric management device, a processing resource, and a machine-readable storage medium with instructions executable by the processing resource. The machine-readable storage medium comprises instructions establish communication across the serial interface with the network device via a fabric management device driver, discover a topology of the network fabric, wherein the network fabric comprises a plurality of network devices, and monitor a set of network performance metrics of the plurality of network devices. The machine-readable storage medium further comprises instructions to dynamically configure the network fabric based on the set of network performance metrics.

Fabric management devices

Some examples provide a system to automatically discover network devices. The system enables a network device discovery protocol with a transmit mode and a receive mode on a network device. The system enables an auxiliary communication protocol on the network device. The system broadcasts the network device discovery protocol records from the network device including local neighbors and connectivity information. The system engine processes topological information using the auxiliary communication protocol and timing cycles to update age of a set of topology information records.

Automatic discovery

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Roseville, CA, United States of America

Peter Erik Mellquist