Abstract: In one embodiment, a system has host machines forming a cluster. Each host machine runs containers, where each container includes a segment of hardware resources associated with the host machine, a segment of an operating system utilized by the host machine, and at least one application. Host agents operate on the host machines. Each host agent collects operational parameters associated with the containers on each host machine. A management platform is operative to divide the cluster into container pools, where each container pool includes a sub-set of computation resources in the cluster and has associated container pool metrics including a priority level and computation resource limits. Operational parameters are collected from the host agents. The operational parameters are evaluated in accordance with the container pool metrics.

Abstract: In one embodiment, a system has host machines forming a cluster. Each host machine runs containers, where each container includes a segment of hardware resources associated with the host machine, a segment of an operating system utilized by the host machine, and at least one application. Host agents operate on the host machines. Each host agent collects operational parameters associated with the containers on each host machine. A management platform is operative to divide the cluster into container pools, where each container pool includes a sub-set of computation resources in the cluster and has associated container pool metrics including a priority level and computation resource limits. Operational parameters are collected from the host agents. The operational parameters are evaluated in accordance with the container pool metrics.

Abstract: In one embodiment, a system has host machines forming a cluster. Each host machine runs containers, where each container includes a segment of hardware resources associated with the host machine, a segment of an operating system utilized by the host machine, and at least one application. Host agents operate on the host machines. Each host agent collects operational parameters associated with the containers on each host machine. A management platform is operative to divide the cluster into container pools, where each container pool includes a sub-set of computation resources in the cluster and has associated container pool metrics including a priority level and computation resource limits. Operational parameters are collected from the host agents. The operational parameters are evaluated in accordance with the container pool metrics.

Abstract: In one embodiment, a system has host machines forming a cluster. Each host machine runs containers, where each container includes a segment of hardware resources associated with the host machine, a segment of an operating system utilized by the host machine, and at least one application. Host agents operate on the host machines. Each host agent collects operational parameters associated with the containers on each host machine. A management platform is operative to divide the cluster into container pools, where each container pool includes a sub-set of computation resources in the cluster and has associated container pool metrics including a priority level and computation resource limits. Operational parameters are collected from the host agents. The operational parameters are evaluated in accordance with the container pool metrics.

Abstract: A system and method for performing a resource allocation diagnosis on a distributed computer system includes obtaining a target resource allocation and a snapshot of the distributed computer system, where the snapshot includes configurations and resource usage information of at least some components of the distributed computer system, and generating a resource allocation recommendation based on the target resource allocation and the snapshot by iteratively traversing a resource hierarchy in the distributed computer system. The resource allocation recommendation specifies at least one resource configuration action or at least one capacity expansion action for the distributed computer system to meet the target resource allocation.

Abstract: A system and method for performing a resource allocation diagnosis on a distributed computer system includes obtaining a target resource allocation and a snapshot of the distributed computer system, where the snapshot includes configurations and resource usage information of at least some components of the distributed computer system, and generating a resource allocation recommendation based on the target resource allocation and the snapshot by iteratively traversing a resource hierarchy in the distributed computer system. The resource allocation recommendation specifies at least one resource configuration action or at least one capacity expansion action for the distributed computer system to meet the target resource allocation.