Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.