Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include calculating a priority factor with a node autonomous center in a node and computing a node service capability with the node autonomous center. The operations may further include selecting, with the node autonomous center, a task based on the priority factor and the node service capability. The operations may further include directing the task to the node.

Abstract: Embodiments relate to dynamic horizontal autoscaling for a multi-tenant service. According to an aspect, a computer-implemented method includes configuring a network computing element to route a plurality of requests from two or more clients to a service in a containerized-networked system. A horizontal service-level autoscaler monitors one or more aspects of the requests to the service from the two or more clients. A new pod including a set of running containers with shared resources in the containerized-networked system is created based at least in part on the horizontal service-level autoscaler determining that at least one of the one or more aspects of the requests exceeds a threshold. A new service mapping is created to accept subsequent requests from one of the two or more clients that triggered creation of the new pod.

Abstract: Managing an image storage space is provided. A number of processor units identifies a benchmark image in a similar images group. A number of other images not identified in the similar images group as the benchmark image is a set of similar images. The number of processor units creates an image mapping tree. The image mapping tree has a root block for the benchmark image and blocks arranged in a set of layers below the root block based on the set of similar images; the blocks represent portions of the benchmark image; and a plurality of lower blocks in the blocks in a lower layer correspond to subdivisions in an upper block in the blocks in an upper layer. The number of processor units stores a set of selected blocks in the set of similar images that have differences from a set of corresponding blocks in image mapping tree for the benchmark image.

Abstract: Managing an image storage space is provided. A number of processor units identifies a benchmark image in a similar images group. A number of other images not identified in the similar images group as the benchmark image is a set of similar images. The number of processor units creates an image mapping tree. The image mapping tree has a root block for the benchmark image and blocks arranged in a set of layers below the root block based on the set of similar images; the blocks represent portions of the benchmark image; and a plurality of lower blocks in the blocks in a lower layer correspond to subdivisions in an upper block in the blocks in an upper layer. The number of processor units stores a set of selected blocks in the set of similar images that have differences from a set of corresponding blocks in image mapping tree for the benchmark image.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include calculating a priority factor with a node autonomous center in a node and computing a node service capability with the node autonomous center. The operations may further include selecting, with the node autonomous center, a task based on the priority factor and the node service capability. The operations may further include directing the task to the node.