International Business Machines Corporation

Chuan Qing Yu

Wen Jie Wang

Rong Fu

Jian Dong Yin

Hao Sheng

Kang Ed Zhang

Kang Zhang

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.

Dynamic horizontal autoscaling for multi-tenant service

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.

Distributed system workload management via node autonomy

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. The number of processor units store metadata for the set of selected blocks that describes set of paths in the image mapping tree from the set of corresponding blocks in the image mapping tree to the root block.

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Beijing, China

Chuan Qing Yu